565 Generative Ai Jobs - Page 12

Job Title: AI Technical Lead Location: Bengaluru, work from Avaali office Employment Type: Full-time Reports to: CTO Key Responsibilities 1. Develop and Execute AI Initiatives Collaborate closely with business stakeholders at all levels to identify and implement AI-driven solutions that address key pain points and deliver measurable outcomes. Actively participate in multidisciplinary and cross-functional (fusion) teams to support the entire lifecycle of AI projectsfrom ideation to execution. Stay on top of cutting-edge AI trends, innovations, and best practices in the industry while leveraging these insights to deliver impactful solutions. 2. Design and Implement AI Solutions Architect AI-based solutions that align with Avaali's vision of operational cost optimization and margin improvement for clients. Ensure that all AI solutions are scalable, secure, governed, and adhere to applicable regulations and compliance standards. Create personalized solutions aligned with specific business requirements and ensure the delivery of high-quality outcomes. 3. Build and Scale the AI Practice in collaboration with the CTO Develop and implement standardized methodologies, frameworks, and best practices to drive consistency and excellence across AI initiatives. Create knowledge-sharing forums, training modules, and certifications to upskill internal teams and establish Avaali as a center of excellence for AI. This person would support the CTO in this area (he/she will be an important team member in this activity) Required Skills and Competencies Deep knowledge of AI/ML technologies, frameworks, and platforms, including hands-on experience with AI-based tools and cloud ecosystems. Strong expertise in designing enterprise-class AI systems that balance innovation with security, governance, and compliance needs. Proven track record of managing large-scale AI initiatives across industries, including successful implementation of impactful solutions. Outstanding analytical and problem-solving skills combined with a strategic mindset that embraces emerging opportunities. Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. Advanced degrees preferred. Minimum 8 years of experience including in AI leadership roles, ideally including consultancy or enterprise environments. Demonstrated success in building and scaling AI capabilities and teams. Experience defining and managing budgets for AI initiatives while delivering cost-effective outcomes. Benefits of Joining Avaali Be a key player in driving transformational change in cutting-edge industries. Work with a highly skilled and innovative team eager to push the boundaries of what AI can achieve. Opportunity to develop AI solutions with real-world impact, empowering businesses to thrive in a digital-first era. If you are ready to shape the future of AI at scale, we invite you to apply for this role.

Role & responsibilities Architect and implement AI/ML solutions tailored to client-specific business problems using Gen AI (e.g., LLMs like GPT, Gemini, Mistral) and traditional ML models (e.g., scikit-learn, XGBoost). Collaborate with client stakeholders to understand requirements, define problem statements, and translate them into scalable AI/ML solutions. Present demos and proof-of-concepts (POCs) to clients, showcasing the value of AI/ML in real-world scenarios Mentor and guide a cross-functional team of data scientists, ML engineers, and developers Drive best practices in model development, deployment, and monitoring Stay abreast of the latest advancements in Gen AI and ML, and evaluate their applicability to client use cases Contribute to internal knowledge bases and reusable solution accelerators Preferred candidate profile Strong programming skills in Python and experience with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn). Hands-on experience with Gen AI platforms and LLMs (e.g., OpenAI, Gemini, LLaMA, Mistral). Proven track record of deploying ML models in production environments (cloud/on-prem). Experience with API development, data pipelines, and dashboarding tools like Streamlit. Familiarity with DevOps and MLOps practices for model lifecycle management. Excellent communication and stakeholder management skills. Tools: LLM, SLM, Vector DB, Graph DB, Airflow, MLFlow, MLOps tools, NLP, KG, ML models (Regression, Clustering, Classification etc), LangChain, LangGraph, AutoGen

Job Description: Lead Solution Architect with experience in government programs preferred The candidate is expected to play the role of an expert level Technical Solution Architect in large programs The resource should mandatorily have minimum 10 Years experience in solution planning and system architecture designing with at least 5 years of experience as a Lead Architect for Analytical Systems The resource should have demonstrated extensive experience in the use of various techniques to develop robust data warehouse business intelligence AI solutions which have significant weightage to statistical and advanced analytics Key Responsibilities: ROLE AND RESPONSIBILITIES As a Principal Technical Solution Architect lead the engagement efforts at different stages from problem definition to diagnosis to solution design development deployment in large government implementation programs Create detailed design and architecture and process artifacts implement the solution and the deployment plan Connect with senior client business and IT stakeholders demonstrating thought leadership in domain process and technology Contribute to Unit and Organizational initiatives and COEs REQUIRED SKILLS AND EXPERIENCE Domain process functional technical Strong hands on and in depth knowledge of Data Analytics module Strong understanding of the Data Warehousing Business Intelligence AI solutions good understanding of airlines industry Thorough understanding of Agile methodologies Good understanding of business processes in the airlines domain or with government organizations Experience in leading and driving Business process workshops and Fit GAP analysis Should have working experience in a highly regulated environment Should be aware of release governance processes and have experience in working on any incident management tool Preferred Skills: Technology->Machine Learning->Generative AI,Technology->Machine Learning->AI/ML Solution Architecture and Design->traditional ai ml

