16 Langraph Jobs

The Specialized Analytics Manager provides full leadership and supervisory responsibility. You will provide operational/service leadership and direction to team(s). You will apply in-depth disciplinary knowledge through provision of value-added perspectives or advisory services. You may contribute to the development of new techniques, models, and plans within the area of expertise. Excellent communication and diplomacy skills are required for this role. You will generally have responsibility for volume, quality, timeliness of end results, and shared responsibility for planning and budgets. Your work will affect an entire area, which eventually affects the overall performance and effectiveness of the sub-function/job family. You will have full supervisory responsibility, ensuring motivation and development of the team through professional leadership. This will include duties such as performance evaluation, compensation, hiring, disciplinary and terminations, as well as direction of daily tasks and responsibilities. The Data Science Analyst is a developing professional role within the GWFO team. In this role, you will apply specialized knowledge in machine learning, statistical modeling, and data analysis to monitor, assess, analyze, and evaluate processes and data. You will identify opportunities to leverage advanced analytics to improve business outcomes, automate processes, and generate actionable insights. Additionally, you will contribute to the development and deployment of innovative AI solutions, including generative AI and agentic AI applications. You will work with cross-functional stakeholders to gather and process operational data from various sources to examine past business performance and identify areas for improvement. As a successful candidate, you should ideally have 7+ years of relevant experience in data science, machine learning, or a related field. You should possess advanced process management skills, be organized and detail-oriented, curious about learning and developing new skill sets, particularly in the area of artificial intelligence, have a positive outlook with a can-do mindset, and strong programming skills in Python and proficiency in relevant data science libraries such as scikit-learn, TensorFlow, PyTorch, and Transformers. Experience with statistical modeling techniques, building GenAI solutions, agentic AI frameworks, and data visualization tools such as Tableau or Power BI is required. Strong logical reasoning capabilities, willingness to learn new skills, and good communication and presentation skills are also essential. You should have a Bachelors/University degree or equivalent experience. This job description provides a high-level review of the types of work performed, and other job-related duties may be assigned as required. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity, review Accessibility at Citi. View Citis EEO Policy Statement and the Know Your Rights poster.,

As a part of the global leader in Cloud, AI, and Digital technologies, you will be responsible for leveraging GenAI models and frameworks to enhance the efficiency and productivity of businesses worldwide. Your role will involve serving as the primary technical expert for GenAI technologies, focusing on developing, implementing, and optimizing advanced AI models and solutions to expand our GenAI footprint across clients. You will provide technical leadership, drive innovation, and ensure the successful integration of AI technologies into our IT services for clients. Your responsibilities will include defining best practices, standards, and templates for AI solutions, conducting workshops, demos, and client presentations on GenAI use cases, and collaborating closely with cross-functional teams to identify, evaluate, and implement use cases across different customers. In addition, you will evaluate and integrate emerging GenAI technologies to enhance conversational AI capabilities, provide technical leadership, mentorship, and guidance to teams, troubleshoot and resolve complex platform integration and functionality issues. You will also be hands-on in independently building quick prototypes and demonstrating them to key decision-makers. To be successful in this role, you should have 10+ years of total IT experience with at least 3-4 years of hands-on experience with AI/GenAI technologies. Expertise in NLP, NLU, NLQ, and NLG technologies is essential, along with Core Python proficiency to build applications and engineer GenAI solutions at an enterprise scale. You must have delivered production-grade projects on agentic AI frameworks, as well as hands-on experience with agentic AI frameworks such as Autogen, Langraph, or Crew.AI. Experience with NLQ to SQL-based GenAI applications using core Python tools and frameworks, databases, data warehouses, and data lakes on cloud platforms is required. Deep knowledge of architecting product-scale GenAI applications on Microsoft Azure Cloud, AWS Cloud, or GCP cloud environments is a must. Strong programming skills in Python, Node.js, Java, or similar, API programming, familiarity with LLMs, prompt engineering, fine-tuning, and embeddings are desired. Excellent problem-solving skills, solution architecture capabilities, and client-facing communication skills are essential. The ability to translate business needs into technical solutions, manage multiple projects and priorities in a fast-paced environment, and work with cloud platforms is crucial. Moreover, expertise in building technical proposals with winning engineering architectures and technical articulation for CXO level audience, and experience in developing fast PoVs and blueprints on new and emerging GenAI models, tools, frameworks, and other stack will be advantageous for this role.,

