139 Autogen Jobs - Page 6

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.

Job Summary Director, Collection Platforms and AI As a director, you will be essential to drive customer satisfaction by delivering tangible business results to the customers. You will be working for the Enterprise Data Organization and will be an advocate and problem solver for the customers in your portfolio as part of the Collection Platforms and AI team. You will be using communication and problem-solving skills to support the customer on their automation journey with emerging automation tools to build and deliver end to end automation solutions for them. Team Collection Platforms and AI Enterprise Data Organizations objective is to drive growth across S&P divisions, enhance speed and productivity in our operations, and prepare our data estate for the future, benefiting our customers. Therefore, automation represents a massive opportunity to improve quality and efficiency, to expand into new markets and products, and to create customer and shareholder value. Agentic automation is the next frontier in intelligent process evolution, combining AI agents, orchestration layers, and cloud-native infrastructure to enable autonomous decision-making and task execution. To leverage the advancements in automation tools, its imperative to not only invest in the technologies but also democratize them, build literacy, and empower the work force. The Collection Platforms and AI team's mission is to drive this automation strategy across S&P Global and help create a truly digital workplace. We are responsible for creating, planning, and delivering transformational projects for the company using state of the art technologies and data science methods, developed either in house or in partnership with vendors. We are transforming the way we are collecting the essential intelligence our customers need to do decision with conviction, delivering it faster and at scale while maintaining the highest quality standards. What were looking for ? You will lead the design, development, and scaling of AI-driven agentic pipelines to transform workflows across S&P Global. This role requires a strategic leader who can architect end-to-end automation solutions using agentic frameworks, cloud infrastructure, and orchestration tools while managing senior stakeholders and driving adoption at scale. A visionary technical leader with knowledge of designing agentic pipelines and deploying AI applications in production environments. Understanding of cloud infrastructure (AWS/Azure/GCP), orchestration tools (e.g., Airflow, Kubeflow), and agentic frameworks (e.g., LangChain, AutoGen). Proven ability to translate business workflows into automation solutions, with emphasis on financial/data services use cases. An independent proactive person who is innovative, adaptable, creative, and detailed-oriented with high energy and a positive attitude. Exceptional skills in listening to clients, articulating ideas, and complex information in a clear and concise manner. Proven record of creating and maintaining strong relationships with senior members of client organizations, addressing their needs, and maintaining a high level of client satisfaction. Ability to understand what the right solution is for all type of problems, understanding and identifying the ultimate value of each project. Operationalize this technology across S&P Global, delivering scalable solutions that enhance efficiency, reduce latency, and unlock new capabilities for internal and external clients. Exceptional communication skills with experience presenting to C-level executives Responsibilities Engage with the multiple client areas (external and internal) and truly understand their problem and then deliver and support solutions that fit their needs. Understand the existing S&P Global product to leverage existing products as necessary to deliver a seamless end to end solution to the client. Evangelize agentic capabilities through workshops, demos, and executive briefings. Educate and spread awareness within the external client-base about automation capabilities to increase usage and idea generation. Increase automation adoption by focusing on distinct users and distinct processes. Deliver exceptional communication to multiple layers of management for the client. Provide automation training, coaching, and assistance specific to a users role. Demonstrate strong working knowledge of automation features to meet evolving client needs. Extensive knowledge and literacy of the suite of products and services offered through ongoing enhancements, and new offerings and how they fulfill customer needs. Establish monitoring frameworks for agent performance, drift detection, and self-healing mechanisms. Develop governance models for ethical AI agent deployment and compliance. Preferred Qualification 12+ years work experience with 5+ years in the Automation/AI space Knowledge of: Cloud platforms (AWS SageMaker, Azure ML; etc) Orchestration tools (Prefect, Airflow; etc) Agentic toolkits (LangChain, LlamaIndex, AutoGen) Experience in productionizing AI applications. Strong programming skills in python and common AI frameworks Experience with multi-modal LLMs and integrating vision and text for autonomous agents. Excellent written and oral communication in English Excellent presentation skills with a high degree of comfort speaking with senior executives, IT Management, and developers. Hands-on ability to build quick prototype/visuals to assist with high level product concepts and capabilities. Experience in deployment and management of applications utilizing cloud-based infrastructure. A desire to work in a fast-paced and challenging work environment Ability to work in a cross functional, multi geographic teams