7-10 years of experience in machine learning, deep learning. Experience End-to-end architecture design for machine learning solutions Deployment of AI models into scalable services Staying at the forefront of generative AI advancements Optimizing models for performance and scalability Collaborating with cross-functional teams for successful project delivery Degree in Computer Science, Information Technology, Electrical Engineering, or related field Experience or understanding of machine learning, deep learning, generative AIand MLOps Knowledge of deep learning techniques and frameworks (TensorFlow, PyTorch) Familiarity with cloud platforms, preferably Microsoft Azure A certification in AI or machine learning is advantageous Strong analytical and problem-solving skills Excellent communication and team collaboration abilities

Job Summary We are seeking highly skilled Sr. Backend Developers with an experience of 8 - 12 years to join our dynamic team. The ideal candidates should have strong expertise in Node.js , along with experience in Python, Generative AI (Gen AI) , and Natural Language Processing (NLP) preferred. Additionally, experience working with MongoDB, AWS Lambda, and cloud-based deployments is required. Key Responsibilities: Design, develop, and maintain scalable applications using Node.js and Python. Implement and optimize NLP models and Gen AI solutions for various applications. Develop and manage RESTful APIs and microservices using Node.js. Work with MongoDB for database management and optimization. Deploy and manage applications in AWS Lambda and other AWS services. Collaborate with cross-functional teams to integrate AI-driven solutions into the platform. Troubleshoot and debug applications, ensuring high availability and reliability. Required Skills & Experience: 8-12 years of hands-on experience in Backend Development using Node Js. Strong proficiency in Python, especially in AI/ML frameworks (TensorFlow, PyTorch, etc.). Experience working with Natural Language Processing (NLP) or Generative AI models. Proficiency in MongoDB, including database design and performance tuning. Hands-on experience with AWS Lambda and serverless architectures. Strong knowledge of REST APIs, GraphQL, and microservices. Experience with Docker, Kubernetes, and CI/CD pipelines is a plus. Ability to work in an Agile environment and collaborate with remote teams

What Your Responsibilities Will Be Lead and manage a team of AIML engineers, overseeing project lifecycles from conception to deployment, ensuring high-quality standards and timely delivery. Mentor and develop team members, providing guidance on technical challenges, career development, and professional growth opportunities. Stay abreast of the latest AIML technologies and methodologies, incorporating new and innovative approaches into our projects to maintain competitive advantage. Develop and execute our AIML strategy, aligning with the company's objectives, and ensuring the team's projects support this vision. Collaborate with cross-functional teams, including product management, engineering, and design, to define project requirements, set priorities, and allocate resources effectively. Ensure operational excellence, implementing best practices in project management, software development, and quality assurance to optimize team performance and productivity. Manage stakeholder communications, providing regular updates on project status, key milestones, and any challenges or risks, ensuring alignment and support across the organization. What You'll Need to be Successful Specific Qualifications Proven expertise in Gen AI technologies and methodologies, with a strong portfolio of projects demonstrating your ability to apply these in solving complex problems. Experience with building and deploying to enterprise production environments APIs powered by AI Machine Learning systems. Proficiency in programming languages relevant to AI ML, such as Python, R, Java, Scala, C++ and familiarity with AI ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Experience with cloud computing platforms (AWS, Azure, Google Cloud) and understanding of how to leverage these for scalable, secure, reliable distributed systems with complex workflows relying on AI ML solutions. Strong background in data engineering and familiarity with database technologies, as well as, data processing / ETL pipelines and visualization tools. General Qualifications Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related science field. A minimum of 10 years of experience in AI ML with at least 5 years in a leadership or management position, overseeing technical teams. Excellent project management skills, with experience in agile methodologies.

Experience working closely with other data scientists, data engineers' software engineers, data managers and business partners. 7+ years in designing, planning, prototyping, productionizing, maintaining knowledge in Python, Go, Java, SQL knowledge

Role Summary The Ecosystem Engineering Technology Engineer is responsible for guiding and supporting partners in embedding, sell-to, resell, and influence scenarios with IBM's strategic technologies. Activities include deal support with partners selling to clients and co-creating with partners (Joint Solutions, Assets, embedding of IBM technology). The Technology Engineer is part of a cross-functional team that delivers a unique co-creation experience for partners to accelerate and scale the embedding and use of IBM's strategic technologies to/in partner solutions. They use contemporary technologies and approaches to design, develop, test, and co-deliver solutions across the IBM Technology platform; They work closely with the Ecosystem Engineering: Solution Architect(s) to determine the feasibility of the solution and collaborate with the partner's and other Technology Engineers to implement a comprehensive solution. Ecosystem Technology Engineers are asked to specialize in a brand or set of capabilities to provide deep technical skills in their area of expertise. Required Education Bachelor's Degree Preferred Education Bachelor's Degree Required Technical and Professional Expertise Expert level knowledge in IBM Business Automation suite of products (CP4BA - RPA, BPM - BAW, Process Mining, FileNet) . Very good understanding of Generative AI (IBM watsonx platform or equivalent) . Hands-on coding experience in Python, Java, Node.js, JavaScript, React . Agentic AI framework will be an added advantage. Excellent communication and presentation skills.

