AI Solution Engineer

We are looking for engineers who can move fast across the full AI stack, from applied research/benchmarking and prototyping to production deployment, and who bring both technical depth and the curiosity to keep pace with a rapidly evolving landscape.

Responsibilities

Design and build LLM-powered applications using frontier models (OpenAI, Anthropic, Gemini) and open-source alternatives, across the full stack from data ingestion and vector stores through to model serving and deployment

Architect agentic workflows including tool calling, memory, planning, and multi-agent orchestration using frameworks such as LangGraph and CrewAI, as well as with native LLM primitives

Integrate AI systems with external tools, services, and data sources using primitives like A2A, MCP, and API function calling

Rapidly prototype and iterate using agentic coding tools such as Claude Code, Codex, and Antigravity to accelerate development cycles

Apply prompt engineering, RAG pipelines, and LLM evaluation techniques to build reliable, production-grade AI systems

Translate complex business problems into practical AI solutions, working both as part of cross-functional teams and as an independent contributor with end-to-end ownership

Scan the landscape to identify state-of-the-art frontier as well as open weight models, and make recommendations for specific solutions

Requirements / What We're Looking For

Strong hands-on experience building LLM-powered applications, with working knowledge of at least one frontier model provider and familiarity with open-source alternatives

Demonstrated ability to architect AI-native solutions and pipelines end-to-end

Experience designing agentic systems, with practical knowledge of agent frameworks, orchestration patterns, and integration primitives

Ability to synthesize data from disparate systems and build pipelines that construct rich, reliable context for AI applications

Familiarity with at least one major cloud platform (AWS, Azure, or GCP) for AI application deployment

A self-driven learning orientation, actively following developments in LLMs, agent frameworks, and the broader AI ecosystem

10+ years of experience architecting and building robust, enterprise-grade systems, with a track record of taking complex solutions from concept to production at scale