Role: AI/ML Engineer Has 4+ years of work experience , with at least 2+ years directly working on Generative AI and Agentic systems Knows how to use Large Language Models (LLMs) like GPT for real applications (not just research or theory) Has worked on multi-agent systems or autonomous AI agents using tools like CrewAI, AutoGen, or similar frameworks Can write smart prompts ( prompt engineering ), build apps with LLMs, and knows how to do RAG (Retrieval-Augmented Generation) Has done fine-tuning of models and built custom AI workflows Codes well in Python Has used ML frameworks like TensorFlow or PyTorch Familiar with tools like LangChain , and cloud/data platforms like AWS or Databricks Location: Bangalore/ Mumbai Shift Timing: 12:00 PM 9:00 PM Notice Period: 30 days or less Call Anumeha @ +91 6376649769/ Alfiya @ +91 8787064649

Role & responsibilities Job Description: The ideal candidate will have a proven track record of working across the tech stack, from backend systems and APIs to frontend user interfaces, ensuring a seamless integration of AI models into production ready systems. The candidate will need to demonstrate he or she has a strong technical background, is curious, experienced with leading teams, and has exceptional communication and problem-solving skills. Key responsibilities include: Lead the design and build of scalable web and cloud-based applications integrating generative AI models. Collaborate with the Lead Data Architect to define system architecture, select appropriate tools and frameworks, and ensure best practices in software design and development. Build and maintain a robust agentic architecture, APIs, and microservices using technologies such as Python and Node.js or similar. Develop user friendly, responsive user interfaces using technologies such React and Angular. Design and maintain Azure based infrastructure for hosting and scaling AI solutions. Monitor and improve system performance. Implement best practices for secure and scalable application design, data storage, and API handling. Work closely with cross-functional team members, including Product Owners, Scrum Master, Lead Data Architect, UI/UX, and Application Owners to ensure the end-to-end delivery of user stories and features. Participate in Scrum ceremonies and actively maintain your cards on the scrum board. Maintain comprehensive technical documentation for all systems and processes. Provide technical guidance and mentorship to junior engineers, conduct code reviews, and foster a culture of growth and learning. Skills and Abilities: Proven experience in backend development using Python and Node.js. Advanced frontend development skills using React or Angular with a deep understanding of component-based architecture. Hands-on knowledge and experience with Microsoft Azure cloud services, including Azure Foundry, Functions, Blob, and container tools such as Azure Kubernetes. Ability to design and manage data pipelines ensures high-quality data is available for AI model training and deployment. Strong knowledge and experience working with structured and unstructured data that span across SQL databases and NoSQL databases such as MongoDB or CosmosDB. Experience with various AI tools like LangChain, Autogen, and LangGraph. Experienced in developing APIs and API management. Experience building and working with CI/CD pipelines and version control tools like GIT. Experience developing and delivering event driven architectures. Experience in using and implementing open-source large language models such as Llama, Mistral, and assorted embedding models Experience doing prompt engineering. Experience working with agile delivery methodologies and working in an agile delivery team. Ability to listen, build rapport, and credibility within IT and across various business units. Ability to lead and guide junior engineers. Curious. Stays abreast of current and upcoming technologies and tools.