Your role and responsibilities Back end development with GoLang Expertise in Kubernetes/OpenShift, Cloud service providers. Knowledge of Generative AI, and ability to integrate AI to applications. Ability to pick up new areas based on business requirements Excellent communication skills Required education Bachelor's Degree Required technical and professional expertise 6+ years of overall experience in backend development. Excellent understanding of system design and best practices. 6+ years of application development with GoLang development. Good level of expertise in Kubernetes or OpenShift, use of Docker/Podman and Cloud service providers. Good level of knowledge of CNI, container native storage. Expertise in Version Control - Git Experience using cloud technologies (AWS/GCP/Azure/IBM Cloud) Experience with Ansible and Shell scripting Proficient in Linux administration. Experience of IaC (Terraform) Expertise in Version Control - Git Design functional DevOps application lifecycle. Good understanding of CICD pipelines such as Jenkins. Should have hands-on in writing and debugging Jenkinsfile Experience using build tools such as Maven, Gradle, Make, Ant Knowledge of AI - Pytorch, TensorFlow, Scikit,Generative AI, and ability to integrate AI functionalities to applications. ABOUT BUSINESS UNIT IBM Systems helps IT leaders think differently about their infrastructure. IBM servers and storage are no longer inanimate - they can understand, reason, and learn so our clients can innovate while avoiding IT issues. Our systems power the world's most important industries and our clients are the architects of the future.Join us to help build our leading-edge technology portfoliodesigned for cognitive business and optimized for cloud computing.

Design, develop, & optimize AI-powered apps Implement large language models (LLMs) & generative AI apps Integrate Copilot Studio, Azure AI Search, and other AI/ML platforms into enterprise solutions RAG (Retrieval-Augmented Generation) architecture Required Candidate profile 7+ yrs of exp in Python, C#, Java, JavaScript, C++ Generative AI capabilities Strong .NET Full Stack exp 3+ yrs of experience as Full Stack Developers & AI exposure can apply not a Data Scientist role

Requirement Role: ML Engineer/Data Scientist Experience: 3 to 15 Years Job Description: Responsibilities: Strong understanding of ML algorithms, techniques, and best practices. Strong understanding of Databricks, Azure AI services and other ML platforms and cloud computing platforms (e.g., AWS, Azure, GCP) and frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Strong understanding of Mlflow or Kubeflow frameworks Strong programming skills in python and Data analytical expertise Experience in building Gen AI based solutions like chatbots using RAG approaches Expertise in any of the gen ai frameworks such as Langchain/ Langgraph, autogen, crewai, etc. Requirements: Proven experience as a Machine Learning Engineer, Data Scientist, or similar role, with a focus on product matching, image matching, and LLM. Solid understanding of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on experience with product matching algorithms and image recognition techniques. Experience with natural language processing and large language models (LLMs) such as GPT, BERT, or similar architectures. Optimize and fine-tune models for performance and scalability.. Collaborate with cross-functional teams to integrate ML solutions into products. Stay updated with the latest advancements in AI and machine learning.

Technical Lead AI & Data Warehouse (DWH) Pando is a global leader in supply chain technology, building the world's quickest time-to-value Fulfillment Cloud platform. Pandos Fulfillment Cloud provides manufacturers, retailers, and 3PLs with a single pane of glass to streamline end-to-end purchase order fulfillment and customer order fulfillment to improve service levels, reduce carbon footprint, and bring down costs. As a partner of choice for Fortune 500 enterprises globally, with a presence across APAC, the Middle East, and the US, Pando is recognized as a Technology Pioneer by the World Economic Forum (WEF), and as one of the fastest growing technology companies by Deloitte. Role As the Senior Lead for AI and Data Warehouse at Pando, you will be responsible for building and scaling the data and AI services team. You will drive the design and implementation of highly scalable, modular, and reusable data pipelines, leveraging big data technologies and low-code implementations. This is a senior leadership position where you will work closely with cross-functional teams to deliver solutions that power advanced analytics, dashboards, and AI-based insights. Key Responsibilities Lead the development of scalable, high-performance data pipelines using PySpark or Big Data ETL pipeline technologies. Drive data modeling efforts for analytics, dashboards, and knowledge graphs. Oversee the implementation of parquet-based data lakes. Work on OLAP databases, ensuring optimal data structure for reporting and querying. Architect and optimize large-scale enterprise big data implementations with a focus on modular and reusable low-code libraries. Collaborate with stakeholders to design and deliver AI and DWH solutions that align with business needs. Mentor and lead a team of engineers, building out the data and AI services organization. Required 8-10 years of experience in big data and AI technologies, with expertise in PySpark or similar Big Data ETL pipeline technologies. Strong proficiency in SQL and OLAP database technologies. Firsthand experience with data modeling for analytics, dashboards, and knowledge graphs. Proven experience with parquet-based data lake implementations. Expertise in building highly scalable, high-volume data pipelines. Experience with modular, reusable, low-code-based implementations. Involvement in large-scale enterprise big data implementations. Initiative-taker with strong motivation and the ability to lead a growing team. Preferred Experience leading a team or building out a new department. Experience with cloud-based data platforms and AI services. Familiarity with supply chain technology or fulfilment platforms is a plus.

Role: ML Engineer Experience: 3 to 15 Years Chennai location must or relocation also fine- Hybrid mode We have good budget Job Description: Responsibilities: Strong understanding of ML algorithms, techniques, and best practices. Strong understanding of Databricks, Azure AI services and other ML platforms and cloud computing platforms (e.g., AWS, Azure, GCP) and frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Strong understanding of Mlflow or Kubeflow frameworks Strong programming skills in python and Data analytical expertise Experience in building Gen AI based solutions like chatbots using RAG approaches Expertise in any of the gen ai frameworks such as Langchain/ Langgraph, autogen, crewai, etc. Requirements: Proven experience as a Machine Learning Engineer, Data Scientist, or similar role, with a focus on product matching, image matching, and LLM. Solid understanding of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on experience with product matching algorithms and image recognition techniques. Experience with natural language processing and large language models (LLMs) such as GPT, BERT, or similar architectures. Optimize and fine-tune models for performance and scalability.. Collaborate with cross-functional teams to integrate ML solutions into products. Stay updated with the latest advancements in AI and machine learning.

