Introduction
A career in IBM Consulting fosters long-term relationships and close collaboration with clients worldwide.
You’ll have the opportunity to work alongside visionaries from various industries, enhancing the hybrid and AI journey for some of the most innovative and valuable companies on the globe. Your ability to drive impact and facilitate meaningful change for clients will be supported by our strategic partner ecosystem and robust technology platforms across the IBM portfolio, including IBM Software and Red Hat.
Curiosity and an insatiable quest for knowledge are the foundations of success in IBM Consulting. In this role, you’ll be encouraged to challenge the status quo, explore ideas outside your immediate responsibilities, and develop creative solutions that yield groundbreaking results for a broad network of clients. Our culture, centered on evolution and empathy, emphasizes long-term career growth and development opportunities, embracing your unique skills and experiences.
As part of the IBM Consulting team, you will work in one of our Client Innovation Centers (Delivery Centers), where we provide deep technical and industry expertise to a diverse range of public and private sector clients worldwide. Our delivery centers equip clients with locally-based skills and technical know-how to drive innovation and the adoption of new technologies.
Your Role and Responsibilities
We are seeking a Lead AutoGen Engineer with substantial experience in Autogen. This individual will go beyond merely building RAG pipelines and will design systems that ensure agentic AI operates reliably in regulated, high-stakes environments for both client-facing and internal platforms.
This role is tailored for someone who has grappled with the complexities of regulatory language and has built an agentic workflow from the ground up. You will approach LLM outputs as a systems engineer would, with a focus on correctness guarantees. This hands-on technical leadership role involves designing and building production-grade agentic systems — not as a research exercise, but as engineering deliverables that function reliably in compliance-driven, high-stakes settings. The challenges you face will not have off-the-shelf solutions; thus, you will be responsible for making architectural decisions, iterating on initial designs, and clearly communicating those decisions to both technical teams and enterprise stakeholders.
What You Will Do
- Design and deliver RAG systems for complex, document-heavy domains, defining ingestion strategies, retrieval architectures, and generation-side optimizations tailored to content types and use cases.
- Architect multi-agent orchestration systems that coordinate specialized agents using autogen and other frameworks across parallel and sequential workflows, integrating structured quality evaluations and targeted correction loops.
- Build LLM routing and evaluation infrastructure, selecting models per task, optimizing generation parameters, and ensuring full auditability of outputs for regulated delivery environments.
- Lead end-to-end technical delivery, from problem framing and system design to implementation, quality assurance, and stakeholder communication.
- Collaborate with regulated industries, including life sciences, insurance, and financial services; understanding compliance, traceability, and domain accuracy at the implementation level.
- Evaluate and apply fine-tuning approaches where retrieval-based solutions are inadequate, demonstrating the judgment to ascertain the appropriateness of each method.
- Mentor engineers and establish technical standards for agentic AI development within the practice.
- Work with client stakeholders to translate complex domain requirements into functional system behaviors.
What We Offer
- Individual career path development
- Access to extensive training and certification offerings
- A culture of knowledge sharing
- An environment where your ideas are actively contributed
- The opportunity to work on projects with one of the largest IT companies
Required Technical and Professional Expertise
- Proven experience (8+ years) in building and refining production-grade agentic systems across the full stack — ingestion, retrieval, orchestration, generation, and quality assurance.
- Deep understanding of statistics, probability, data science, machine learning, and transformer architectures.
- Strong expertise in multi-agent frameworks, including designing orchestration patterns, parallel agent architectures, and structured output pipelines.
- Comprehensive knowledge of data ingestion and RAG pipeline designs across diverse content types, retrieval strategies, and generation optimization techniques.
- Substantial experience delivering agentic systems end-to-end in production pipelines within regulated industries.
- Experience integrating multiple LLM providers with routing logic, audit logging, and parameter optimization for enterprise and regulated contexts.
- Proficiency in prompt and context engineering.
- Ability to integrate agentic solutions with cloud platforms, such as Azure OpenAI, IBM Watsonx, and AWS, ensuring governance, safety, and monitoring.
- Proficient in Python and relevant engineering tools, with experience on cloud platforms like AWS and GCP.
- A track record of delivering agentic systems with measurable operational impact for enterprise clients in regulated industries.
- Advanced database skills with SQL (MySQL, SQL Server), NoSQL (MongoDB, Neo4j), and VectorDBs (CosmosDB, Azure AI Search, FAISS).
- Capability to lead small technical teams, set direction, and maintain delivery quality across complex projects.
- Strong communication skills to present architectural decisions and system behaviors to non-technical audiences, including clinical, regulatory, and business stakeholders.
- Professional proficiency in both Hindi and English to coordinate effectively with other project teams.
Preferred Technical and Professional Experience
- Experience with clinical or regulatory document workflows, including pharmaceutical submissions, compliance reporting, or large-scale structured document generation.
- Familiarity with IBM's agentic asset portfolio.
- Knowledge of Model Context Protocol (MCP) and emerging agentic interoperability standards, as well as agentic skills and tools.
- Experience in multi-agent system design, demonstrating the application of agentic architecture beyond a single domain.
Apply online using the form below. Only applications matching the job profile will be considered.