The Data Science Analyst role at Citi within the GWFO team is a developing professional position that involves applying specialized knowledge in machine learning, statistical modeling, and data analysis to monitor, assess, analyze, and evaluate processes and data. The main responsibilities include identifying opportunities to leverage advanced analytics to improve business outcomes, automate processes, and generate actionable insights. Additionally, the individual in this role will contribute to the development and deployment of innovative AI solutions, including generative AI and agentic AI applications, while collaborating with cross-functional stakeholders. As a Data Science Analyst at Citi, you will be expected to: - Gather and process operational data from various cross-functional stakeholders to examine past business performance and identify areas for improvement. - Apply machine learning techniques to identify data patterns and trends and provide insights to enhance business decision-making capabilities in various areas. - Develop and implement machine learning models for predictive analytics, forecasting, and optimization. - Design, build, and deploy Generative AI solutions to enhance customer experience, automate tasks, and personalize interactions. - Experiment with agentic AI frameworks to create autonomous systems that can learn, adapt, and solve complex problems. - Develop tools and techniques to evaluate the performance and impact of AI solutions. - Translate data into consumer or customer behavioral insights to drive targeting and segmentation strategies and effectively communicate findings to business partners and senior leaders. - Continuously explore and evaluate new data sources, tools, and capabilities, focusing on cutting-edge AI technologies to improve processes and strategies. - Collaborate closely with internal and external business partners to build, implement, track, and enhance decision strategies. Skills and Experience: - 5+ years of relevant experience in data science, machine learning, or a related field. - Advanced process management skills, organized and detail-oriented. - Curiosity about learning and developing new skill sets, particularly in the area of artificial intelligence. - Positive outlook with a can-do mindset. - Strong programming skills in Python and proficiency in relevant data science libraries such as scikit-learn, TensorFlow, PyTorch, and Transformers. - Experience with statistical modeling techniques, including regression, classification, and clustering. - Experience building GenAI solutions using LLMs and vector databases. - Experience with agentic AI frameworks, such as Langchain, Langraph, MLOps. - Experience with data visualization tools such as Tableau or Power BI. - Other skills required include strong logical reasoning capabilities, willingness to learn new skills, and good communication and presentation skills. Education: - Bachelor's/University degree or equivalent experience in a quantitative field such as computer science, statistics, mathematics, or engineering. Master's degree preferred. Working at Citi offers more than just a job - it means joining a global family of dedicated individuals where you can grow your career, contribute to your community, and make a real impact.,

The Data Science Analyst is a developing professional role within GWFO team. This role applies specialized knowledge in machine learning, statistical modeling, and data analysis to monitor, assess, analyze, and evaluate processes and data. You will identify opportunities to leverage advanced analytics to improve business outcomes, automate processes, and generate actionable insights. Additionally, you will contribute to the development and deployment of innovative AI solutions, including generative AI and agentic AI applications. Working with cross-functional stakeholders, you will gather and process operational data to examine past business performance and identify areas for improvement. Utilizing machine learning techniques, you will identify data patterns and trends, providing insights to enhance business decision-making capabilities in various areas such as business planning, process improvement, and solution assessment. Your responsibilities will include developing and implementing machine learning models for predictive analytics, forecasting, and optimization. You will design, build, and deploy Generative AI solutions to enhance customer experience, automate tasks, and personalize interactions. Furthermore, you will experiment with agentic AI frameworks to create autonomous systems that can learn, adapt, and solve complex problems. Developing tools and techniques to evaluate the performance and impact of AI solutions will be part of your role. You will translate data into consumer or customer behavioral insights to drive targeting and segmentation strategies, communicating findings clearly and effectively to business partners and senior leaders. Continuous improvement is key, and you will explore and evaluate new data sources, tools, and capabilities with a focus on cutting-edge AI technologies. Collaboration with internal and external business partners in building, implementing, tracking, and improving decision strategies will be essential. As a successful candidate, you should ideally have 7+ years of relevant experience in data science, machine learning, or a related field. You should possess advanced process management skills, be organized and detail-oriented, and have a curious mindset for learning and developing new skill sets, particularly in artificial intelligence. Strong programming skills in Python and proficiency in relevant data science libraries such as scikit-learn, TensorFlow, PyTorch, and Transformers are required. Experience with statistical modeling techniques, GenAI solutions, agentic AI frameworks, and data visualization tools like Tableau or Power BI is beneficial. Other essential skills include strong logical reasoning capabilities, willingness to learn new skills, and good communication and presentation skills. A Bachelors/University degree or equivalent experience is necessary for this role.,