AI Engineer & Lead This role is a blend of technical innovation, strategic consulting, and hands-on problem-solving, making each day varied, challenging, and impactful. Exp: 3-8 Years Location: Chennai & Hyderabad Organization: Intellect Design Arena - Product Company ------------------------------------------------------------------------------------------------------------- About Intellect Design Arena Limited Intellect Design Arena Ltd is an enterprise-grade financial technology leader, providing composable and intelligent solutions for futuristic global financial institutions across 57 countries. Intellects revolutionary First Principles Thinking-based Enterprise Connected Intelligence Platform, eMACH.ai, is the most comprehensive, composable, and intelligent open finance platform in the world. With an impressive array of 329 microservices, 535 events, and over 1757 APIs, eMACH.ai enables financial institutions to design and deploy future-ready technology solutions that provide a significant global competitive edge. With three decades of domain expertise, Intellect offers a full spectrum of banking and insurance technology products through four lines of business: Global Consumer Banking (iGCB), Global Transaction Banking (iGTB), IntellectAI and Digital Technology for Commerce (iDTC). Intellect is a pioneer in applying Design Thinking and our 8012 FinTech Design Center, the world's first Design Center dedicated to Design Thinking Principles, underscores our commitment to continuous and impactful innovation, addressing the ever-growing need for digital transformation. We proudly serve over 325+ customers worldwide, supported by a diverse workforce of solution architects and domain and technology experts in major global financial hubs. Summary: As an AI Engineer, you will work directly with clients to own the implementation of AI solutions using our AI platform. You will build and deploy end-to-end AI workflows, taking projects from concept to production, and solving complex, real-world challenges at scale. Your insights and learnings from client engagements will directly contribute to the evolution of our platform, ensuring we stay at the forefront of AI innovation. You will play a key role in expanding our presence into new markets and problem spaces unlocked by Generative AI. Key Responsibilities: Deliver Production-Ready AI Solutions: Design and deploy AI Agents, data processing pipelines, that are robust, scalable, and suitable for real-world applications. Solve Real Business Problems: Focus on practical AI solutions that address tangible business challenges, moving beyond theoretical approaches. Collaborate Across Teams: Work effectively with both technical and non-technical stakeholders to ensure clear communication and smooth project execution. Adapt in Dynamic Environments: Operate comfortably in fast-paced, evolving settings, adjusting quickly to shifting objectives and direct user feedback. Drive Innovation and Growth: Embrace an entrepreneurial mindset, continuously learning, innovating, and striving to make a high impact in a rapidly changing field. Client Interaction and Strategy Development: Engage with clients to understand their challenges, develop AI strategies, and translate their needs into actionable technical solutions. Deploying Solutions to Production: Move AI workflows from prototype to production, ensuring they integrate smoothly into client environments and solve real-world problems. Iterating and Improving: Continuously enhance deployed solutions based on feedback and evolving requirements, focusing on debugging, performance improvement, and workflow adaptation. Contributing to Platform Evolution: Share field insights to influence the development of new features and capabilities within the AI platform, aligning it with market needs. Key Traits: Technical Proficiency: Expertise in building and deploying AI models, data pipelines, and advanced analytics in production environments. Problem-Solver: Ability to design practical, impactful AI solutions that address real business challenges, focusing on tangible outcomes Collaborative: Effective communication skills to work with diverse teams, including technical and non-technical stakeholders, and explain complex AI concepts in understandable terms. Adaptable: Comfortable working in dynamic, fast-paced environments with evolving objectives, quickly iterating on solutions based on feedback. Innovative and Entrepreneurial: Passion for continuous learning, innovation, and applying an entrepreneurial approach to drive impact and growth. Client-Focused: Strong ability to engage directly with clients, understand their needs, and align AI strategies with business objectives. Detail-Oriented: Focus on refining, testing, and fine-tuning AI solutions for optimal performance in real-world settings. Continuous Learner: Commitment to staying updated on the latest AI technologies, tools, and methodologies, exploring new approaches to keep skills and solutions cutting-edge. Skills and Qualifications: Proven experience developing solutions using Generative AI models, with a strong understanding of the AI landscape and related technologies. Solid foundation in Machine Learning principles, including evaluation, training, and problem decomposition. Strong background in engineering or a related technical field such as Computer Science, Mathematics, Software Engineering, Physics, or Machine Learning. Proficiency in programming languages such as Python, Java, C++, JavaScript/TypeScript, or similar. Interested folks can reach out to bicky.nath@intellectdesign.com

