Senior Software Engineer (Tech MNC/ AI Platform/ LLM/ UP12K+)

The Opportunity

• Adecco is partnering our client, a famous Tech MNC
• We are looking for a Senior Software Engineer
• The role will start out as a 6-months contract (renewable)
• Candidates who are immediately available/ able to start work within short notice will be preferred

The Talent

• Minimum of 2 years experience in or at at least most:
• EvalsHub, LangSmith, LangGraph/LangChain, FastAPI, Temporal, Grafana, Redis, or similar technologies.
• React/TypeScript and internal developer-tooling interfaces.
• LLM-as-judge, multi-turn evaluation, tool/MCP evaluation, and agent-trajectory analysis.
• Text-to-SQL/Text-to-DSL, RAG, semantic retrieval, embedding evaluation, or model benchmarking.
• Building platform capabilities that can be reused across several AI products.
• Strong analytical and problem-solving skills related to geo data
• Excellent project management and cross-department communication abilities
• Detail-oriented and metrics-driven approach to continuous improvement

Job Description

• Embed with AI product teams and own measurable agent-quality outcomes.
• Build and maintain golden datasets, regression suites, evaluation pipelines, and quality dashboards.
• Convert product rules and human review procedures into deterministic, numeric, LLM-as-judge, trajectory, tool-selection, SOP-adherence, and multi-turn evaluators.
• Diagnose evaluation and production-trace failures, then convert findings into dataset improvements, evaluator changes, or fixes to prompts, tools, skills, and agent workflows.
• Instrument distributed agent systems using OpenTelemetry, including Temporal workflows and Go/Python services.
• Ensure traces contain consistent inputs, outputs, tool calls, metadata, feedback, and root-agent results.
• Develop reusable capabilities across EvalsHub backend, SDK, CLI/plugins, and supporting frontend interfaces.
• Integrate evaluations into CI/CD and model-release workflows.
• Run model, retrieval, embedding, and agent-architecture experiments balance accuracy, latency, and cost.
• Drive migrations from legacy evaluation and observability systems.
• Write technical designs and documentation, run demonstrations, and enable engineering teams to use evaluation tooling independently.
• Participate in the LLMOps operational rotation and support production-quality integrations.

Next Step

• Prepare your updated resume
• Send your resume to [Confidential Information]
• All shortlisted candidates will be contacted

Liu XinYang

EA Licence Number: 91C2918

Personnel Registration Number: R1988872