You will be responsible for leveraging GenAI models and frameworks to build applications and optimize AI solutions for clients. As the primary technical expert in GenAI technologies, you will focus on enhancing the GenAI footprint by developing and implementing advanced AI models. Your role will involve defining best practices, conducting workshops and demos, collaborating with cross-functional teams, and integrating emerging GenAI technologies for improving conversational AI capabilities. Additionally, you will provide technical leadership, mentorship, and guidance to teams, troubleshoot platform integration issues, and independently build prototypes to demonstrate to key decision-makers. To excel in this position, you should have at least 10 years of IT experience, with 3-4 years specifically in AI/Gen AI technologies such as OpenAI, Anthropic, or Hugging Face. Proficiency in NLP, NLU, NLQ, NLG technologies, and core Python expertise for building enterprise-scale applications are essential. You must have delivered production-grade projects on agentic AI frameworks, hands-on experience with frameworks like Autogen, Langraph, or Crew.AI, and expertise in NLQ to SQL-based GenAI applications using Python tools. Experience with cloud platforms like Microsoft Azure, AWS, or GCP, API integrations, and programming skills in Python, Node.js, or Java are also required. Moreover, you should possess strong problem-solving skills, solution architecture capabilities, and client-facing communication abilities to translate business requirements into technical solutions effectively. The ability to manage multiple projects in a fast-paced environment and experience working with cloud platforms will be beneficial. Additionally, expertise in building technical proposals, fast PoVs, and blueprints on new GenAI models and tools are desired for this role.,

The Spec Analytics Intmd Analyst role is a developing professional position where you will independently handle most problems and have the freedom to solve complex issues. You will utilize your in-depth specialty knowledge along with industry standards to integrate with the team and achieve sub-function/job family objectives. Your role will involve applying analytical thinking and data analysis tools to make judgments and recommendations based on factual information with attention to detail. You will be dealing with variable issues that could have broader business impacts and will have a direct influence on the core activities of the business through close contact. Your communication and diplomacy skills will be crucial to exchange potentially complex information effectively. Responsibilities: - Working with large and complex data sets to evaluate, recommend, and support business strategies - Identifying and compiling data sets using tools like SQL and Access to predict, improve, and measure business outcomes - Documenting data requirements, data collection, processing, cleaning, and exploratory data analysis - Specializing in marketing, risk, digital, and AML fields - Assessing risk in business decisions with consideration for the firm's reputation and compliance with laws and regulations Skills and Experience: As a successful candidate, you should ideally have: - 5+ years of experience in data science, machine learning, or related fields - Advanced process management skills, detail-oriented, and organized - Curiosity and willingness to learn new skill sets, particularly in artificial intelligence - Strong programming skills in Python and proficiency in data science libraries such as scikit-learn, TensorFlow, PyTorch, and Transformers - Experience with statistical modeling techniques, data visualization tools, and GenAI solutions - Familiarity with agentic AI frameworks and MLOps Education: - Bachelors/University degree or equivalent experience This job description provides an overview of the work performed, and additional duties may be assigned as needed.,

The Data Science Analyst role at Citi, located in Gurgaon, is a developing professional position within the GWFO team. As a Data Science Analyst, you will utilize specialized knowledge in machine learning, statistical modeling, and data analysis to evaluate processes and data, identifying opportunities for leveraging advanced analytics to enhance business outcomes. You will play a key role in automating processes, generating actionable insights, and developing innovative AI solutions to contribute to the organization's success. Collaboration with cross-functional stakeholders is a fundamental aspect of this role. In this position, your responsibilities will include gathering and processing operational data from various stakeholders, applying machine learning techniques to identify data patterns and trends, developing and implementing machine learning models for predictive analytics, and designing Generative AI solutions to enhance customer experience. You will also experiment with agentic AI frameworks, develop tools to evaluate AI solutions" performance, and translate data into consumer insights to drive targeting and segmentation strategies. Effective communication of findings to business partners and senior leaders is essential for success in this role. The ideal candidate should possess 5+ years of relevant experience in data science or a related field, advanced process management skills, a curious mindset for learning new skill sets, and strong programming skills in Python. Proficiency in relevant data science libraries, experience with statistical modeling techniques, and familiarity with data visualization tools are required. Additionally, strong logical reasoning capabilities, willingness to learn new skills, and good communication and presentation skills are essential for this position. A Bachelor's/University degree or equivalent experience in a quantitative field is necessary, with a Master's degree being preferred. Working at Citi offers more than just a job it provides the opportunity to join a global family of dedicated individuals, grow your career, contribute to your community, and make a meaningful impact. If you require a reasonable accommodation due to a disability to access our search tools or apply for a career opportunity, please review the Accessibility at Citi information. For more details, you can refer to Citis EEO Policy Statement and the Know Your Rights poster.,