Experience: 10+ years overall | Minimum 10 full-cycle AI/ML project implementations, including GenAI experience Role Summary: We are seeking a AI Architect to lead strategic AI transformation initiatives within the retail domain. This role demands deep hands-on experience in AI, Machine Learning (ML), and Generative AI (GenAI), along with the ability to engage directly with C-level stakeholders, align technical delivery with business objectives, and drive enterprise-wide adoption of advanced AI solutions.The ideal candidate is a techno-strategic leader who can take AI/ML/GenAI projects from ideation to productionbuilding architectures, leading cross-functional teams, and ensuring regulatory and operational alignment in retail environments.Key Responsibilities:Consulting & Business Alignment Partner with senior business and IT leadership, including CIOs, CDOs, and COOs, to identify high-impact use cases across e-commerce, retail operations, supply chain, and customer experience. Translate complex retail challenges into technically feasible and scalable AI/ML/GenAI solutions. Create strategic roadmaps, capability assessments, and PoV/PoC execution plans that align with business KPIs and regulatory needs. Solution Architecture & Delivery Leadership Design and lead delivery of AI/ML/GenAI pipelines covering data ingestion, model training, validation, deployment, and monitoring. Build and scale GenAI-based solutions like LLM-driven chatbots, intelligent product recommendation engines, RAG pipelines, summarization tools, and virtual assistants. Architect cloud-native AI platforms using AWS (SageMaker, Bedrock), Azure (ML, OpenAI), or GCP (Vertex AI, BigQuery, LangChain). Define and implement MLOps and LLMOps frameworks for versioning, retraining, CI/CD, and production observability. Ensure adherence to Responsible AI principles, including explainability, bias mitigation, auditability, and compliance with retail regulations (GDPR, CCPA, SOC2, etc.). Engineering & Integration Work closely with data engineering teams to acquire, transform, and pipeline data from retail systems, customer databases, inventory management systems, and real-time feeds. Design architecture for data lakes, feature stores, and vector databases supporting AI and GenAI use cases. Enable seamless integration of AI capabilities into enterprise workflows, customer platforms, and decision engines via APIs and microservices. Required Skills & Experience: 10+ years of experience in AI/ML, data engineering, and cloud architecture. Minimum of 5 end-to-end AI/ML project implementations from use case discovery through to productionization. Proven expertise in: (Any One) AI/ML frameworks: scikit-learn, XGBoost, TensorFlow, PyTorch GenAI/LLM platforms: OpenAI, Cohere, Mistral, LangChain, Hugging Face, vector DBs (Pinecone, FAISS, Chroma) Cloud platforms: AWS, Azure, GCP including AI/ML & GenAI native services MLOps/LLMOps tools: MLflow, Kubeflow, SageMaker Pipelines, Vertex AI Pipelines Strong experience with data security, governance, model risk management, and AI compliance frameworks relevant to retail. Ability to lead large cross-functional teams and engage both technical teams and senior stakeholders.

Position : Customer Success Manager US B2B SaaS Location: Bangalore (HSR Layout) Time Zone - Night Shift (Hybrid Model) Experience: 2+ years Salary : Negotiable Job Description What You'll Do Be the face of the company post-sale leading customer relationships and ensuring ongoing value delivery. Identify and pursue upsell/cross-sell opportunities, partnering with Sales to close. Lead customer onboarding and implementation, ensuring smooth handoffs and successful adoption. Conduct weekly/biweekly syncs and Quarterly Business Reviews (QBRs) to track progress, align on goals, and maintain executive buy-in. Ensure timely resolution of customer queries with in-depth product knowledge and a problem-solving mindset. Drive advocacy through referrals, testimonials, case studies, and co-marketing initiatives. Orchestrate executive dinners, micro-events with Sales to deepen engagement and foster trust. Collaborate closely with Product, Operations, and Sales to deliver a seamless and high-impact customer experience. Continuously gather product feedback and market insights to help shape our roadmap. What We're Looking For Minimum 2 years of experience in a Customer Success or Account Management role in B2B SaaS targeting the US market. Proven track record managing mid to high ACV accounts ($60K$200K) with strong stakeholder engagement. Strong background in engineering services sales, SaaS, or AI-driven business solutions. A mindset defined by customer obsession, speed, and ownership you go the extra mile. Excellent communication, relationship-building, and organizational skills. Bonus: Experience working with AI-powered products or in fast-paced startup environments. Interested candidates kindly share your CV and below details to usha.sundar@adecco.com 1) Present CTC (Fixed + VP) - 2) Expected CTC - 3) No. of years experience - 4) Notice Period - 5) Offer-in hand - 6) Reason of Change - 7) Present Location -

Role Purpose The purpose of this role is to develop minimum viable product (MVP) and comprehensive AI solutions that meet and exceed clients expectations and add value to business. Do Manage the product/ solution development using the desired AI techniques Lead development and implementation of custom solutions through thoughtful use of modern AI technology Review and evaluate the use cases and decide whether a product can be developed to add business value Create the overall product development strategy and integrating with the larger interfaces Create AI models and framework and implement them to cater to a business problem Draft the desired user Interface and create AI models as per business problem Analyze technology environment and client requirements to define product solutions using AI framework/ architecture Implement the necessary security features as per products requirements Review the used case and see the latest AI that can be used in products development Identify problem areas and perform root cause analysis and provide relevant solutions to the problem Tracks industry and application trends and relates these to planning current and future AI needs Create and delegate work plans to the programming team for product development Interact with Holmes advisory board for knowledge sharing and best practices Responsible for developing and maintaining client relationships with the key strategic partners and decision makers Drive discussions and provide consultation around product design as per customer needs Participate in client interactions and gather insights regarding product development Interact with vertical delivery and business teams and provide and correct responses to RFP/ client requirements Assist in products demonstration and receive feedback from the client Design presentations for seminars, meetings and enclave primarily focused over product Team Management Resourcing Forecast talent requirements as per the current and future business needs Hire adequate and right resources for the team Talent Management Ensure adequate onboarding and training for the team members to enhance capability & effectiveness Build an internal talent pool and ensure their career progression within the organization Manage team attrition Drive diversity in leadership positions Performance Management Set goals for the team, conduct timely performance reviews and provide constructive feedback to own direct reports Ensure that the Performance Nxt is followed for the entire team Employee Satisfaction and Engagement Lead and drive engagement initiatives for the team Track team satisfaction scores and identify initiatives to build engagement within the team Deliver No.Performance Parameter Measure 1.Continuous technical project management & deliveryAdoption of new technologies, IP creation, MVP creation, Number of patents filed, Research papers created 2.Client CentricityNo. of automation done, On-Time Delivery, cost of delivery, optimal resource allocation 3.Capability Building & Team Management % trained on new age skills, Team attrition %, Number of webinars conducted (internal/external) Mandatory Skills: Generative AI.