TargetBay is a fast-growing eCommerce marketing automation SaaS company based out of Chennai and Atlanta. Clients use our products to increase their online sales through our personalized email marketing and reviews technologies. Job Title: AI/ML Engineer - Multi-Agent Systems Experience: 4 - 5 years Location: Perungudi, Chennai Key Skills: Multi-Agent Systems, AI Agents, LLM, Generative AI, RAG, Autogen, LangChain, Prompt Engineering, Fine-tuning, Python, Product Development, NLP, Machine Learning, Deep Learning, Vector Databases, Huggingface, Flask, Docker Roles & Responsibilities: Strong experience in prompt engineering, working on proprietary and public LLMs, including fine-tuning, inference optimization, and experience in the latest LLM frameworks/libraries (like LangChain, Langfuse, Ragas, Llamaindex, Huggingface, and Chainlit) Strong experience in AI/ML, with a strong understanding of machine learning, deep learning, and NLP concepts Strong programming skills in Python and experience with frameworks like Flask/Django Design, develop, and deploy generative AI-based solutions using cutting-edge technologies and methodologies Hands-on experience with building and deploying chatbots using language models Hands-on experience with LLMs (Large language models) and advanced techniques such as RAG (Retrieval-Augmented Generation), Fine-tuning, reasoning, etc. Experience with Langchain and open-source Gen AI LLMs e.g., Llama and Mistral Knowledge of prompt engineering techniques Familiarity with Vector databases like Pinecone Knowledge of natural language processing techniques and libraries such as NLTK, and Spacy Knowledge of Docker containers Experience with any cloud (AWS/Azure/GCP) Any extra specification(Optional): Must have extensive experience in Multi-Agent AI systems development Must have proven end-to-end product development and maintenance experience Must have AI Agent experience

Role Overview We are seeking a highly skilled Agentic AI Developer to join our advanced AI engineering team. The ideal candidate will have hands-on experience in building intelligent multi-agent systems using cutting-edge frameworks and technologies in Generative AI, LLMOps, and AIOps. Must-Have Skills & Experience Backend Development Proficiency in Python Experience with FastAPI for backend services and API integration Generative AI & LLMOps Hands-on experience with Large Language Models (LLMs) , especially OpenAI models Expertise in Prompt Engineering and Retrieval-Augmented Generation (RAG) Agentic AI Systems Experience building multi-agent systems using the AutoGen framework Familiarity with Agentic AI design patterns , including: Reflection Planning Tool Use Multi-agent Collaboration Cloud & Data Services Experience with Azure AI Services Working knowledge of Vector Databases Proficiency in both SQL and NoSQL databases Preferred Skills Exposure to MLOps and AIOps practices Experience in Deep Learning frameworks Familiarity with Data Science workflows and pipelines Additional Information Strong problem-solving and system design skills Ability to work in a fast-paced, collaborative environment Excellent communication and documentation abilities

Role Summary: We are looking to hire Junior Gen AI Developers with hands-on experience in building and deploying Generative AI applications. Candidates must have actively contributed to at least one real-time project rollout to a customer. At least 6 months of hands-on experience in Gen AI application development Exposure to real-time Gen AI project rollout Ability to develop AI Assistants and Agents Experience in deploying Gen AI applications on cloud (Azure, AWS) or on-premises infrastructure Strong understanding and implementation of prompt engineering techniques Understand the use case and design AI solution which fits for customer needs Develop AI Assistants and Agents using GenAI AI platforms Deploy on any cloud or on Prem infrastructure Experience in using different prompt techniques Experience in testing & finetuning the Gen AI solutions Experience in implementing Guardrails as per customer needs