* If you are 5+ years experienced and Immediate joiner , please apply: https://forms.gle/TbiZ5o9oN2ZtJSpKA 5+ years of experience as a backend or full-stack engineer with a strong backend focus Advanced proficiency in Python Practical experience integrating LLMs (e.g., RAG pipelines, agent frameworks, LangChain, LangGraph, or similar) Background in machine learning engineering is a strong plus Solid understanding of service architecture and production deployment workflows Hands-on LLM integration in production (not academic/chatbot-only experience) Expertise in designing production-grade APIs and backend services Strong knowledge of async workflows, deployment, observability, and performance *This is a software engineering role (not data science, analytics, or annotation)* Description: A complete remote role, you can use your own laptop. 8hrs/day, Mon-Fri required Eligibility: Candidates with 5+ years of relevant professional experience are eligible to apply.Must possess strong communication skills , both written and verbal.Should have proven expertise in the specific field or role being applied for. Timings: 8 hrs/day, Mon-Fri Preferred candidate profile : Immediate Joiners Fully remote, 3 months contract in the starting

Role & responsibilities Must Haves Proven track record of project delivery for 1+ years Good coding (Preferably Python) skills and DSA Good problem solving and communication skills. Good Knowledge of Gen-AI technologies (LLM prompt engineering) Familiarity with React, HTML, CSS, JS or similar frameworks Familiarity with HTTP, REST, microservices, concurrency and Multithreading Willingness to work in a dynamic and fast paced environment. 4-6 years of experience with a Bachelor / Master's Degree in Computer Science or equivalent. Ownership and commitment towards work

* If you are 5+ years experienced and Immediate joiner , please apply: https://forms.gle/9n6GFcewkBo9VBNF8 5+ years of experience as a backend or full-stack engineer with a strong backend focus Advanced proficiency in Python Practical experience integrating LLMs (e.g., RAG pipelines, agent frameworks, LangChain, LangGraph, or similar) Background in machine learning engineering is a strong plus Solid understanding of service architecture and production deployment workflows Hands-on LLM integration in production (not academic/chatbot-only experience) Expertise in designing production-grade APIs and backend services Strong knowledge of async workflows, deployment, observability, and performance *This is a software engineering role (not data science, analytics, or annotation)* Description: A complete remote role, you can use your own laptop. 8hrs/day, Mon-Fri required Eligibility: Candidates with 5+ years of relevant professional experience are eligible to apply.Must possess strong communication skills , both written and verbal.Should have proven expertise in the specific field or role being applied for. Timings: 8 hrs/day, Mon-Fri Preferred candidate profile : Immediate Joiners Fully remote, 3 months contract in the starting

* If you are 3+ years experienced and Immediate joiner , please apply: https://docs.google.com/forms/d/e/1FAIpQLScorR1zEgu9FvDHO-4gjJEOPhk_2tJE6cgftARiy9rwcVcDHg/viewform 3+ years of experience as a backend or full-stack engineer with a strong backend focus Advanced proficiency in Python Practical experience integrating LLMs (e.g., RAG pipelines, agent frameworks, LangChain, LangGraph, or similar) Background in machine learning engineering is a strong plus Solid understanding of service architecture and production deployment workflows Hands-on LLM integration in production (not academic/chatbot-only experience) Expertise in designing production-grade APIs and backend services Strong knowledge of async workflows, deployment, observability, and performance *This is a software engineering role (not data science, analytics, or annotation)* Description: A complete remote role, you can use your own laptop. 8hrs/day, Mon-Fri required Eligibility: Candidates with 3+ years of relevant professional experience are eligible to apply.Must possess strong communication skills , both written and verbal.Should have proven expertise in the specific field or role being applied for. Timings: 8 hrs/day, Mon-Fri Preferred candidate profile : Immediate Joiners Fully remote, 3 months contract in the starting

