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:

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/Google Cloud Platform)
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.

Preferred Skills:

AI Engineering Lead

Key skills