20 Aws Bedrock Jobs

About the Role: We are seeking a visionary AI Architect to drive our AI/ML and GenAI roadmap. You will lead the design of multi-modal generative workflows that combine image, video, and LLM-driven tasks for media workflow automation. This role will influence our core platform strategy by integrating custom and open-source diffusion models, prompt-to-image generation, segmentation, and agentic task orchestration using LLMs. Key Responsibilities: Architect AI solutions for image/video generation, segmentation, pose estimation, and retouching using diffusion models and GANs. Design agentic workflows leveraging LLMs (OpenAI, Claude, etc.) for orchestrating creative task chains, model prompting, or hybrid AI-human loops. Lead data pipeline and preparation strategy define data requirements, build annotation pipelines, and guide synthetic data generation. Evaluate and fine-tune foundation models like Stable Diffusion, ControlNet, OpenPose, DeepFaceLab, CP-VTON. Guide research, benchmarking, fine-tuning, and deployment of models. Evaluate build vs. buy decisions for third-party APIs or in-house model development. Ensure compliance with IP, client data protection, fairness, and ethical AI practices. Desired Skills: Deep experience in computer vision, generative AI (diffusion, transformers), and LLM integration Hands-on with PyTorch, Hugging Face, Diffusion/ GAN Architectures Hands-on with LLM and agentic frameworks like LangChain, AWS Bedrock Strong understanding of synthetic data pipelines, model evaluation metrics, and prompt engineering Strong understanding of image harmonization, segmentation, texture transfer Ability to architect scalable ML pipelines combining image/video generation with LLM reasoning Experience leading a technical team or managing AI initiatives end-to-end. Familiarity with AWS/GCP, GPU infrastructure, and scalable AI model serving Familiarity with co-pilot tools and AI-assisted code generation to accelerate prototyping and implementation of AI systems Desired Profile & Qualification: 8+ years in AI/ML roles including leadership in GenAI or CV-heavy platforms Degree in Computer Science, Machine Learning, or related field (MS/PhD preferred). Prior contributions to open-source AI or research publications is an advantage Note: This is an on-site position.

About this role: Lead Software Engineer (AI) position having experience in classic and generative AI techniques, and responsible for design, implementation, and support of Python based applications to help fulfill our Research & Consulting Delivery strategy. What youll do: Deliver client engagements that use AI rapidly, on the order of a few weeks Stay on top of current tools, techniques, and frameworks to be able to use and advise clients on them Build proofs of concept rapidly, to learn and adapt to changing market needs Support building internal applications for use by associates to improve productivity What you’ll need: 6-8 years of experience in classic AI techniques and at least 1.5 years in generative AI techniques. Demonstrated ability to run short development cycles and solid grasp of building software in a collaborative team setting. Must have: Experience building applications for knowledge search and summarization, frameworks to evaluate and compare performance of different GenAI techniques, measuring and improving accuracy and helpfulness of generative responses, implementing observability. Experience with agentic AI frameworks, RAG, embedding models, vector DBs Experience working with Python libraries like Pandas, Scikit-Learn, Numpy, and Scipy is required. Experience deploying applications to cloud platforms such as Azure and AWS. Solid grasp of building software in a collaborative team setting - use of agile scrum and tools like Jira / GitHub. Nice to have: Experience in finetuning Language models. Familiarity with AWS Bedrock / Azure AI / Databricks Services. Experience in Machine learning models and techniques like NLP, BERT, Transformers, Deep learning. Experience in MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc., Experience building scalable data models and performing complex relational databases queries using SQL (Oracle, MySQL, PostgreSQL). Who you are: Excellent written, verbal, and interpersonal communication skills with the ability to present technical information in a clear and concise manner to IT Leaders and business stakeholders. Effective time management skills and ability to meet deadlines. Excellent communications skills interacting with technical and business audiences. Excellent organization, multitasking, and prioritization skills. Must possess a willingness and aptitude to embrace new technologies/ideas and master concepts rapidly. Intellectual curiosity, passion for technology and keeping up with new trends. Delivering project work on-time within budget with high quality. Demonstrated ability to run short development cycle.

