We build the evaluation layer that validates AI agents before they reach customers — an automated system that scores across large volumes of agent traces.
You'll own core parts of that platform: the pipeline that runs traces through model-based judges at scale, and the scoring logic that turns raw output into results teams can act on.

What you'll do
- Design evaluation methodologies and benchmarks for agent reasoning, planning, tool use, reliability, and safety — across LLM-as-a-Judge, trajectory-based, and human evaluation
- Take problems from research question to prototype to shipped feature, owning them end to end
- Build and harden the pipelines and scoring logic behind customer-facing evaluation
- Curate synthetic and real-world datasets; measure the evaluator itself for consistency and agreement with human labels

What we're looking for
- 5+ years in ML, applied AI, prompt engineering, agentic AI, including shipping something real to users
- Strong Python skills
- Practical depth in agentic AI and context engineering: planning, reasoning, memory, tool use, retrieval,



long-context
- Experience designing evaluation methodologies, not just running evaluations
- Hands-on production work with LLM APIs — prompt engineering, structured output, cost and latency tradeoffs
- Clear communication with technical and non-technical audiences
- Good to have Experience with AI-assisted development tools (Claude code, Windsurf, or similar)

Work Personas

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Equal Prospect Employer

ServiceNow is an equal opportunity employer. All qualif

📌 Senior Research Scientist, Agentic AI (Hyderabad)
🏢 ServiceNow
📍 Hyderabad