Software Architect - AI Accelerated Engineering Lead (west)

Software Architect

As a Software Architect, you will own the architecture of client solutions while pioneering the next generation of AI-empowered software development. You'll lead teams in adopting AI-first engineering practices-bringing clarity, structure, and guardrails to how organizations build with generative AI.

You'll join a tightly knit product team-engineers, product leaders, designers, and data practitioners-who co-create modern software with our customers. We move from discovery to delivery together, pairing on code, pressure-testing ideas with real users, and turning learnings into ship-ready increments. You'll collaborate with customer stakeholders and field teams to bring outside-in insights into the roadmap, and you'll help enable clients on the practices and tools we use so they can sustain value long after launch. Think craft-driven Builders who care about outcomes, not just output.

Redefine the AI-first SDLC: Design flows, patterns, and guardrails that integrate generative AI from ideation through operations.

Lead with @context engineering: Apply and guide strategies like prompt templating, embeddings, retrieval-augmented generation, and data grounding to ensure AI-driven development is accurate, reliable, and safe.

Manage GenAI-driven teams: Orchestrate multi-developer environments where AI agents and engineers work side by side-ensuring productivity, quality, and responsible adoption.

Ship AI-enabled platforms: Build and codify repeatable practices such as evaluation harnesses, code-review agents, @context packs, and CI/CD hooks.

Stay hands-on: Own product architecture while prototyping and hardening AI-driven solutions using modern DevOps and observability practices.

Enable and transform: Coach teams and client stakeholders on AI-accelerated ways of working; translate complex AI concepts into clear business outcomes.

Experience: 6+ years building and operating production software, with proven leadership in system or platform architecture.

Hands-on AI-accelerated development: Daily use of agentic IDEs and advanced tooling (e.g., GitHub Copilot, Cursor, Claude Code) beyond basic chat interfaces.

Proven track record with GenAI integration: Experience delivering solutions where multiple developers collaborated with generative AI and AI agents using @context engineering strategies.

Architecture expertise: Deep knowledge of APIs, microservices, eventing, reliability, and security.

Programming skills: Proficiency in languages like TypeScript/Node, Python, or Java; comfort with React/Next and modern frameworks.

Cloud & DevOps: Strong background with AWS/Azure/GCP, Kubernetes, CI/CD, IaC, and production observability.

Leadership & communication: Ability to guide teams, mentor engineers, and articulate value to both technical and business audiences.

Bonus Skills

AI orchestration frameworks (LangChain, LlamaIndex), vector databases, or model routing experience.

MLOps, AI governance, or safety practices.

Contributions to open source or thought leadership in AI-accelerated engineering.