*****GenAI DevOps Engineer AWS Bedrock***** *****Pune Hinjewadi***** *****Immediate Joiners Preferred***** *****Minimum 4 Days WFO***** Job Description: We are seeking a highly experienced GenAI DevOps Engineer to join our dynamic team in Pune. The ideal candidate will have a strong background in building, deploying, and optimizing Generative AI applications on AWS Bedrock, along with expertise in DevOps practices. You will be responsible for automating infrastructure, managing CI/CD pipelines, and ensuring high performance and reliability of AI models. Key Responsibilities: Design, develop, and deploy Generative AI applications leveraging AWS Bedrock and SageMaker. Automate infrastructure provisioning and deployment processes. Build and maintain robust CI/CD pipelines using CodePipeline and CodeBuild. Monitor application and model performance using CloudWatch, Prometheus, and Grafana. Optimize AI models for performance, scalability, and cost-efficiency. Work with RAG (Retrieval-Augmented Generation) tools such as LangChain, Haystack, and LlamaIndex for building advanced AI solutions. Collaborate with data scientists and developers to streamline model deployment and monitoring. Required Skills: Extensive hands-on experience with AWS Bedrock and SageMaker. Strong expertise in CI/CD tools: CodePipeline, CodeBuild. Proficiency with monitoring tools: CloudWatch, Prometheus, Grafana. Experience with RAG frameworks like LangChain, Haystack, and LlamaIndex. Solid understanding of DevOps best practices and automation. Ability to troubleshoot and optimize AI deployment pipelines. Excellent problem-solving and communication skills. Preferred Skills: Knowledge of containerization (Docker, Kubernetes). Familiarity with scripting languages (Python, Bash). Experience with cloud security best practices. Understanding of machine learning lifecycle management. Mandatory Skills: AWS Bedrock and SageMaker expertise. CI/CD pipeline automation. Monitoring and performance optimization. RAG-based application development.

We are looking for an experienced Data Scientist with expertise in Generative AI and Large Language Models (LLMs) to join our innovation team. In this role, you will work at the cutting edge of AI technologies, leveraging LLMs to develop intelligent applications that can generate, analyze, and process text data. You will collaborate with data scientists, machine learning engineers, and product teams to build and deploy state-of-the-art AI solutions that solve complex real-world problems. Programming Python GenAI Technologies understanding evaluation LLM-LMM integration, Optimization, Deployment RAG, Knowledge graphs, transformers AWS Bedrock We re hiring Sr. Data Scientist for one of our Leading MNC to join their growing team. This position is based out in Bangalore. Education: Any Engineering

Design and develop full-stack applications using React (frontend) and Fast API (backend) Build and optimize LLM applications using Langchain and related frameworks Architect and maintain cloud-native applications on AWS EKS clusters Implement and optimize integrations with Bedrock services for LLM functionalities Develop and maintain AI pipelines using Python ML frameworks Manage and optimize databases (ex. PostgreSQL) in AWS RDS Integrate and maintain SSO solutions using OKTA Collaborate with AI researchers to implement and deploy ML models Design and develop RESTful APIs for AI service integration Implement secure and scalable cloud infrastructure using AWS services Lead technical design discussions and architecture reviews To ensure youre set up for success, you will bring the following skillset & experience: 5+ years of full-stack development experience Strong proficiency in React.js and modern JavaScript/TypeScript Expert-level Python development skills Experience with Python AI/ML frameworks: Langchain for LLM applications NumPy and Pandas for data manipulation Scikit-learn for ML implementations PyTorch or TensorFlow (preferred) Experience with Fast API framework Proven experience with AWS services, especially EKS and RDS Solid understanding of Kubernetes and container orchestration Experience with PostgreSQL and database optimization Knowledge of authentication systems and SSO implementation (OKTA preferred) Experience with CI/CD pipelines and DevOps practices Understanding of RESTful API design principles Whilst these are nice to have, our team can help you develop in the following skills: Experience with LLM integration and AI services Familiarity with AWS Bedrock or similar AI services Strong background in Python ecosystem: Hugging Face transformers Streamlet for AI applications Experience with vector databases (e.g., Pinecone, Chroma) Experience in prompt engineering and LLM optimization techniques Experience in implementing microservices architecture Experience with monitoring and observability tools Security best practices in cloud environments

Bachelors, M.S. (preferred) or Ph.D. (preferred) in Data Science, Computer Science, Electrical Engineering, Biomedical Engineering, Applied Optics, or related quantitative fields. Lead the design and development of generative AI models for new product development, particularly leveraging LLM and LMM AI models. Proven experience in applying generative AI, LLMs, and multi-modal models to solve real-world problems in the medical device industry or equivalent industry and/or academic experience. Demonstrable expertise in algorithm development, including, coding, algorithm testing, algorithm validation, and software development for Medical Device. Utilize tools such as AWS Bedrock, Azure AI Studio, and other cloud-based platforms to deploy, manage, and optimize AI models. Apply advanced data science techniques, including natural language processing (NLP), computer vision, and machine learning, to solve complex problems and enhance product functionality. Exceptional written and verbal communication skills and proven ability to collaborate effectively with multidisciplinary project teams is highly desirable. Minimum Requirements: Bachelor's Degree or equivalent The ability to fluently read, write, understand and communicate in English. Proficiency in Python programming and data science libraries (e.g., NumPy, Pandas, Scikit-learn, TensorFlow/PyTorch). At least 3 years of hands-on working experience in applying AI/ML methods for real-world problem solving in the medical device industry or equivalent industry experience.