Key Responsibilities: Agentic AI solution implementation leveraging Azure ecosystem, open-source RPA tools and scripting solutions where needed. Automation Solution Development : Create, deploy, and optimize automation workflows and BOTs using Agentic AI frameworks like Autogen. Leverage AI-driven processes to enable smart automation in business operations. Hands-on Cloud Integration : Design and implement automation solutions that integrate seamlessly with Microsoft Azure services (such as Azure Functions , Logic Apps , Azure Storage ) and other cloud-based tools to improve scalability and performance. AI and Python Libraries : Utilize Agentic AI frameworks for enhancing automation processes, and use Python libraries like Playwright for web automation, browser interaction, and testing. Implement machine learning models or AI algorithms where applicable to automate decision-making and data processing tasks. Scripting & Customization : Develop custom scripts in languages such as Python , PowerShell , JavaScript , and others to extend the functionality of RPA solutions, optimize workflows, and troubleshoot complex scenarios. Stakeholder Engagement : Collaborate with business analysts, IT teams, and key stakeholders to gather requirements, align automation goals with business priorities, and ensure automation solutions meet the desired business outcomes. Process Optimization : Continuously monitor, analyze, and optimize existing automation systems to enhance performance, reduce processing times, and ensure robustness. Identify opportunities to further automate manual processes across departments. Technical Leadership & Mentorship : Provide leadership, mentorship, and training to Agentic AI developers and junior engineers. Share best practices and foster a collaborative environment to ensure high standards of automation development.

Key Responsibilities: 1. Model Development and Deployment: Design, develop, and deploy generative AI models using cutting-edge techniques and frameworks. Utilize tools like LangChain, LangGraph, LangSmith to enhance model functionality and performance. Build models on complex RAG Architecture & should be able to incorporate AI security by design. 2. Agentic AI and Intelligent Systems: Develop and integrate intelligent agents and agentic AI systems to automate and optimize processes. Collaborate with cross-functional teams to implement agent-based solutions in various applications. 3. Research and Innovation: Stay updated with the latest advancements in AI and machine learning. Experiment with new algorithms and methodologies to improve existing models and systems. 4. Collaboration and Technical Leadership: Work closely with data scientists, software engineers, and product managers to ensure AI solutions meet business needs. Provide technical guidance and mentorship to junior team members. 5. Performance Optimization and Scalability: Optimize models for efficiency, scalability, and robustness in production environments. Monitor and evaluate system performance, implementing improvements as necessary. 6. Documentation and Knowledge Sharing: Document model architectures, processes, and key findings. Share insights and advancements with the team and stakeholders. Qualifications: Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Proven experience in developing and deploying generative AI models and machine learning systems. Proficiency in programming languages such as Python, with expertise in frameworks like TensorFlow, PyTorch, or Keras. In-depth knowledge of LangChain, Langraph, LangSmith, Agents, Agentic AI, and MCP. Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization technologies (e.g., Docker, Kubernetes). Strong analytical and problem-solving skills. Excellent communication skills and ability to work collaboratively in a tea Mandatory Skills: Generative AI.Experience3-5 Years.

