AI/ML Engineering

Job Title: AI/ML Engineering

Location: Sunnyvale, CA (3 days onsite per week)
Duration : 6+ Months 

Job Description

We are seeking an experienced AI/ML Engineering professional with a strong background in enterprise architecture, distributed systems, and modern AI-driven platforms. The ideal candidate will lead large-scale modernization initiatives, design scalable API-first architectures, and contribute hands-on to building intelligent, future-ready enterprise systems.

Key Responsibilities

• Lead service rationalization and decomposition across complex enterprise ecosystems
• Design and develop API-first and event-driven architectures
• Build and contribute hands-on to domain services, integrations, and proof-of-concepts
• Drive service reuse through governance, standards, and service catalogs
• Modernize legacy applications using incremental transformation approaches such as the strangler pattern
• Collaborate with cross-functional global teams to promote a platform-first engineering mindset
• Develop systems optimized for AI agents, automation workflows, and future integrations
• Design observability strategies including distributed tracing, structured logging, and metrics dashboards
• Implement secure architectures with a strong focus on zero-trust principles, API security, and identity federation
• Support CI/CD pipeline design, GitOps workflows, and release engineering best practices
• Evaluate and communicate architectural trade-offs effectively

Required Skills

• 10+ years of hands-on experience building enterprise-grade distributed systems
• Strong expertise in microservices architecture, REST/GraphQL APIs, Kafka, and cloud platforms such as AWS, Azure, or Google Cloud Platform
• Solid experience with domain-driven design (DDD), service decomposition, and distributed architecture patterns
• Proven experience modernizing monolithic systems into scalable reusable service layers
• Hands-on experience building MCP server-based solutions and Gen AI agent platforms
• Strong understanding of AI-enabled and agent-driven system architecture
• Experience integrating AI capabilities into enterprise service ecosystems
• Expertise in observability, monitoring, and platform reliability engineering
• Strong understanding of security architecture and enterprise identity solutions
• Experience with DevOps, CI/CD automation, GitOps, and release engineering
• Excellent problem-solving and technical leadership skills

Preferred Skills

• Experience with AI-assisted development tools such as Claude Code
• Knowledge of internal developer platforms and service catalogs
• Experience working in highly distributed multi-region enterprise environments
• Exposure to AI-driven automation workflows at scale