A career in IBM Consulting embraces long‑term relationships and close collaboration with clients across the globe. You’ll work with visionaries across multiple industries to improve the hybrid and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio, including IBM Software and Red Hat. Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role, you’ll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions resulting in groundbreaking impact for a wide network of clients. Our culture of evolution and empathy centers on long‑term career growth and development opportunities in an environment that embraces your unique skills and experience.
Your Role And Responsibilities
We are seeking a Lead AutoGen Engineer with deep experience in Autogen who has moved beyond building RAG pipelines and is designing the systems that make agentic AI reliable in regulated, high‑stakes environments for both client‑facing and internal platforms. This is a role for someone who has wrestled with why naive retrieval fails against complex regulatory language, who has built an agentic workflow from scratch, and who thinks about LLM outputs the way a systems engineer thinks about correctness guarantees. This is a hands‑on technical leadership role for someone who designs and builds production‑grade agentic systems — not as a research exercise, but as engineering deliverables that operate reliably in compliance‑driven, high‑stakes environments. The problems you will work on do not have off‑the‑shelf solutions. You will be expected to make architectural decisions, iterate when the first design proves insufficient, and communicate those decisions clearly to both technical teams and enterprise stakeholders.
What You Will Do
Design and deliver RAG systems for complex, document‑heavy domains — defining ingestion strategy, retrieval architecture, and generation‑side optimisation appropriate to the content type and use case.
Architect multi‑agent orchestration systems that coordinate specialised agents using Autogen and other frameworks across parallel and sequential workflows, with structured quality evaluation and targeted correction loops built into the pipeline.
Build LLM routing and evaluation infrastructure — selecting models per task, optimising generation parameters, and ensuring full auditability of outputs for regulated delivery environments.
Lead end‑to‑end technical delivery: from problem framing and system design through implementation, quality assurance, and stakeholder communication.
Work across regulated industries including life sciences, insurance, and financial services — understanding what compliance, traceability, and domain accuracy mean at implementation level.
Evaluate and apply fine‑tuning approaches where retrieval‑based solutions are insufficient, with the judgment to know when each is appropriate.
Mentor engineers and establish technical standards for agentic AI development within the practice.
Collaborate with client stakeholders to translate complex domain requirements into functioning system behaviours.
What We Offer
Individual career path
Access to countless trainings and certification offerings
A knowledge sharing culture
An environment where you are actively contributing your ideas
The possibility to work in projects in one of the largest IT companies
Required Technical And Professional Expertise
Proven experience (8 years +) building and iterating on production‑grade agentic systems across the full stack — ingestion, retrieval, orchestration, generation, and quality assurance.
Deep and thorough understanding of statistics, probability, data science, machine learning, transformer architectures.
Strong expertise in multi‑agent frameworks — designing orchestration patterns, parallel agent architectures, feedback loops, and structured output pipelines.
Deep understanding of data ingestion and RAG pipeline designs across diverse content types, retrieval strategies, and generation optimisation techniques.
Deep experience with delivering agentic systems end‑to‑end to production pipelines in regulated industries.
Experience integrating multiple LLM providers with routing logic, audit logging, and parameter optimisation for enterprise and regulated contexts.
Proficient in advanced skills in prompt and context engineering.
Integrating agentic solutions with cloud platforms such as Azure OpenAI, IBM Watsonx, and AWS, ensuring governance, safety, and monitoring.
Proficiency in Python and relevant engineering tooling; cloud platform experience across AWS and GCP.
Track record of delivering agentic systems with measurable operational impact for enterprise clients in regulated industries.
Advanced database skills across SQL (MySQL, SQL Server), NoSQL (MongoDB, Neo4j), and VectorDBs (CosmosDB, Azure AI Search, FAISS).
Ability to lead small technical teams, set direction, and maintain delivery quality across complex engagements.
Strong communication skills — able to present architectural decisions and system behaviours to non‑technical audiences including clinical, regulatory, and business stakeholders.
Language – Hindi &️ English: Professional proficiency — required for coordination with other teams embedded in the engagement.
Preferred Technical And Professional Experience
Experience with clinical or regulatory document workflows — pharmaceutical submissions, compliance reporting, or structured document generation at scale.
Experience in working with IBM's agentic asset portfolio.
Familiarity with Model Context Protocol (MCP) and emerging agentic interoperability standards, agentic skills, and tools.
Multi‑agent system design demonstrating breadth of agentic architecture application beyond a single domain.
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