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Weekend Interviews – AI/ML Engineering – Sunnyvale, CA ( 3 days work from office)

Title: AI/ML Engineering

Location : Sunnyvale, CA ( 3 days work from office)

Experience- 10 – 13 Years, H1B Needed

Weekend Interviews Must – Sat and Sunday

Responsibilities / Experience:

  • 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 POCs
  • Enable service reuse through catalogs, standards, and governance
  • Drive incremental legacy modernization (strangler pattern)
  • Partner across global teams to influence a platform-first mindset
  • Build systems ready for AI agents, automation workflows, and future integrations

 Qualifications/Required Skills:

1. Strong Engineering & Architecture Execution (10+ years)

  • Deep hands-on experience building and delivering production-grade systems in enterprise environments
  • Expertise in microservices, APIs (REST/GraphQL), event-driven architecture (Kafka), and cloud platforms (AWS/Azure/GCP)
  • Proven ability to move between architecture design, hands-on coding, and leading engineering teams with a pragmatic, delivery-focused mindset


2. Service Decomposition & Enterprise Modernization

  • Strong experience with domain-driven design (DDD), service decomposition, and distributed system design
  • Hands-on track record breaking down monoliths/fragmented systems into reusable service layers
  • Experience leading modernization efforts using incremental approaches (e.g., strangler pattern) with a focus on reuse, scalability, and clean service boundaries


3. MCP Servers & Gen AI / Agent-Based Systems

  • 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
  • Ability to integrate AI into service architectures and make platforms “agent-ready” for future automation and intelligence

4. Experience designing observability strategies: distributed tracing, structured logging, metrics dashboards 

5. Deep understanding of zero-trust architecture, API security, and identity federation

6. Hands-on experience with CI/CD pipeline design, GitOps workflows, and release engineering

7. Ability to make and communicate well-reasoned architectural trade-offs.

Preferred Skills:

  • Expertise with Claude Code or similar AI-assisted development tools
  • Experience building service catalogs / internal developer platforms
  • Background in highly distributed, multi-region enterprise environments
  • Exposure to AI-driven automation workflows at scale

 

Thanks

Yogesh Sharma K,

Reveille Technologies, Inc

yogesh@reveilletechnologies.com

About Author

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