AI/ML Engineering
About The Position
The AI/ML Engineering role is a 12+ month contract based in Sunnyvale, California, with three days of work from the office. The role leads service rationalization and decomposition across complex enterprise ecosystems and designs and builds API-first, event-driven architectures. It also contributes hands-on to domain services, integrations, and proofs of concept; enables service reuse through catalogs, standards, and governance; and drives incremental legacy modernization using approaches such as the strangler pattern. The position partners with global teams to promote a platform-first mindset and helps build systems ready for AI agents, automation workflows, and future integrations. It combines architecture design, hands-on engineering, and engineering-team leadership, with a pragmatic, delivery-focused approach.
Requirements
- 10+ years of strong engineering and architecture execution experience.
- Deep hands-on experience building and delivering production-grade systems in enterprise environments.
- Expertise in microservices, REST or GraphQL APIs, event-driven architecture using Kafka, and cloud platforms such as AWS, Azure, or GCP.
- Ability to move between architecture design, hands-on coding, and leading engineering teams with a pragmatic, delivery-focused mindset.
- Strong experience with domain-driven design (DDD), service decomposition, and distributed system design.
- Hands-on track record breaking down monoliths or fragmented systems into reusable service layers.
- Experience leading incremental modernization efforts, such as the strangler pattern, focused on reuse, scalability, and clean service boundaries.
- Proven experience building MCP server-based solutions and Gen AI agents from concept through production.
- Strong understanding of designing systems for an agentic, AI-driven ecosystem and integrating AI into service architectures to make platforms ready for future automation and intelligence.
- Deep understanding of zero-trust architecture, API security, and identity federation.
- Hands-on experience with CI/CD pipeline design, GitOps workflows, and release engineering.
- Ability to make and communicate well-reasoned architectural trade-offs.
Nice To Haves
- Expertise with Claude Code or similar AI-assisted development tools.
- Experience building service catalogs or internal developer platforms.
- Background in highly distributed, multi-region enterprise environments.
- Exposure to AI-driven automation workflows at scale.
Responsibilities
- Lead service rationalization and decomposition across complex enterprise ecosystems.
- Design and build API-first, event-driven architectures.
- Contribute hands-on to domain services, integrations, and proofs of concept.
- Enable service reuse through catalogs, standards, and governance.
- Drive incremental legacy modernization, including use of the strangler pattern.
- Partner across global teams to influence a platform-first mindset.
- Build systems ready for AI agents, automation workflows, and future integrations.
- Build MCP server-based solutions and Gen AI agents from concept through production.
- Design observability strategies covering distributed tracing, structured logging, and metrics dashboards.
- Make and communicate well-reasoned architectural trade-offs.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Career Level
Senior
Education Level
No Education Listed