Position Summary: As a member of Redaptive's AI team, you will be driving Agentic AI and Generative AI integration across all of Redaptives business units. You will drive AI development and integration across the organization, directly impacting Redaptives global sustainability efforts and shaping how we leverage AI to serve Fortune 500 clients. Responsibilities and Duties: Strategic Leadership (10%): Champion the AI/ML roadmap, driving strategic planning and execution for all initiatives. Provide guidance on data science projects (Agentic AI, Generative AI, and Machine Learning), aligning them with business objectives and best practices. Foster a data-driven culture, advocating for AI-powered solutions to business challenges and efficiency improvements. Collaborate with product management, engineering, and business stakeholders to identify opportunities and deliver impactful solutions Technical Leadership (40%): Architect and develop Proof-of-Concept (POC) solutions for Agentic AI, Generative AI, and ML. Utilize Python and relevant data science libraries, leveraging MLflow. Provide technical guidance on AI projects, ensuring alignment with business objectives and best practices. Assist in developmentand documentation of standards for ethical and regulatory-compliant AI usage. Stay current with AI advancements, contributing to the team's knowledge and expertise. Perform hands-on data wrangling and AI model development Operational Leadership (50%): Drive continuous improvement through Agentic AI, Generative AI, and predictive modeling. Participate in Agile development processes (Scrum and Kanban). Ensure compliance with regulatory and ethical AI standards. Other duties as assigned Required Abilities and Skills: Agentic AI development and deployment. Statistical modeling, machine learning algorithms, and data mining techniques. Databricks and MLflow for model training, deployment, and management on AWS. Working with large datasets on AWS and Databricks Strong hands-on experience with: Agentic AI development and deployment. Working with large datasets on AWS and Databricks. Desired Experience: Statistical modeling, machine learning algorithms, and data mining techniques. Databricks and MLflow for model training, deployment, and management on AWS. Experience integrating AI with IoT/event data. Experience with real-time and batch inference integration with SaaS applications. International team management experience. Track record of successful product launches in regulated environments Education and Experience: 5+ years of data science/AI experience Bachelor's degree in Statistics, Data Science, Computer Engineering, Mathematics, or a related field (Master's preferred). Proven track record of deploying successful Agentic AI, Generative AI, and ML projects from concept to production. Excellent communication skills, able to explain complex technical concepts to both technical and non-technical audiences.

Job Description & Responsibilities Identify valuable data sources and automate collection processes Undertake preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams. Qualification, Skills & Experience Good hands-on experience in Advanced Python Programming Experiences in scalable Microservice Architecture and Development Good understanding of API Development, Messaging Queues and Asynchronous Task Management Basic DevOp skills and working with Docker Experience with LangChain, LangGraph, AutoGen or CrewAI are a big plus Ability to co-work in a small team with different locations Ability to learn and understand a new Python framework

We are seeking a proficient AI/ML Engineer responsible for testing, deploying, and hosting various Large Language Models (LLMs). The role involves monitoring deployed agentic services, ensuring their optimal performance, and staying abreast of the latest advancements in AI technologies. Key Responsibilities: LLM Deployment & Hosting Evaluate, test, and deploy diverse LLMs on cloud-based and on-premise infrastructures. Optimize model performance for scalability and efficiency. Implement secure API endpoints and model-serving pipelines. Strong CI/CD skills and knowledge of CI/CD tools like Jenkins, GitHub Actions, CircleCI etc. Agentic AI Services Deploy and maintain AI agents using frameworks such as CrewAI, Agnos(Phi Data), AutoGen etc. Integrate LLMs into business workflows and automation tools. Design, monitor, and enhance agentic services for real-world applications. Monitoring & Optimization Utilize advanced observability tools to monitor model performance, latency, and cost efficiency. Implement tools like AgentOps, OpenLIT, Langfuse, and Langtrace for comprehensive monitoring and debugging of LLM applications. Develop logging, tracing, and alerting systems for deployed models and AI agents. Conduct A/B testing and gather user feedback to refine AI behavior. Address model drift and retrain models as necessary. Best Practices & Research Stay updated with the latest advancements in AI, LLMs, and agentic systems. Implement best practices for prompt engineering, reinforcement learning from human feedback (RLHF), and fine-tuning methodologies. Optimize compute costs and infrastructure usage for AI applications. Collaborate with researchers and ML engineers to integrate state-of-the-art AI techniques. Strong knowledge on version control tools like GitHub Qualifications & Skills: Proficiency with LLM frameworks such as Hugging Face Transformers, OpenAI API, or Meta AI models. Strong programming skills in Python and experience with deep learning libraries (PyTorch, TensorFlow, JAX). Experience with cloud platforms (AWS, Azure, GCP) and model deployment tools (Docker, Kubernetes, FastAPI, Ray Serve). Familiarity with vector databases (FAISS, Pinecone, Weaviate) and retrieval-augmented generation (RAG) techniques. Hands-on experience with monitoring tools such as AgentOps, OpenLIT, Langfuse, and Langtrace. Understanding of prompt engineering, LLM fine-tuning, and agent-based automation. Excellent problem-solving skills and the ability to work in a dynamic AI research and deployment team. Preferred Qualifications: Experience in reinforcement learning, fine-tuning LLMs, or training custom models. Knowledge of security best practices for AI applications. Contributions to open-source AI/ML projects or research publications in the field.