26 days ago
Mountain View, CA, USA or San Francisco, CA, USASenior
Responsibilities
- Partner with customer engineering, product, business, and domain teams to discover workflows, constraints, and high-value AI opportunities.
- Design AI-powered systems integrating models with customer data, tools, APIs, applications, identity systems, and security controls.
- Build prototypes, production applications, APIs, integrations, internal tools, and workflow automation using AI models.
- Own deployments from prototype through production, including testing, rollout planning, observability, reliability, and operational readiness.
- Define evaluations and feedback loops for model quality, grounding, accuracy, latency, cost, safety, and workflow impact.
- Drive customer adoption and communicate deployment learnings to Product, Research, Engineering, Safety, and go-to-market teams.
Requirements
- Strong experience in software engineering, applied AI engineering, product engineering, solutions engineering, platform engineering, or technical consulting.
- Hands-on programming experience with Python and at least one of TypeScript, JavaScript, Go, Java, C++, or Rust.
- Experience building production software systems, APIs, integrations, backend services, data pipelines, or customer-facing applications.
- Understanding of LLM application patterns including prompts, context windows, RAG, embeddings, tool or function calling, agents, evaluations, and model orchestration.
- Strong system design judgment concerning reliability, security, scalability, latency, cost, and maintainability.
- Ability to work directly with customer technical and business teams in ambiguous, fast-moving environments.
- Excellent communication, ownership, product judgment, and ability to deliver production outcomes.
- Preferred qualifications include production deployment of LLM, generative AI, agentic, or AI assistant systems; experience with OpenAI API, ChatGPT Enterprise, Codex, retrieval systems, vector databases, enterprise integrations, observability, and evaluation frameworks; and customer-facing engineering or complex enterprise deployment experience.
Benefits
- Hybrid work arrangement in San Francisco, United States.
Categories
Forward Deployed