Job Summary: We are seeking a versatile QA & AIOps Engineer with a minimum of 5 years of hands-on experience in both AI Ops implementation and intelligent QA automation. The ideal candidate will bridge the gap between DevOps, QA, and AI engineering ensuring robust infrastructure, AI agent deployment, intelligent testing, and automated monitoring for scalable AI systems. This role requires strong technical depth in cloud-native deployment (AKS/EKS), CI/CD pipelines, and AI/ML toolchains. Key Responsibilities: AI Ops & DevOps Engineering: Deploy and manage AI agents in scalable production environments (Azure/AWS). Set up and maintain Kubernetes clusters (AKS/EKS), Docker containers, and Ingress Controllers (NGINX/Traefik). Integrate platforms like Azure AI Foundry or AWS Bedrock into production pipelines. Implement auto-scaling policies using tools like KEDA or Horizontal Pod Autoscaler. Promote use of Vector Databases (e.g., Pinecone, Weaviate) for AI workflows. Configure infrastructure security: secrets management, access controls, and network policies. Use Helm charts to manage complex deployments and upgrades of AI services. Troubleshoot production issues, identify bottlenecks, and ensure high availability of AI workloads. Collaborate with SREs, DevOps, and ML engineers to ensure seamless agent deployment, monitoring, and scaling. QA & Intelligent Testing: Design, develop, and execute test cases (manual and automated) for web, API, and backend systems. Implement AI-driven test strategies (e.g., test prioritization, risk-based testing). Create and maintain automated test scripts using tools like JUnit, PyTest, and JMeter. Integrate QA automation into CI/CD pipelines with anomaly detection and predictive analytics. Log and manage bugs; track issues to closure with development and DevOps teams. Use AI-powered QA tools such as Test.ai, Functionize for test optimization. Monitor AIOps dashboards to validate intelligent issue detection and auto-remediation flows. Required Skills & Qualifications: 5+ years of combined experience in QA automation, DevOps, or AI Ops roles. Hands-on expertise with Kubernetes (AKS/EKS), Docker, Helm, CI/CD pipelines. Experience integrating AI/ML tools such as Azure AI Foundry, AWS Bedrock. Knowledge of AI Ops platforms, observability tools, and monitoring dashboards. Proficient in Python, Bash, or JavaScript. Familiarity with Vector DBs, AI observability, and security practices. Strong collaboration skills with cross-functional DevOps, QA, and AI engineering teams.

Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients . Powered by our purpose - the relentless pursuit of a world that works better for people - we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI. Inviting applications for the role of Principal Consultant , Generative AI + Agentic AI ! In this role, we are seeking a highly skilled and experienced AI Engineer with hands-on expertise in Generative AI, AWS Bedrock, Azure Open AI, Document Intelligence tools, Huggingface , Agentic AI, and Advanced Data Pipelines . It%27s platforms semantic kernel, autogen , langchain . Responsibilities Architect and implement advanced generative AI models, focusing on applications such as image and text generation, image and document extraction, RAG, Prompt engineering, and synthetic data generation. Advanced Prompt Engineering techniques. Stay at the forefront of AI/ML and generative AI advancements, driving the adoption of new technologies and best practices within the team. Develop, fine-tune, and optimize generative AI models, ensuring they meet performance, scalability, and business objectives . Firm grasp on tools to compare outputs of each model and compare against each other. Apply solid data science principles to enhance AI/ML models, using statistical analysis and machine learning techniques to improve model accuracy and efficiency. Work closely with data engineers, software developers, and product managers to integrate generative AI models into products and services, aligning with business objectives . Ensure that AI models are designed and deployed with ethical considerations, adhering to industry standards and regulatory requirements. Qualifications we seek in you! Minimum Q ualifications / Skills B achelor&rsquos or M aster&rsquos degree in computer science, AI, Machine Learning, Data Science, or a related field, with 5+ years of experience in AI/ML, particularly with generative AI models. Strong expertise in developing and deploying generative AI models. Proficiency in Python and experience with AI development libraries such as TensorFlow and PyTorch . Experience with Azure OpenAI, Open Source LLMs, and LangChain . Solid experience in applying data science principles, including statistical analysis, data preprocessing, and machine learning, to enhance AI/ML models. Preferred Q ualifications / Skills Familiarity with advanced techniques such as Retrieval-Augmented Generation (RAG), fine-tuning, prompt engineering, and zero-shot learning. Familiarity with NLP or computer vision related to generative AI applications. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. For more information, visit Follow us on X , Facebook, LinkedIn, and YouTube. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training .

