AI Agent Engineer - Lead and Support

AI Agent Engineer Lead / Support – GenAI, RAG, Agents, SAP BTP

Remote, India | Contract End Client: Enterprise Procurement AI Client

About the Role Our consulting client is seeking an AI Agent Engineer Lead / Support to help design, build, test, and optimize AI agents for an enterprise Procurement AI platform. This role will support delivery across SAP ARIBA, SAP Business AI, SAP BTP, GenAI/RAG, and enterprise procurement automation. The Lead AI Agent Engineer will own the shared agent framework, AI orchestration, RAG pipeline, prompt patterns, evaluation approach, and reusable components. The Support AI Agent Engineer will help build individual agent capabilities, tools, prompts, document extraction routines, and evaluation datasets during peak development.

Responsibilities • Design, build, test, and optimize AI agents supporting procurement automation use cases. • Lead or support the reusable agent framework, memory patterns, orchestration, tool usage, and agent lifecycle. • Build agent modules using established framework patterns and reusable components. • Design and develop RFP authoring capabilities, including RFP drafts, templates, clause suggestions, category enrichment, and structured outputs. • Implement supplier-facing Q&A workflows, clarification logging, response governance, FAQ retrieval, and safety guardrails. • Develop bid evaluation capabilities including scoring explanations, normalization assist, supplier ranking outputs, confidence measures, and bid comparison summaries. • Build AI-assisted compliance functionality for risk detection, clause deviation checks, mandatory document validations, and auditable exception explanations. • Create analytics agent capabilities for natural-language KPI insights, supplier performance narratives, trend explanations, and feedback-loop summaries. • Own or support RAG pipeline components including embeddings, chunking, metadata design, retrieval quality, citations, grounding, and retrieval evaluation. • Define and execute AI evaluation methods including test harnesses, golden datasets, accuracy metrics, hallucination checks, regression tests, and prompt tuning cycles. • Define and implement agent-to-system tool interfaces, backend service interactions, API calls, and output schemas. • Produce key deliverables including agent design documents, shared agent framework, prompt library, RAG pipeline, document ingestion, and retrieval logic.

Required Skills / What You Bring • Hands-on experience building LLM applications using OpenAI, Azure OpenAI, Gemini, Claude, SAP AI Core, or equivalent services. • Experience with agentic AI, including tool-using agents, workflow agents, multi-step business processes, and orchestration frameworks. • Strong knowledge of RAG, including document ingestion, embeddings, chunking, vector search, reranking, metadata filtering, and grounded answer generation. • Ability to create reliable prompts, structured outputs, JSON schemas, chain-of-verification patterns, and guardrails. • Strong Python and/or Node.js backend engineering experience. • Ability to build APIs, services, and enterprise integrations. • Experience with AI evaluation, model evaluation, test datasets, scoring, hallucination checks, regression testing, and confidence measurement. • Strong understanding of enterprise AI requirements including security, auditability, explainability, data privacy, and human approval flows. • Exposure to SAP ARIBA, SAP Business AI, SAP AI Core, SAP Generative AI Hub, and SAP BTP is preferred. • Experience with LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or equivalent frameworks is preferred. • Experience with vector databases such as SAP HANA Vector Engine, Azure AI Search, Pinecone, Weaviate, FAISS, Chroma, or equivalent. • Experience with REST APIs, JSON schema, structured outputs, prompt evaluation frameworks, Git, CI/CD, Docker, and cloud deployment basics.

Qualifications • Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, Engineering, or a related field. • Strong software engineering background is highly preferred. • For the Lead role, prior ownership of enterprise GenAI solution delivery is important.

Experience Level Lead AI Agent Engineer: • 7–12 years total experience. • 3+ years AI / ML / GenAI experience. • 5+ years backend engineering experience. • Prior ownership of enterprise GenAI solution delivery preferred. Support AI Agent Engineer: • 3–6 years total experience. • 1–3 years AI / ML / GenAI experience. • 2+ years backend engineering experience. • SAP exposure is preferred / nice to have.

Preferred Certifications • Microsoft Certified: Azure AI Engineer Associate. • Microsoft Certified: Azure Data Scientist Associate. • Google Professional Machine Learning Engineer. • AWS Certified Machine Learning – Specialty. • SAP AI Core / SAP BTP related certifications, where applicable. • Databricks, Snowflake, or cloud data engineering certification is beneficial.

Compensation Compensation details will be confirmed based on the finalized employment type, experience, qualifications, and other relevant factors.