Job Overview: We are looking for a highly skilled AI & Agentic Developer to design, build, and deploy intelligent autonomous systems. This role involves developing AI-powered agents that can perceive, reason, and act independently, leveraging LLMs, reinforcement learning, and multi-agent systems. You will work on cutting-edge AI frameworks like LangChain, AutoGen, CrewAI, and MLOps pipelines for scalable deployment. Key Responsibilities: AI & Machine Learning Development: Develop, train, and fine-tune machine learning (ML) and deep learning (DL) models. Implement LLMs, NLP, reinforcement learning (RL), and computer vision (CV) models. Optimize retrieval-augmented generation (RAG) systems with vector databases (FAISS, Pinecone, Chroma). Work on multimodal AI systems integrating text, image, and audio processing. Agentic AI Systems Development: Build autonomous AI agents that can make decisions, learn from feedback, and interact with environments. Implement multi-agent frameworks using LangChain, CrewAI, AutoGen, BabyAGI, MetaGPT. Integrate AI agents with APIs, databases, and enterprise applications for real-world deployment. Software Engineering & MLOps: Design and deploy AI models using Docker, Kubernetes, and CI/CD pipelines. Implement MLOps workflows for continuous training, monitoring, and model retraining. Optimize AI solutions for cloud platforms (AWS, Azure, GCP) and edge computing. AI Governance & Security: Implement AI safety measures, including adversarial defense and bias mitigation. Ensure compliance with AI regulations (GDPR, HIPAA, SOC 2) and ethical AI principles. Secure AI agents against prompt injection, model poisoning, and adversarial attacks. Required Skills & Qualifications: Technical Skills: Strong programming skills in Python, Java, or R. Expertise in machine learning frameworks (TensorFlow, PyTorch, Scikit-Learn). Experience with LLMs & NLP (Hugging Face, OpenAI API, BERT, GPT, Claude). Proficiency in multi-agent frameworks (LangChain, CrewAI, AutoGen). Knowledge of reinforcement learning (PPO, A3C, DDPG, SAC). Experience with vector databases (FAISS, Pinecone, Chroma) and knowledge graphs. Strong foundation in MLOps, cloud AI services (AWS, Azure AI, Google Vertex AI). Soft Skills: Strong analytical and problem-solving skills. Ability to work in a fast-paced, cross-functional team. Excellent communication and documentation skills.

