AI/ML Engineering Engineer

Cloudious•Sunnyvale, CA

About The Position

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.

Requirements

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

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