About this role
Culture Amp needs a Senior Applied AI Engineer to address the challenge of building production-ready, agentic AI solutions that translate complex workplace data into meaningful context. Operating within the Frontier team, this individual will sit at the intersection of applied research and product engineering to ship features that directly impact how millions of employees experience work. The work involves developing multi-turn conversational systems, orchestrating context graphs, and implementing scalable retrieval-augmented generation frameworks.
Candidates joining this team will design stateful architectures, build session memory grounded in custom ontologies, and own the end-to-end feedback loop for LLM-powered tools. Success in this role requires a pragmatic, solution-focused mindset capable of balancing technical ambition with enterprise requirements for transparency and responsible AI. Ideal candidates combine strong full-stack foundations with hands-on production experience in deploying machine learning systems and knowledge graphs.
What you will do
- Design and implement agentic AI capabilities utilizing frameworks like LangGraph for multi-turn conversations.
- Orchestrate data pipelines that integrate workplace metrics such as surveys, performance reviews, and feedback into a coherent context view.
- Build session memory, context graphs, and per-user procedural memory that persist securely to user profiles.
- Develop and evaluate retrieval-augmented generation systems incorporating pre-processing and hybrid search mechanisms.
- Manage the complete feedback loop encompassing prompt engineering, scalable evaluation, and continuous system improvement.
- Collaborate closely with product, design, and people science teams to ensure features scale appropriately for enterprise needs.
- Establish production guardrails, safety protocols, and bias testing frameworks to meet responsible AI standards.
What you need
- Demonstrated commercial experience successfully moving machine learning and artificial intelligence systems into production environments.
- Practical background working with knowledge graphs and graph databases including Neo4j or Neptune.
- Familiarity with production LLM evaluation and observability tools such as Langfuse, LangSmith, LLM-as-judge, and tracing mechanisms.
- Experience designing and scaling production-grade multi-agent architectures, RAG frameworks, and prompt engineering strategies.
- Proficiency in full-stack software development with working knowledge of Python, React, and PGVector.
- Solid software engineering fundamentals demonstrating the ability to write clean, tested, and maintainable code.
- Ability to delegate complex workflows to autonomous agents and build reliable feedback loops for automated actions.
Nice to have
- Experience at startups or founding teams with comfort in ambiguity
- Postgraduate degree in Machine Learning, Computer Science, or Applied Mathematics
- Familiarity with people analytics, HR technology, or behavioural science applications
- Open source contributions or public technical writing
- Experience implementing GraphRAG or advanced knowledge graph structures
Benefits
- Equity through the Employee Share Option Program
- Learning programs and coaching
- Quarterly refresh days, an extended end-of-year break and a monthly wellbeing allowance
- Inclusive parental leave from day one
- MacBook and home workspace setup budget
- Five annual social impact days
Skills and tech stack
Questions candidates ask
What is the remote work policy?
Employees work from their local Culture Amp office an average of two days a week to support connection and culture. The company is a believer in the power of in-person collaboration.
What kind of team will I be joining?
You will join the Frontier team, which focuses on building agentic AI solutions at Culture Amp. The team works at the intersection of applied AI research and product engineering.
What technologies and tools are used in this role?
The tech stack includes Python, React, PGVector, LangGraph for stateful conversations, graph databases like Neo4j or Neptune, and observability tools such as Langfuse and LangSmith.
What benefits are provided with the position?
Benefits include equity through an Employee Share Option Program, learning and coaching programs, a monthly wellbeing allowance, inclusive parental leave, and a MacBook with a home workspace setup budget.