About this role: Wells Fargo is seeking a Principal AI Engineer. In this role, you will: Act as an advisor to leadership to develop or influence applications, network, information security, database, operating systems, or web technologies for highly complex business and technical needs across multiple groups Lead the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas or the enterprise, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, advanced analytical and inductive thinking Translate advanced technology experience, an in-depth knowledge of the organizations tactical and strategic business objectives, the enterprise technological environment, the organization structure, and strategic technological opportunities and requirements into technical engineering solutions Provide vision, direction and expertise to leadership on implementing innovative and significant business solutions Maintain knowledge of industry best practices and new technologies and recommends innovations that enhance operations or provide a competitive advantage to the organization Strategically engage with all levels of professionals and managers across the enterprise and serve as an expert advisor to leadership Required Qualifications: 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications: This is an individual contributor role (Principal AI Engineer) which is at the level of Executive Director Own the end-to-end AI/ML lifecycledesign, build, deploy, and maintain scalable agent solutions for Technology Analytics. Embed Generative AI and Agentic AI into day-to-day business processes to lift efficiency and employee productivity. Execute and refine the AI roadmap, keeping every project tightly aligned with enterprise strategy and measurable KPIs. Design autonomous AI agents capable of real-time decision-making and action with minimal human oversight. Enforce best-in-class practices for model scalability, reliability, security, and ongoing maintenance. Lead R&D on emerging AI tech, scouting fresh use cases to keep Wells Fargo at the innovation forefront. Drive cross-division rollout of AI solutions, track impact, and deliver tangible cost- and time-savings. Serve as an AI thought leadermentor teams, champion best practices, and translate complex concepts for senior stakeholders. 7 years of Analytics, AI or Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education. 3+ years of experience in Generative AI tech like Retrieval-Augmented Generation (RAG) design end-to-end pipelines (Vector DBs, chunking, embedding, retrieval, context injection) to ground LLM responses on enterprise knowledge. Strong software development skills, particularly in Python, with experience working with AI frameworks (any one of Langchain, Langgraph, CrewAI, Autogen, Google ADK ) and tools in cloud environments; Knowledge of ML, NLP, Information Retrieval, Recommender Systems and LLMs. Must havedeployed role-based agent ( Multi Agent Orchestration ) teams with one of the listed frameworks Experience with container & orchestration technologies (Docker, Kubernetes etc) and cloud platforms (AWS, GCP or Azure); Experience with training, fine-tuning, and applying large language models (LLMs) for agentic AI application Deployment & MLOps - containerize inference endpoints with Docker/K8s, scale on AWS/GCP GPU instances, and automate CI/CD, canary releases, and rollback strategies. 5+ years of experience with NLP Tech/ NLP pipelines (NLTK, spaCy, Hugging Face, BERT/GPT) 5+ years of hands-on experience with Microsoft Power Platform (Power Apps, Power Automate, Power BI, Dataverse), including solution architecture, governance, and deployment. Working knowledge of enterprise tools like MS Copilot Studio and AgentSpace for Agentic AI, with a strong understanding of prompt engineering, grounding, and extensibility. Familiarity with Data Connectors and API gateways that support seamless communication between systems. General Analytics Data Visualization using Tableau, PowerBI. Strong knowledge of SQL (Structured Databases) Deep subject matter expertise in AI technologies, including but not limited to Copilot Studio, Azure AI Foundry, Google Agent Space, Google Gemini, Microsoft 365, and M365 Copilot. Traditional Data Science - classical ML and statistical modelinglinear/logistic regression, time-series ARIMA/Prophet, decision trees, random forests, gradient-boosting (XGBoost/LightGBM), SVMs, k-means and hierarchical clustering, association-rule mining (Apriori), and A/B testing with hypothesis-testing frameworks Ability to orchestrate processes across integrated systems to enable robust workflows and seamless operations. Ability to collaborate with cross-functional teams to align technical solutions with business goals and end-user needs. A strong focus on cybersecurity and risk management throughout the software development lifecycle. Passion for designing solutions that prioritize end-user experience and usability. Strong problem-solving skills and attention to detail in complex system design. Proficiency in designing and developing multi-agent systems where multiple AI agents collaborate to achieve complex tasks 7 Aug 2025 To request a medical accommodation during the application or interview process, visit . Wells Fargo maintains a drug free workplace. Please see our to learn more.

Job Description for Senior Software Engineer Generative AI & Multi-Agentic Systems Responsibilities:• Design and implement Multi-Agentic GenAI systems to solve regulatory and compliance workflows for global trade.• Assess and recommend the right architecture, tools, and frameworks, ensuring modularity, scalability, and maintainability.• Integrate with a mix of open-source and cloud-based agentic orchestration stacks such as:o LangChain, LangGraph, Autogen, Flowable, N8N, AWS Strands, AWS Bedrock, etc. Lead the development of production-ready agent workflows that interface with legal policies, classification engines, third-party compliance data, and case management systems. Collaborate with U.S.-based business and technical stakeholders to define problem scope, user personas, and use cases.• Work on LLM evaluations, prompt engineering, embedding-based retrieval, and tool-augmented agent behavior. • Integrate with enterprise systems (APIs, data layers, UI components) to support human-in-the-loop decision-making. • Drive rapid prototyping, POCs, and iterative delivery while ensuring testability and traceability of GenAI behavior. • Ensure all systems comply with Autodesk’s standards for security, data protection, auditability, and compliance. • Participate in technical reviews, provide mentorship, and document technical decisions. Qualifications: • 5+ years of software engineering experience with a strong focus on Python and modern software design principles. • Hands-on experience building Multi-Agentic systems using frameworks like LangChain, LangGraph, AutoGen, AWS Strands, Flowable, and N8N. • Solid understanding of Generative AI techniques, including LLMs, embeddings, prompt engineering, and retrieval-augmented generation (RAG). • Strong grasp of Model Context Protocol (MCP) and Agent-to-Agent (A2A) orchestration strategies for scalable, tool-augmented agent workflows .• Experience integrating with vector databases (e.g., FAISS, Weaviate, Pinecone) and using OpenAI or AWS Bedrock APIs. • Knowledge of cloud-native architecture, event-driven microservices, and AWS AI/ML services (e.g., SageMaker, Lambda, Step Functions).• Background in legal, risk, or trade compliance domains is a strong plus.• Ability to work effectively with distributed teams and adjust to U.S. West Coast working hours.• Excellent communication skills and experience collaborating with business users, domain experts, and enterprise architects.