Ready to build the future with AI At Genpact, we don&rsquot just keep up with technology&mdashwe set the pace. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what&rsquos possible, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and Inviting applications for the role of S e n i o r M a n ager - AI Senior Engineer -Agentic AI! In this role, you%27ll be part of Genpact%27s transformation under GenpactNext , as we lead the shift to Agentic AI Solutions&mdashdomain-specific, autonomous systems that redefine how we deliver value to clients. You%27ll help drive the adoption of innovations like the Genpact AP Suite in finance and accounting, with more Agentic AI products set to expand across service lines. In this role you&rsquoll be leveraging Azure&rsquos advanced AI capabilities or AWS Advance Ai capability, including Azure Machine Learning , Azure OpenAI, PrompFlow , Azure Cognitive Search, Azure AI Document Intelligence,AWS Sage Maker, AWS Bedrocks to deliver scalable and efficient solutions. You will also ensure seamless integration into enterprise workflows and operationalize models with robust monitoring and optimization. Responsibilities AI Orchestration - Design and manage AI Orchestration flow using tools such as: Prompt Flow, Or LangChain Continuously evaluate and refine models to ensure optimal accuracy, latency, and robustness in production. Document AI and Data Extraction , Build AI-driven workflows for extracting structured and unstructured data fromLearning , receipts, reports, and other documents using Azure AI Document Intelligence, and Azure Cognitive Services. RAG Systems - Design and implement retrieval-augmented generation (RAG) systems using vector embeddings and LLMs for intelligent and efficient document retrieval Optimize RAG workflows for large datasets and low-latency operations. Monitoring and Optimization - I mplement advanced monitoring systems using Azure Monitor, Application Insights, and Log Analytics to track model performance and system health Continuously evaluate and refine models and workflows to meet enterprise-grade SLAs for performance and reliability. Collaboration and Documentation - Collaborate with data engineers, software developers, and DevOps teams to deliver robust and scalable AI-driven solutions Document best practices, workflows, and troubleshooting guides for knowledge sharing and scalability. Qualifications we seek in you Minimum Qualifications Proven experience with Machine Learning, Azure OpenAI, PrompFlow , Azure Cognitive Search, Azure AI Document Intelligence , AWS Bedrock, SageMaker Proficiency in building and optimizing RAG systems for document retrieval and comparison. Strong understanding of AI/ML concepts, including natural language processing (NLP ), embeddings, model fine-tuning, and evaluation Experience in applying machine learning algorithms and techniques to solve complex problems in real-world applications Familiarity with state-of-the-art LLM architectures and their practical implementation in production environments Expertise in designing and managing Prompt Flow pipelines for task-specific customization of LLM outputs. Hands-on experience in training LLMs and evaluating their performance using appropriate metrics for accuracy, latency, and robustness Proven ability to iteratively refine models to meet specific business needs and optimize them for production environments. Knowledge of ethical AI practices and responsible AI frameworks . Experience with CI/CD pipelines using Azure DevOps or equivalent tools Familiarity with containerized environments managed through Docker and Kubernetes. Knowledge of Azure Key Vault, Managed Identities, and Azure Activ e Directory (AAD) for secure authentication. Experience with PyTorch or TensorFlow. Proven track record of developing and deploying Azure-based AI solutions for large-scale, enterprise-grade environments. Strong analytical and problem-solving skills, with a results-driven approach to building scalable and secure systems. Why join Genpact Lead AI-first transformation - Build and scale AI solutions that redefine industries Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career &mdashGain hands-on experience, world-class training, mentorship, and AI certifications to advance your skills Grow with the best - Learn from top engineers, data scientists, and AI experts in a dynamic, fast-moving workplace Committed to ethical AI - Work in an environment where governance, transparency, and security are at the core of everything we build Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the 140,000+ coders, tech shapers, and growth makers at Genpact and take your career in the only direction that matters: Up . Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Location: Any / Remote / Work From Home Employment Type: Full-time Job Summary: We are seeking skilled and innovative AI Engineers with a minimum 2-4 years of experience in developing and deploying AI solutions . The ideal candidate should have practical knowledge in AWS , Amazon Bedrock , LLMs , Claude AI , and Custom AI Development . You will contribute to the design and implementation of cutting-edge Generative AI (GenAI) and Mainstream AI applications across diverse business domains. This is an excellent opportunity to work with emerging technologies in an agile, fast-paced environment with full ownership of AI engineering pipelines. Key Responsibilities: Develop custom machine learning models and fine-tune foundation models for enterprise use Design and implement LLM-based and Generative AI solutions tailored to client use cases Work with OpenAI, Anthropic, HuggingFace models and their APIs to build secure, scalable AI systems Perform prompt engineering and experiment with parameter tuning and context optimization Build APIs and backend services to integrate AI models into product workflows Collaborate with product, data, and DevOps teams to deliver end-to-end AI-powered solutions Ensure best practices for AI model governance, security, performance, and ethical use Stay current with advancements in LLMs, vector databases (e.g., Pinecone, FAISS), and GenAI tooling Document architecture, experiments, and processes clearly and effectively Participate in peer reviews, client meetings, and cross-functional planning discussions Required Qualifications: Minimum 2-4 years of professional experience in AI/ML , with specific focus on LLMs and GenAI Strong experience working on AWS Bedrock , Lambda, and related services Proficiency in Python , including experience with libraries like HuggingFace, LangChain, etc. Familiarity with Anthropic , OpenAI , or other foundation models in production settings Experience with custom AI model development and model fine-tuning Good understanding of cloud-native AI deployments and API integrations Ability to apply prompt engineering techniques to optimize LLM responses Exposure to vector databases and RAG pipelines Strong problem-solving, communication, and team collaboration skills Preferred Qualifications (STRONG PLUS): Hands-on experience with LangChain, RAG pipelines, or agent frameworks Familiarity with AWS Sagemaker, DynamoDB, Lambda, or other AI tooling in AWS Knowledge of Docker or Kubernetes for containerizing AI workloads Understanding of MLOps principles and tools (MLflow, SageMaker Pipelines, etc.) Contributions to open-source AI projects or published GenAI applications AI/ML certifications Familiarity with enterprise use cases in biotech, healthcare, or manufacturing What We Offer: Remote work option Competitive salary package Exciting projects in the field of LLMs, AI, and cloud-native development Continuous learning opportunities in Generative AI and cloud AI tools A collaborative and fast-paced environment with a forward-thinking team Access to state-of-the-art tools and flexible project ownership How to Apply: Please submit your resume and cover letter outlining your relevant experience and why you'd be a great fit for Arocom. We differentiate candidates based on professionalism. We admire the new age methods like a video resume. If you have one please share the URL along with your resume. Your privacy is important to us, so we will not be contacting candidates by phone. If your application is selected, we will email you a link to schedule your interview at your convenient time. Please check your emails regularly, including your SPAM folder. Arocom encourages work from home and has a Bring Your Own Device (BYOD) policy. Employees / Consultants working from home are expected to use their personal laptops/desktops for work-related tasks.

