Senior AI Engineer (Agentic Systems & LLM Applications)
Role details
Job location
Tech stack
Job description
This is a high-ownership, builder role for engineers who want to push beyond "feature-level AI" and design systems that actually reason, act, and operate in production.
You will own end-to-end development of AI systems - from architecture and design through deployment, evaluation, and iteration. The focus is on building agentic systems and retrieval-driven pipelines that can handle complex, multi-step workflows across large volumes of structured and unstructured data.
This role is best suited for engineers who have already shipped LLM-based systems and want to go deeper - improving system reliability, designing evaluation frameworks, and building AI that can be trusted in high-stakes environments.
You'll work closely with product and engineering leadership to define what gets built, not just how it gets built., * Architect and deploy production LLM systems capable of multi-step reasoning and decision support
- Build and scale agentic workflows that automate complex, long-running processes
- Design end-to-end RAG pipelines (ingestion, embeddings, retrieval, ranking, generation)
- Develop evaluation frameworks and guardrails to ensure system accuracy, reliability, and safety
- Optimize systems for latency, cost efficiency, and production performance
- Partner with product and engineering leaders to identify and prioritize high-impact AI opportunities
- Contribute to backend systems and infrastructure supporting large-scale AI deployment
Requirements
- 7+ years of software engineering experience, including 2+ years building AI/ML systems
- Strong Python expertise and experience building production-grade systems
- Proven track record shipping LLM-based applications into production
- Hands-on experience with RAG pipelines, embeddings, and vector databases
- Experience building agent-based or multi-step AI systems
- Strong system design skills with experience in distributed systems
- Clear ownership of systems from initial concept through production and iteration
Nice to Have
- Experience with workflow orchestration or distributed task systems
- Familiarity with backend systems or TypeScript-based services
- Experience working with document-heavy or high-complexity datasets
- Exposure to evaluation frameworks, monitoring systems, or AI safety practices
Benefits & conditions
Why Join
- Build AI systems that operate in real-world, high-stakes environments - not prototypes
- Own the architecture and evolution of agentic systems used by real customers
- Work on problems where correctness, reliability, and trust actually matter
- High autonomy with direct influence on product direction and technical strategy
- Strong compensation, meaningful equity, and comprehensive benefits
- In-person collaboration Tuesday-Thursday with a focused, high-caliber engineering team
- Opportunity to raise the technical bar alongside engineers who have shipped real systems