Lead Specialist, Technical Architect
On-siteBengaluru, Karnataka, India
Bengaluru, Karnataka, IndiaOn-siteFull TimeSenior LevelEducational ServicesEnterprise
Full TimeSenior LevelEnterpriseEducational Services
Job Summary
Architect the future state of Pearson's AgentOps platform by defining target-state patterns for orchestration, runtime, and evaluation, then prove hard trade-offs with reference implementations rather than diagrams. Scout emerging agentic-AI technologies and de-risk them through rapid POCs and MVPs that establish clear paths to production. Design multi-agent workflows, routing logic, and resilience patterns for non-deterministic AI, while building reusable components and standards for skills, tools, and observability. Mentor IC20–IC25 engineers through design reviews and hands-on guidance to raise the team's engineering bar.
Required Qualifications
- Staff-level engineer
- Designed and built production-grade agentic systems
- Scout emerging technology and de-risk it through rapid POCs and MVPs
- Deep Python and backend/platform engineering—async services, typed code, and clean, scalable architecture
- Set patterns and standards others adopt: orchestration, agent tooling, runtime, and resilience for non-deterministic AI
- Design and build agent orchestration and routing across frameworks—delegation, retries, fallback, structured outputs, human-in-the-loop
- Own a real platform codebase end-to-end—APIs, runtime, storage
- Strong prompt engineering for structured outputs, nested schemas, and multi-agent coordination
- Mentor engineers and lead through design and code reviews, without managing them
- Live Our Purpose: connect technical direction to Pearson's mission and strategy
- Simplify the Complexity: set direction in a fast-changing field, distilling complex agentic systems into clear, reliable architecture
- Carry Our Culture: lead through design and code reviews, mentor engineers, and raise the bar without authority
- Deliver Results: set the quality bar, own the hardest technical outcomes, and ship the patterns the platform depends on
- Work Location/s: Bengaluru, India
Desired Qualifications
- Experience defining evaluation strategy for agentic systems—groundedness, tool-use accuracy, regression suites
- Experience with tool/context interoperability protocols (such as MCP)
- Deep experience with a major cloud platform (AWS preferred)
- Experience with containerization, CI/CD, and state stores for orchestration and persistence
- AI observability and evaluation tooling for LLM systems
- RAG and memory patterns: vector databases, hybrid retrieval, re-ranking, and grounding
- Secure execution, sandboxing, and prompt-injection mitigation
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