Lead Consultant Cloud Platform Azure API Gateway

Overview

In this role you will design and deliver AI-native capabilities and agentic workflows that solve real business problems at scale. You will contribute to a reusable AI delivery platform, enabling engineers to build AI features with platform-first abstractions. You will own end-to-end delivery of AI features and ensure governance, observability, and reliability in enterprise environments. This is a hands-on, production-focused position that emphasizes impact, ownership, and rapid experimentation within a fast-paced AI-first culture.

Responsibilities

• Build AI-native capabilities and multi-agent workflows to address business problems across operations, service health, and enterprise processes
• Develop LLM-powered features via various APIs (OpenAI, Google, AWS, Anthropic) using patterns like RAG, tool usage, planning, and memory
• Contribute to the AI Delivery Platform (AIDLC) by creating reusable components for orchestration, tooling, evaluation, guardrails, and observability
• Deliver end-to-end AI features from concept to production, implementing closed-loop workflows (detect, reason, act, validate)
• Operationalize AI at scale with evaluation, monitoring, feedback loops, and enterprise-grade governance and reliability
• Advance AI engineering through prompt engineering, orchestration, knowledge grounding, and mentorship to other engineers
• Mentor engineers on AI-first development approaches and foster a culture of rapid experimentation and measurable delivery

Key requirements

• 5+ years in software/platform engineering with a strong delivery focus
• Experience building production-grade LLM-powered applications or agentic systems (not prototypes)
• Background in enterprise platform engineering, cloud-native development, or distributed systems
• Familiarity with enterprise AI delivery lifecycle concepts (governed, scalable, auditable)
• Strong production experience in Python; TypeScript/JavaScript, FastAPI/AsyncIO, OpenAPI/AsyncAPI/Protobuf
• Experience with cloud environments (GCP preferred, AWS), Kubernetes, Docker, and CI/CD (GitHub Actions, Cloud Build)
• Experience with vector databases, NoSQL/SQL databases, and storage (VectorDB, Firestore, MongoDB, PostgreSQL, GCS)
• Knowledge of observability and governance tools (OpenTelemetry, Grafana, SLOs, DORA metrics)
• Experience with agentic AI systems and inter-agent communication protocols (A2A/ACP)
• Mentoring experience and platform-first mindset; ability to ship production-grade systems across teams
• Knowledge of prompt engineering, evaluation tooling, and responsible AI practices

• ownership
• ability to work in fast-paced environments
• mentorship and collaboration
• Google Agent Development Kit (ADK)
• LangChain & LangGraph
• Model Context Protocol (MCP) - FastMCP