Senior AI Engineer (AI-Native)

About the Role

We're looking for a Senior AI Engineer who doesn't just work with AI, they think in it. This is a role for someone who has internalized AI-first development patterns, builds with LLMs as a primary primitive, and can architect systems that put intelligent automation at the core rather than the edge.

What You'll Do

• Design and build production-grade AI systems including LLM-powered pipelines, agentic workflows, and retrieval-augmented generation (RAG) architectures

• Lead the integration of AI capabilities across products, from prototyping through to scalable deployment

• Evaluate, fine-tune, and optimize foundation models for specific use cases; stay current on the rapidly evolving model landscape

• Define engineering best practices for prompt engineering, model evaluation, observability, and safety guardrails

• Collaborate with product and platform teams to identify high-leverage AI opportunities

• Mentor engineers on AI-native development patterns and help level up the broader team

What We're Looking For

• 5+ years of software engineering experience, with at least 2 years focused on applied AI/ML systems

• Deep hands-on experience with LLM APIs (OpenAI, Anthropic, Gemini, etc.) and orchestration frameworks such as LangChain, LlamaIndex, or similar

• Strong programming skills in Python, TypeScript, or equivalent, we care more about engineering fundamentals than language loyalty

• Experience with vector databases (Pinecone, Weaviate, pgvector), embeddings, and semantic search

• Proven ability to ship AI features to production, not just demos or notebooks

• Comfort operating in ambiguity: you can take a vague idea and turn it into a scoped, working system

• Experience with evaluation frameworks, A/B testing for model outputs, and monitoring for model drift or degradation

Nice to Have

• Experience with fine-tuning or RLHF workflows

• Familiarity with multi-agent architectures and tool-use patterns

• Background in ML engineering (training pipelines, model serving, MLOps)

• Contributions to open-source AI projects

What "AI-Native" Means to Us

This isn't a traditional ML role retrofitted with a trendy title. We mean someone for whom AI is the default lens, who reaches for an LLM-based solution where others would reach for a rule engine, who understands the tradeoffs between prompt engineering and fine-tuning, and who builds systems that stay useful as the underlying models evolve.