Key Responsibilities: Design, develop, and implement AI-driven chatbots and IVAs to streamline customer interactions. Work on conversational AI platforms to create a seamless customer experience, with a focus on natural language processing (NLP), intent recognition, and sentiment analysis. Collaborate with cross-functional teams, including product managers and customer support, to translate business requirements into technical solutions. Build, train, and fine-tune machine learning models to enhance IVA capabilities and ensure high accuracy in responses. Continuously optimize models based on user feedback and data-driven insights to improve performance. Integrate IVA/chat solutions with internal systems such as CRM and backend databases. Ensure scalability, robustness, and security of IVA/chat solutions in compliance with industry standards. Participate in code reviews, testing, and deployment of AI solutions to ensure high quality and reliability. Required Skills and Qualifications: Bachelors or master’s degree in computer science, Data Science, AI/ML, or a related field. 3+ years of experience in developing IVA/chatbots, conversational AI, or similar AI-driven systems using AWS services Expert in using Amazon Lex, Amazon Polly, AWS lambda, AWS connect AWS Bedrock experience with Sage maker will have added advantage Solid understanding of API integration and experience working with RESTful services. Strong problem-solving skills, attention to detail, and ability to work independently and in a team. Excellent communication skills in English, both written and verbal. Preferred Qualifications: Experience in financial services or fintech projects. Knowledge of data security best practices and compliance requirements in the financial sector.