Role Purpose The purpose of this role is to develop minimum viable product (MVP) and comprehensive AI solutions that meet and exceed clients expectations and add value to business. Do Manage the product/ solution development using the desired AI techniques Lead development and implementation of custom solutions through thoughtful use of modern AI technology Review and evaluate the use cases and decide whether a product can be developed to add business value Create the overall product development strategy and integrating with the larger interfaces Create AI models and framework and implement them to cater to a business problem Draft the desired user Interface and create AI models as per business problem Analyze technology environment and client requirements to define product solutions using AI framework/ architecture Implement the necessary security features as per products requirements Review the used case and see the latest AI that can be used in products development Identify problem areas and perform root cause analysis and provide relevant solutions to the problem Tracks industry and application trends and relates these to planning current and future AI needs Create and delegate work plans to the programming team for product development Interact with Holmes advisory board for knowledge sharing and best practices Responsible for developing and maintaining client relationships with the key strategic partners and decision makers Drive discussions and provide consultation around product design as per customer needs Participate in client interactions and gather insights regarding product development Interact with vertical delivery and business teams and provide and correct responses to RFP/ client requirements Assist in products demonstration and receive feedback from the client Design presentations for seminars, meetings and enclave primarily focused over product Team Management Resourcing Forecast talent requirements as per the current and future business needs Hire adequate and right resources for the team Talent Management Ensure adequate onboarding and training for the team members to enhance capability & effectiveness Build an internal talent pool and ensure their career progression within the organization Manage team attrition Drive diversity in leadership positions Performance Management Set goals for the team, conduct timely performance reviews and provide constructive feedback to own direct reports Ensure that the Performance Nxt is followed for the entire team Employee Satisfaction and Engagement Lead and drive engagement initiatives for the team Track team satisfaction scores and identify initiatives to build engagement within the team Deliver No.Performance Parameter Measure 1.Continuous technical project management & deliveryAdoption of new technologies, IP creation, MVP creation, Number of patents filed, Research papers created 2.Client CentricityNo. of automation done, On-Time Delivery, cost of delivery, optimal resource allocation 3.Capability Building & Team Management % trained on new age skills, Team attrition %, Number of webinars conducted (internal/external) Mandatory Skills: Generative AI.

Job Description: Minimum 2 years of hands-on experience in Generative AI (GenAI), including working with various LLMs, prompt engineering, fine-tuning, Retrieval-Augmented Generation (RAG), and deploying GenAI solutions in production environments. At least 3 years of experience in Python and SQL, with strong fundamentals in data manipulation and backend logic. Good experience with AWS AI/ML services[ Comprehend, Bedrock, Textract, SageMaker, Lambda, and DynamoDB ] OCR and ML model development/maintenance experience, including experience in productionizing and monitoring ML models Hands-on experience with Docker, including containerization of ML workloads and deployment in scalable environments. Experience using AWS Step Functions for orchestrating production-level AI workflows and infrastructure automation. Deep knowledge of AWS CloudFormation, with experience in using it for setting up production-grade infrastructure. Proficiency in C++ , especially for performance-critical components or integration with legacy systems. CI/CD pipeline development and maintenance using Git, with best practices for version control and automated deployments.

Key Responsibilities: Develop and maintain backend services and APIs using Java (Spring Boot preferred). Integrate LLMs and GenAI models (e.g., OpenAI, Hugging Face, LangChain) into applications. Collaborate with data scientists to build data pipelines and enable intelligent application features. Design scalable systems to support AI model inference and deployment. Work with cloud platforms (AWS, GCP, or Azure) for deploying AI-driven services. Write clean, maintainable, and well-tested code. Participate in code reviews and technical discussions. Required Skills: 35 years of experience in Java development (preferably with Spring Boot). Experience working with RESTful APIs, microservices, and cloud-based deployments. Exposure to LLMs, NLP, or GenAI tools (OpenAI, Cohere, Hugging Face, LangChain, etc.). Familiarity with Python for data science/ML integration is a plus. Good understanding of software engineering best practices (CI/CD, testing, etc.). Ability to work collaboratively in cross-functional teams.