Job Title : Agentic AI Backend Developer Years of Experience : 5 to 7 years Job Location : Chennai / Hyderabad Work Mode : Hybrid 3 days from Office Job Description: Role Overview: Seeking an experienced backend developer to architect and implement multi-agent AI solutions with a focus on Retrieval-Augmented Generation (RAG). This position will utilize frameworks like LangGraph and Lang Chain, leverage vector databases such as Pinecone and Weaviate, and deploy solutions within AWS environments including S3 and related services. Key Responsibilities: Design, implement, and optimize multi-agent RAG systems using LangGraph, LangChain, and similar agentic frameworks. Orchestrate and coordinate agent-based workflows, managing state and memory across agents for robust, scalable AI features. Integrate, tune, and maintain vector databases such as Pinecone and Weaviate for efficient semantic search and retrieval. Develop backend APIs and microservices in Python or Node.js, with seamless interactions with agentic pipelines and vector databases. Deploy solutions on AWS, leveraging services like Amazon S3, Lambda, EC2, and container orchestration tools. Collaborate with front-end and cross-functional product teams to deliver high-quality, reliable user experiences. Oversee software lifecycle, maintaining documentation, automated testing, CI/CD pipelines, and performance monitoring. Qualifications: Hands-on experience designing and deploying AI/ML and RAG applications with advanced agentic frameworks (LangGraph, Lang Chain, CrewAI or AutoGen). Strong software engineering background in Python or Node.js; familiarity with FastAPI a plus. Significant expertise working with vector databases, including Pinecone and Weaviate, for RAG architecture. Proven track record of deploying, operating, and optimizing applications on AWS (S3, Lambda, API Gateway, etc.). Familiar with DevOps and MLOps practices; skilled in working with cloud-native tools and services. Exposure to advanced agentic concepts and frameworks; familiarity with Google agentic tools is an advantage. Excellent communication and the ability to thrive within cross-functional teams. Regards, Sreejit.

GenAI Engineer Build and deploy conversational agents using LLMs and multi-agent systems. Design RAG pipelines and integrate with enterprise systems. Experience: ~3 years overall, 2+ years in AI/ML engineering. Must have : Experience with LangGraph, Agno, AutoGen or CrewAI.

