Senior AI/ML Engineer - Agentic AI
About The Position
We are building specialized foundation models and AI agents that accelerate SAP customers' data transformation journeys. The agents you build will directly power SAP's Autonomous Enterprise, where AI runs core business processes end-to-end across finance, supply chain, HR, and procurement at global scale. You'll set technical direction, define how we architect and scale multi-agent systems, and raise the engineering bar across a global team. You'll work directly with pretraining and fine-tuning team leads in Europe, India, and early-adopter customers. We want someone who has shipped agentic systems in production and knows where they break.
Requirements
- BS, MS, or PhD in Computer Science, ML, or a related field.
- 6+ years building and shipping ML systems, with 3+ years hands-on with LLMs and agents in production.
- Expert Python; strong fundamentals: system design, testing, modularity, async, API design
- PyTorch; working knowledge of fine-tuning and PEFT methods (LoRA, QLoRA)
- LLM application development: prompting, structured outputs, tool calling, context management
- Inference optimization: vLLM, TensorRT-LLM, quantization (int8, int4, GPTQ, AWQ)
- Human-in-the-loop annotation workflows at scale
- Production experience with at least three of the following agent frameworks and orchestration tools: LangGraph / LangChain, CrewAI, AutoGen/AG2, or equivalent, MCP (Model Context Protocol), Coding agents: Claude Code, OpenCode, or similar
- Production experience with at least two of the following evaluation and observability tools: Langfuse, LangSmith, Arize, or equivalent, LLM-as-judge evaluators, CI/CD eval gates
- Demonstrated track record mentoring engineers and raising team technical quality
- Drives decisions in ambiguous, fast-moving environments
- Writes design docs that earn buy-in across teams
Nice To Haves
- Continued pretraining or fine-tuning pipelines (SFT, DPO, RLHF)
Responsibilities
- Architect and lead multi-agent systems: design, orchestration patterns, failure modes, memory, planning, and human-in-the-loop
- Own the path from prototype to production: containerization, guardrails, cost and latency optimization, scalable serving
- Define the team's evaluation strategy: offline/online harnesses, trajectory quality, tool-call accuracy, regression testing, CI/CD eval gates
- Lead instrumentation and observability: tracing, span capture, automated scoring, closing the trace → eval → fix loop
- Drive tool integration architecture via MCP across multiple product teams
- Mentor junior and mid-level engineers through code and architecture reviews; set engineering standards
Benefits
- Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.
- SAP North America Benefits
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What This Job Offers
Job Type
Full-time
Career Level
Senior