Job Title: Full Stack Developer Generative AI Range: 5-10 Years Location: Noida Job Summary We are seeking a Senior Full-Stack Developer to join our Architecture Practice at Xceedance. In this role, you will design and develop AI-powered applications using Python, .NET Core, Angular, and Azure. You will work on integrating AI models, building scalable cloud-native systems, and leveraging tools like GitHub Copilot, Azure Foundry, Agentic frameworks to accelerate development.This is a hands-on role at the intersection of full-stack engineering and AI innovation, including agentic AI, AI-assisted SDLC, and other emerging technologies. Key Responsibilities Full-Stack Development Build scalable backend services using Python and .NET Core (Web APIs, Entity Framework). Develop responsive frontend applications using Angular (13+) and Stream lit for rapid AI tool prototyping. Integrate AI/ML and LLM models into end-to-end application workflows. AI-Driven SDLC Use AI coding assistants like GitHub Copilot or Code Whisperer to enhance development speed and code quality. Automate testing, code analysis, and deployment using CI/CD pipelines and AI tools. Cloud Deployment Deploy and manage applications on Azure (App Services, Functions, Azure SQL, AI Studio). Implement microservices and event-driven architectures in collaboration with solution architects. Collaboration & Leadership Mentor junior developers on AI/ML integration and modern development practices. Contribute to architectural decisions and technical strategy. Required Skills & Qualifications 5-8 years of experience in web-based application development. Mandatory 5+ years of full-stack development experience with Python and .NET Core. 3+ years of frontend development using Angular, TypeScript, and RxJS. Hands-on experience integrating AI/ML models (e.g., scikit-learn, PyTorch) into production applications. Proficiency in Azure cloud services (App Services, Functions, Azure SQL). Preferred Experience with AI coding tools like GitHub Copilot or CodeWhisperer. Familiarity with Streamlit for AI/ML UI prototyping. Knowledge of Azure Machine Learning, LLM fine-tuning (e.g., GPT, Claude). DevOps skills: CI/CD, Docker, Infrastructure as Code (IaC). Education and Experience Bachelors degree in computer science, Engineering, or a related field (or equivalent practical experience). 58 years of hands-on development experience, including 2+ years in AI/ML projects. Portfolio or GitHub showcasing work in Python, .NET, Angular, and AI/ML (preferred).

We are seeking a highly skilled AI Architect to lead our team in developing cutting-edge generative AI solutions. This role requires a deep understanding of AI/ML concepts, strong technical expertise, and exceptional leadership abilities. As the Lead AI Architect, you will be the technical authority responsible for defining the strategy, architecture, and execution of cutting-edge generative AI initiatives. You will lead a talented team, driving the development of innovative solutions from concept through production deployment. This role demands a deep understanding of state-of-the-art AI models, advanced techniques like Retrieval-Augmented Generation (RAG) and fine-tuning, robust MLOps practices, and scalable cloud deployment strategies. Responsibilities: 1. Technical Vision & Architecture: a. Define and champion the technical vision and architectural roadmap for generative AI solutions (LLMs, Diffusion Models, Multimodal Models, etc.). b. Design, architect, and guide the development of sophisticated generative AI systems, incorporating techniques like fine-tuning, prompt engineering, and Reinforcement Learning from Human Feedback (RLHF). c. Architect and implement advanced Retrieval-Augmented Generation (RAG) pipelines, including vector database selection/optimization, chunking strategies, and multimodal RAG approaches. d. Ensure solutions are scalable, performant, cost-effective, reliable, and adhere to responsible AI principles (fairness, transparency, security). e. Stay relentlessly current with academic research and industry advancements in generative AI, MLOps, and related technologies, integrating relevant innovations. 2. MLOps & Lifecycle Management: a. Lead the design and implementation of robust MLOps pipelines for the entire generative AI lifecycle: data ingestion/preprocessing, model training/fine-tuning, validation, versioning (data, code, models), automated deployment, and continuous monitoring. Job Opening b. Establish best practices for model evaluation, performance tracking, drift detection, and ongoing optimization of generative models in production. c. Champion automation, reproducibility, and governance across all AI/ML workflows. 3. Deployment & Integration : a. Oversee the deployment of fine-tuned models and complex AI systems into scalable production environments using cloud platforms (AWS, GCP, Azure, potentially NVIDIA AI Enterprise). b. Design and implement containerized deployments (Docker, Kubernetes) and serverless architectures for AI model serving. c. Develop robust APIs (RESTful, gRPC) for seamless integration of AI capabilities into broader applications and services. d. Optimize models for inference speed and cost efficiency. 4. Leadership & Collaboration : a. Lead, mentor, and inspire a team of AI/ML engineers and data scientists. b. Collaborate closely with product managers, software engineers, data engineers, and business stakeholders to translate requirements into actionable AI strategies and technical designs. c. Effectively communicate complex technical concepts, architectural decisions, and project status to both technical and non-technical audiences, including executive leadership. d. Foster a culture of innovation, experimentation, and continuous improvement within the AI team. Qualifications : • Typically 8-10+ years of hands-on experience in designing, building, and deploying production-grade AI/ML systems, with a significant recent focus (3+ years) on Generative AI. • Generative AI Expertise: Deep understanding and practical experience with foundational models (e.g., GPT series, Llama series, Stable Diffusion, multimodal models), transformer architectures, and key techniques like fine-tuning, prompt engineering, and RAG. • RAG Proficiency: Proven experience architecting and implementing RAG systems, including familiarity with vector databases (e.g., Pinecone, Weaviate, Milvus, ChromaDB) and embedding techniques. • MLOps Mastery: Demonstrable experience designing, building, and managing end-to-end MLOps pipelines using relevant tools and platforms (e.g., MLflow, Kubeflow, Vertex AI Pipelines, SageMaker Pipelines, Azure ML). • Programming & Frameworks: Expert-level proficiency in Python and core AI/ML libraries/frameworks (e.g., PyTorch, TensorFlow/Keras, JAX, Hugging Face ecosystem, LangChain, LlamaIndex). • Cloud Platforms: Strong hands-on experience with at least one major cloud provider (AWS, GCP, Azure) and their associated AI/ML services (e.g., SageMaker, Vertex AI, Azure Machine Learning). • Deployment Skills: Experience with containerization (Docker, Kubernetes), API development (REST, gRPC), and model serving/optimization techniques. • Leadership: Proven track record of technical leadership, mentoring teams, and successfully delivering complex AI projects from ideation to production. • Communication: Excellent verbal and written communication skills, with the ability to articulate complex technical ideas clearly and concisely. • Methodologies: Familiarity with Agile development practices and version control systems (Git). • Education: Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or a related quantitative field. (PhD preferred but not required). Preferred Qualifications: • Education: Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or a related quantitative field. (PhD preferred but not required). • Experience with multimodal generative models and RAG. • Experience with distributed training and large-scale model optimization (e.g., quantization, pruning). • Familiarity with data engineering tools and platforms (e.g., Spark, Kafka, Airflow). • Contributions to relevant open-source projects or publications in top AI/ML venues.