Job Description: AI Engineer (RAG & Agentic AI Specialist) Work Location: Mumbai and Gurgaon Why would you like to join us? TransOrg Analytics specializes in Data Science, Data Engineering and Generative AI, providing advanced analytics solutions to industry leaders and Fortune 500 companies across India, US, APAC and the Middle East. We leverage data science to streamline, optimize, and accelerate our clients' businesses. Visit at www.transorg.com to know more about us. Job Objective To build enterprise-grade AI solutions that leverage Retrieval-Augmented Generation (RAG), Agentic AI frameworks, and large language models (LLMs). The candidate will be responsible for end-to-end solutioning using modern tools and platforms, interacting with business teams, and driving innovation within the Microsoft and Azure ecosystem. Essential Job Tasks Build and deploy scalable AI solutions, from RAG systems to complex agent-based architectures using LangChain, CrewAI, AutoGen, or low code solutions like Copilot Studio, Azure AI Foundry. Leverage MCP, A2A, Microsoft Flows, and M365 Copilot for reasoning-based process automation. Collaborate with business to gather requirements and recommend best fit AI solutions. Work with the cloud infra team to set up secure, scalable AI systems on Azure. Ensure production-readiness and scalability of deployed AI solutions. Areas of Responsibility End-to-end ownership of AI product delivery. Integration of AI agents and retrieval mechanisms. Enabling adoption and training of AI practice across the organization. Work Experience 2-5 years overall experience in AI/ML or related fields. 2-3 years hands-on experience in RAG and agentic AI solutions. Required Qualifications B.E./B.Tech or M.Sc./B.Sc. in Computer Science, Data Science, or related field. Education from Tier 1 institutes preferred. Generative AI certifications are an advantage. Technical Knowledge LangChain, CrewAI, AutoGen, Copilot Studio, Azure AI Foundry. Creation and deployment of APIs using FastAPI or similar frameworks. OpenAI, Hugging Face, GPT4 APIs. Azure cloud (preferred). Working knowledge of Databricks and Azure Synapse. Power Platform (Power Automate, M365 Copilot Chat). Agent workflow orchestration, prompt design, RAG architecture, vector databases.

Job Location: Pune/ Mumbai/ Chennai/ Bangalore Skills: The role involves building and deploying generative AI and intelligent agents using Python, Azure services, and frameworks like LangChain and AutoGen. It includes integrating with enterprise systems, fine-tuning models, managing data pipelines, prompt engineering, and working in cross-functional teams with DevOps and cloud-based monitoring to support scalable, production-ready AI solutions. Billing Start date: ASAP Shift Timings: 14:00 to 23:00 Job Title: Senior Developer Generative AI & Agentic AI Job Description: We are seeking a skilled and experienced Senior Developer specializing in Generative AI and Agentic AI, with a focus on Azure and OpenAI technologies, to support the development and deployment of cutting-edge AI solutions. In this role, you will be responsible for building, fine-tuning, and optimizing generative and agent-based AI models and integrating them into scalable enterprise applications. Qualification Graduate preferred in data science or big data Total Exp. 10+ yrs GCM 5+ Key Responsibilities: 1. Build and deploy generative AI models (LLMs, GANs, Transformers, Diffusion Models) and intelligent agents using Azure AI services and OpenAI APIs. 2. Develop and orchestrate AI agents capable of autonomous task completion, leveraging frameworks like AutoGen, LangChain, and Azure AI Studio. 3. Integrate LLMs and AI agents with enterprise workflows and APIs using Azure Functions, Logic Apps, and RESTful services. 4. Collaborate with data teams to preprocess, clean, and structure data pipelines for model training and inference using Azure Data Factory and Synapse. 5. Fine-tune foundation models (e.g., GPT, Codex, Whisper) using organization-specific datasets; optimize for performance and cost-efficiency on Azure GPUs. 6. Implement logging, performance tracking, and evaluation metrics using tools like Azure Monitor, Application Insights, and prompt evaluation frameworks. 7. Document model configurations, prompts, agent flows, and development practices to ensure maintainability and reusability. 8. Work with architects, data scientists, product managers, and business stakeholders to translate business needs into technical implementations. Qualifications: Bachelor's or master's degree in computer science, AI/ML, or related field. 8-10 years of experience in developing AI/ML applications, with recent hands-on work in LLMs and Generative AI. Proficiency in Python and experience with ML libraries such as PyTorch, TensorFlow, or Hugging Face Transformers. Experience with Azure AI services (OpenAI, Cognitive Search, Form Recognizer, AI Studio). Familiarity with Agentic AI frameworks like LangChain, AutoGen, or Semantic Kernel. Strong understanding of prompt engineering, embeddings, vector databases (e.g., Pinecone, FAISS), and Retrieval Augmented Generation (RAG). Experience with DevOps/MLOps tools like GitHub Actions, Azure DevOps, MLflow is a plus. Effective communicator with a strong ability to work in agile, collaborative environments.