Gen AI+AWS Skill-Gen AI,AWS,AI Platform,Python,Tensorflow,Langchain,LLM Model,ML Development, AWS Lambda,AWS Bedrock,Data Extraction Exp-3-9YRS In Gen AI AWS PKG Upto-25LPA Loc- Bang, Pune NP-Imm-30Days Ritika-8587970773 ritikab.imaginators@gmail.com Required Candidate profile Gen AI + AWS Mandatory Skill-Gen AI, AWS,AI Platform, Python, Tensor flow, Lang chain, LLM Model, ML Development, AWS Lambda, AWS Bedrock, AWS AI, Data Extraction, GEN AI Solution, RPA Tool

Gen AI+AWS Skill-Gen AI,AWS,AI Platform,Python,Tensorflow,Langchain,LLM Model,ML Development, AWS Lambda,AWS Bedrock,Data Extraction Exp-4-12YRS In Gen AI AWS PKG Upto-25LPA Loc-Bang, Pune NP-Imm-30Days Ritika-8587970773 ritikab.imaginators@gmail.com Required Candidate profile Gen AI + AWS Mandatory Skill-Gen AI, AWS,AI Platform, Python, Tensor flow, Lang chain, LLM Model, ML Development, AWS Lambda, AWS Bedrock, AWS AI, Data Extraction, GEN AI Solution, RPA Tool

Role Overview We are seeking a skilled and innovative Machine Learning Engineer with expertise in Large Language Models (LLMs) to join our team. The ideal candidate has hands-on experience developing, fine-tuning, and deploying LLMs, alongside a deep understanding of the machine learning lifecycle. This role involves building scalable AI solutions, collaborating with cross-functional teams, and contributing to cutting-edge AI initiatives. Key Responsibilities Model Development & Optimization: Develop, fine-tune, and deploy LLMs like OpenAI's GPT, Anthropic's Claude, Googles Gemini, or AWS Bedrock. Customize pre-trained models for specific use cases, ensuring high performance and scalability. Machine Learning Pipeline Design: Build and maintain end-to-end ML pipelines, from data preprocessing to model deployment. Optimize training workflows for efficiency and accuracy. Integration & Deployment: Work closely with software engineering teams to integrate ML solutions into production environments. Ensure APIs and solutions are scalable and robust. Experimentation & Research: Experiment with new architectures, frameworks, and approaches to improve model performance. Stay updated with advancements in LLMs and generative AI technologies. Collaboration: Collaborate with cross-functional teams, including data scientists, engineers, and product managers, to align ML solutions with business goals. Provide mentorship to junior team members as needed. Required Qualifications Experience: At least 5 years of professional experience in machine learning or AI development. Proven experience with LLMs and generative AI technologies. Technical Skills: Proficiency in Python (required) and basic knowledge of Java is needed Hands-on experience with APIs and tools like OpenAI, Anthropic's Claude, Google Gemini, or AWS Bedrock. Familiarity with ML frameworks such as TensorFlow, PyTorch, or Hugging Face. Strong understanding of data structures, algorithms, and distributed systems. Cloud Expertise: Experience with AWS, GCP, or Azure, including services relevant to ML workloads (e.g., AWS SageMaker, Bedrock). Data Engineering: Proficiency in handling large-scale datasets and implementing data pipelines. Experience with ETL tools and platforms for efficient data preprocessing. Problem Solving: Strong analytical and problem-solving skills, with the ability to debug and resolve issues quickly. Preferred Qualifications Experience with multi-modal models and generative AI for images, text, or other modalities. Understanding of ML Ops principles and tools (e.g., MLflow, Kubeflow). Familiarity with reinforcement learning and its applications in AI. Knowledge of distributed training techniques and tools like Horovod or Ray. Advanced degree (Masters or Ph.D.) in Computer Science, Machine Learning, or a related field.

Job Overview: We are seeking an experienced and passionate Technical Manager/Lead to spearhead our cutting-edge AI initiatives including Phoenix Ask , Phoenix Report Writer , and upcoming AI-powered features. This role will lead a team of 5 Senior Developers focused on developing, deploying, and maintaining advanced AI capabilities using state-of-the-art models and technologies. Key Responsibilities: Lead the design, development, and deployment of scalable AI features and tools. Manage and mentor a team of senior AI developers. Collaborate with cross-functional teams (Product, UX, DevOps) to deliver commercial-ready AI features. Architect AI-driven solutions using modern frameworks and cloud platforms. Ensure best practices in model selection, prompt engineering, fine-tuning, and evaluation. Deploy AI applications using Azure Foundry , AWS Bedrock , and similar platforms. Oversee integration of models like GPT-4o , GPT-o3 , Claude , and LLaMA into business products. Maintain robust documentation and ensure product scalability and performance. Required Skills & Experience: 5+ years of experience in AI/ML development with at least 2 years in a leadership role . Strong expertise in Langchain , Pydantic , and FastAPI . Experience working with MCP (Modular Code Platforms or Microsoft Cloud Platform clarify as needed). Proven hands-on experience with deploying models like GPT-4o, GPT-o3, Claude, LLaMA . Solid understanding of AI model training , fine-tuning , and industry-standard tools . Strong deployment experience on Azure Foundry and AWS Bedrock or equivalent cloud services. Ability to manage sprints, code reviews, and project delivery timelines. Preferred Qualifications: Master's/Bachelors degree in Computer Science, Artificial Intelligence, or related field. Experience in integrating AI with enterprise systems. Prior work on generative AI or natural language applications.