Sr. Full Stack Developer AI & Cloud Experience Range: 5–8 Years Location: Noida Job Summary We are looking for a Senior Full-Stack Developer to join our Architecture Practice. This role involves designing and developing AI-powered applications using Python, .NET Core, Angular, and Azure. You will be at the forefront of building scalable, cloud-native systems and integrating advanced AI models into modern web applications. You'll also leverage tools like GitHub Copilot , Azure Foundry , and agentic frameworks to accelerate delivery. This is a hands-on role that blends full-stack development with AI innovation , including agentic AI, AI-assisted software development lifecycle (SDLC), and other emerging technologies. Key Responsibilities Full-Stack Development Build scalable backend services using Python and .NET Core (Web APIs, Entity Framework). Develop responsive frontend applications using Angular (13+) and Streamlit for rapid AI tool prototyping. Integrate AI/ML and LLM models into end-to-end application workflows. AI-Driven SDLC Use AI coding assistants like GitHub Copilot or CodeWhisperer to boost development productivity. Automate testing, code analysis, and deployment with CI/CD pipelines and AI tools. Cloud Deployment Deploy and manage applications on Azure (App Services, Functions, Azure SQL, AI Studio). Implement microservices and event-driven architectures in collaboration with solution architects. Collaboration & Leadership Mentor junior developers in AI/ML integration and modern software engineering practices. Contribute to architectural planning and overall technical strategy. Required Skills & Qualifications Mandatory 5+ years of full-stack development using Python and .NET Core . 3+ years of frontend development with Angular , TypeScript , and RxJS . Experience integrating AI/ML models (e.g., scikit-learn, PyTorch) into production systems. Hands-on with Azure services: App Services, Functions, Azure SQL. Preferred Familiarity with GitHub Copilot or CodeWhisperer . Experience using Streamlit for AI/ML UI prototyping. Exposure to Azure Machine Learning , LLM fine-tuning (e.g., GPT, Claude). DevOps skills including CI/CD , Docker , and Infrastructure as Code (IaC) . Education & Experience Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience). 5–8 years of hands-on software development experience, including at least 2 years on AI/ML projects. A portfolio or GitHub demonstrating full-stack and AI/ML projects (preferred).

Note: Need candidate only from Startup, Banking, Fintech, Product Based We are not looking for NIT or IIT or VIT Candidates. Please don't apply. Required Qualifications: 1+ years of software engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications: Work as a Generative AI engineer developing enterprise-scale AI applications Design, implement, and optimize LLM-based solutions using state-of-the-art frameworks Lead Gen AI initiatives focused on developing intelligent agents and conversational systems Design and build robust LLM interfaces and orchestration pipelines Develop evaluation frameworks to measure and improve model performance Implement prompt engineering techniques to optimize model outputs Integrate Gen AI capabilities with existing enterprise applications Build and maintain frontend interfaces for AI applications Strong proficiency in Python/Java and LLM orchestration frameworks (LangChain, LangGraph) Basic Knowledge of model context protocols, RAG architectures, and embedding techniques Experience with model evaluation frameworks and metrics for LLM performance Proficiency in frontend development with React.js for AI applications Experience with UI/UX design patterns specific to AI interfaces Experience with vector databases and efficient retrieval methods Knowledge of prompt engineering techniques and best practices Experience with containerization and microservices architecture Strong understanding of semantic search and document retrieval systems Working knowledge of both structured and unstructured data processing Experience with version control using GitHub and CI/CD pipelines Experience working with globally distributed teams in Agile scrums Job Expectations: Understanding of enterprise use cases for Generative AI Knowledge of responsible AI practices and ethical considerations Ability to optimize AI solutions for performance and cost Well versed in MLOps concepts for LLM applications Staying current with rapidly evolving Gen AI technologies and best practices Experience implementing security best practices for AI applications

Develop Tableau reports using advanced SQL queries and ETL processes Seamless integrating with AI models and different components Exp in embedded analytics. Exp in connecting tableau with React JS Exp in Tableau Desktop, Tableau Server.