About the role
The Senior Advanced Research Engineer operates at the intersection of AI systems research and production engineering, focusing on building scalable and trustworthy enterprise agentic AI. The role involves investigating complex problems in AI memory systems and inference routing, then translating these research findings into production-ready SDKs and platform capabilities.
ConsultingOnsiteOther Functions
Key Responsibilities
- Investigate active innovation frontiers in agentic AI systems, including agent memory, knowledge persistence architectures, and inference routing strategies.
- Design and execute rigorous benchmarking and evaluation methodologies scoped to production-relevant agentic task profiles.
- Investigate efficiency and scalability frontiers, such as inference cost reduction and context management at scale, to ensure commercial viability on hardware.
- Translate research findings into production-grade implementations such as engineered Python services or Node.js/TypeScript SDK modules.
- Build well-defined provider interfaces and pluggable backends for research components including memory stores and retrieval layers.
- Prototype and validate platform-level capabilities like inference routing policies and agent control mechanisms from experiment to integrated system.
- Instrument research prototypes with observability including distributed tracing, cost accounting, and latency metrics.
- Integrate validated research capabilities into production systems through standard engineering workflows like code review and CI.
- Communicate research findings, architectural trade-offs, and prototype results to technical peers and non-technical stakeholders.
- Mentor junior engineers and researchers on experimental methodology and production-quality code standards.
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, or a related field, or equivalent experience.
- 5 years of experience with Python and/or Node.js/TypeScript building production backend services or AI/ML systems.
- 5 years of hands-on experience with AI or ML systems including large language models and agent frameworks.
- Strong Python engineering skills with the ability to move between experimental research and structured service modules.
- Demonstrated ability to translate research findings into platform-integrated or published artefacts.
- Hands-on experience with async Python such as FastAPI and asyncio.
- Experience with containerisation and orchestration using Kubernetes.
- Proficiency with vector and relational databases and distributed tracing instrumentation like OpenTelemetry.
- Familiarity with modern AI agent framework ecosystems and agent communication protocols.
- Willingness and ability to travel 0 to 100% depending on business need and client requirements.
- Master's or PhD in Computer Science or Computer Engineering is strongly preferred.
- Track record of shipping research into running systems across both research and production contexts.