Summary Bitkraft Technologies LLP is looking for a Senior DevOps Engineer to join our software engineering team. The DevOps engineer will be responsible for implementing cutting-edge technology and solving real-life challenges in a variety of client environments using VI Editor & YAML Editor. If you love solving problems, are a team player, and want to work in a fast-paced environment with core technical and business challenges, we would like to meet you. Key Skills Azure, GitHub Actions, Kubernetes, Infrastructure, Terraform AWS Bedrock (part of Generative AI), Amazon Q, Generative AI, Quicksight Pro Certification in Cloud Technologies Key Responsibilities DevOps Frameworks : Implement and work with newer frameworks in the DevOps landscape, ensuring up-to-date practices and methodologies. Infrastructure as Code : Develop and maintain infrastructure as code solutions, enabling scalable and manageable infrastructure deployment. Microservice Architecture Management : Manage and optimize microservices architectures, ensuring high availability and efficient operation of services. GitHub Actions : Utilize mandatory GitHub actions for automating workflows, including CI/CD pipelines and infrastructure deployment. Infrastructure Automation : Focus on automating the building and maintenance of infrastructure, both in cloud environments and on-premises setups. Cloud and On-Premise Solutions : Work across both cloud and on-premise environments, demonstrating flexibility and adaptability in various infrastructural contexts. Kubernetes Expertise : Manage and optimize container orchestration using Kubernetes, ensuring efficient deployment, scaling, and management of applications. Repository Management : Experience working with both Monorepo and polyrepo setups, understanding the nuances and best practices of each. Tech Stack Proficiency : Proficient in Java and able to leverage this in a DevOps context to improve systems and processes. AWS & Generative AI : Work with AWS Bedrock, Amazon Q, and other Generative AI tools to optimize cloud and automation processes. Visualization & Monitoring : Utilize AWS Quicksight for data visualization and monitoring infrastructure performance. Qualifications Proven experience as a DevOps Engineer, with a focus on modern DevOps practices and tools. Strong knowledge of infrastructure as code and experience in managing microservice architectures. Proficient in GitHub Actions and experienced in automating infrastructure development. Experience working with both cloud and on-premises environments. Demonstrable skills in Kubernetes and familiarity with Monorepo and polyrepo setups Technical proficiency in Java. Experience with AWS Bedrock, Amazon Q, and Generative AI tools. Strong expertise in AWS Quicksight for infrastructure monitoring. Cloud Pro Certification is highly preferred. Excellent problem-solving skills and the ability to work independently or as part of a team. Strong communication skills and the ability to collaborate effectively with cross-functional teams. Experience 5+ years

Mandatory Skills Strong proficiency in Generative AI, Large Language Models (LLMs), deep learning, agentic frameworks, and RAG setup. Experience in designing and implementing machine learning models using scikit-learn and TensorFlow. Hands-on expertise with AI/ML frameworks such as Hugging Face, LangChain, LangGraph, and PyTorch. Cloud AI services experience, particularly in AWS SageMaker and AWS Bedrock. MLOps & DevOps: Knowledge of data pipeline setup, Apache Airflow, CI/CD, and containerization (Docker, Kubernetes). API Development: Ability to develop and maintain APIs following RESTful principles. Technical proficiency in Elastic, Python, YAML, and system integrations. Nice to Have skills - Experience with Observability, Ansible, Terraform, Git, Microservices, AIOps, and scripting in Python. Familiarity with AI cloud services such as Azure OpenAI and Google Vertex AI.

JD is below: Design, develop, and deploy generative AI based applications using AWS Bedrock. Proficiency in prompt engineering and RAG pipeline Experience in building Agentic Generative AI applications Fine-tune and optimize foundation models from AWS Bedrock for various use cases. Integrate generative AI capabilities into enterprise applications and workflows. Collaborate with cross-functional teams, including data scientists, ML engineers, and software developers, to implement AI-powered solutions. Utilize AWS services (S3, Lambda, SageMaker, etc.) to build scalable AI solutions. Develop APIs and interfaces to enable seamless interaction with AI models. Monitor model performance, conduct A/B testing, and enhance AI-driven products. Ensure compliance with AI ethics, governance, and security best practices. Stay up-to-date with advancements in generative AI and AWS cloud technologies. Required Skills & Qualifications: Bachelor's or Masters degree in Computer Science, AI, Machine Learning, or a related field. 3+ years of experience in AI/ML development, with a focus on generative AI. Hands-on experience with AWS Bedrock and foundation models. Proficiency in Python and ML frameworks. Experience with AWS services such as SageMaker, Lambda, API Gateway, DynamoDB, and S3. Experience with prompt engineering, model fine-tuning, and inference optimization. Familiarity with MLOps practices and CI/CD pipelines for AI deployment. Ability to work with large-scale datasets and optimize AI models for performance. Excellent problem-solving skills and ability to work in an agile environment. Preferred Qualifications: AWS Certified Machine Learning – Specialty or equivalent certification. Experience in LLMOps and model lifecycle management. Knowledge of multi-modal AI models (text, image, video generation). Hands-on experience with other cloud AI platforms (Google Vertex AI, Azure OpenAI). Strong understanding of ethical AI principles and bias mitigation techniques.

3+ years of work experience in Python programming for AI/ML, deep learning, and Generative AI model development Proficiency in TensorFlow/PyTorch, Hugging Face Transformers and Langchain libraries Hands-on experience with NLP, LLM prompt design and fine-tuning, embeddings, vector databases and agentic frameworks Strong understanding of ML algorithms, probability and optimization techniques 6+ years of experience in deploying models with Docker, Kubernetes, and cloud services (AWS Bedrock, SageMaker, GCP Vertex AI) through APIs, and using MLOps and CI/CD pipelines Familiarity with retrieval-augmented generation (RAG), cache-augmented generation (CAG), retrieval-integrated generation (RIG), low-rank adaptation (LoRA) fine-tuning Ability to write scalable, production-ready ML code and optimized model inference Experience with developing ML pipelines for text classification, summarization and chat agents Prior experience with SQL and noSQL databases, and Snowflake/Databricks

Roles and Responsibilities: Architecture & Infrastructure Design Architect scalable, resilient, and secure AI/ML infrastructure on AWS using services like EC2, SageMaker, Bedrock, VPC, RDS, DynamoDB, CloudWatch . Develop Infrastructure as Code (IaC) using Terraform , and automate deployments with CI/CD pipelines . Optimize cost and performance of cloud resources used for AI workloads. AI Project Leadership Translate business objectives into actionable AI strategies and solutions. Oversee the entire AI lifecycle from data ingestion, model training, and evaluation to deployment and monitoring. Drive roadmap planning, delivery timelines, and project success metrics. Model Development & Deployment Lead selection and development of AI/ML models, particularly for NLP, GenAI, and AIOps use cases . Implement frameworks for bias detection, explainability , and responsible AI . Enhance model performance through tuning and efficient resource utilization. Security & Compliance Ensure data privacy, security best practices, and compliance with IAM policies, encryption standards , and regulatory frameworks. Perform regular audits and vulnerability assessments to ensure system integrity. Team Leadership & Collaboration Lead and mentor a team of cloud engineers, ML practitioners, software developers, and data analysts. Promote cross-functional collaboration with business and technical stakeholders. Conduct technical reviews and ensure delivery of production-grade solutions. Monitoring & Maintenance Establish robust model monitoring , alerting , and feedback loops to detect drift and maintain model reliability. Ensure ongoing optimization of infrastructure and ML pipelines. Must-Have Skills: 10+ years of experience in IT with 4+ years in AI/ML leadership roles. Strong hands-on experience in AWS services : EC2, SageMaker, Bedrock, RDS, VPC, DynamoDB, CloudWatch. Expertise in Python for ML development and automation. Solid understanding of Terraform, Docker, Git , and CI/CD pipelines . Proven track record in delivering AI/ML projects into production environments . Deep understanding of MLOps, model versioning, monitoring , and retraining pipelines . Experience in implementing Responsible AI practices – including fairness, explainability, and bias mitigation. Knowledge of cloud security best practices and IAM role configuration. Excellent leadership, communication, and stakeholder management skills. Good-to-Have Skills: AWS Certifications such as AWS Certified Machine Learning – Specialty or AWS Certified Solutions Architect. Familiarity with data privacy laws and frameworks (GDPR, HIPAA). Experience with AI governance and ethical AI frameworks. Expertise in cost optimization and performance tuning for AI on the cloud. Exposure to LangChain , LLMs , Kubeflow , or GCP-based AI services .