Senior Software Engineer, AI Agentic Platform

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn't coming; it's here, and we need builders, innovators, and problem solvers to help us create it.

Metropolis is seeking a Senior Software Engineer to architect and build our AI agent swarm, orchestration pipelines, and developer tooling. In this role, you will solve complex distributed systems challenges at scale, make critical build-vs-buy decisions on rapidly-evolving AI infrastructure, and construct low-latency agent orchestration frameworks that enable product engineering teams to deploy autonomous workflows seamlessly supporting both SDLC and business process automation. Working alongside highly technical hypernerds who live and breathe performance optimization, model routing, reliability engineering, and agent protocols, you will collaborate across Application Engineering, Infrastructure, and Advanced Technologies to deliver remarkable, checkout-free real-world experiences.

• Design and build production-grade agentic platform infrastructure, including harness, orchestration pipelines, tool-use abstractions, MCP integrations, and context/memory management systems.

• Architect high-throughput, low-latency LLM inference routing, caching strategies, and semantic search interfaces to optimize cost, performance, and token usage

• Establish robust evaluation, tracing, and observability frameworks (LLMOps/AIOps) to measure agent accuracy, monitor execution paths, and debug non-deterministic workflows

• Build developer tooling, agent SDKs, and CI/CD automation that empower product engineering teams to deploy autonomous AI agents safely and efficiently

• Implement enterprise-grade guardrails, rate-limiting, sandboxing, and security policies for model execution and tool access

• Make critical architectural choices regarding service boundaries, data consistency, multi-agent communication protocols, and overall system reliability

• Drive technical standards, evaluate emerging AI tooling, and mentor engineering peers on agentic architectural patterns

• 6+ years of backend software engineering experience with deep focus on distributed systems, platform infrastructure, and high-load production environments

• 2+ years of hands-on experience architecting and deploying agentic AI systems, LLM orchestration frameworks, or AI platform tooling

• Strong proficiency in Python or Java/TypeScript with production expertise in async concurrency, API design, and system performance tuning

• Production experience with modern agentic orchestration frameworks and protocols such as LangGraph, Anthropic MCP, Google ADK, AutoGen, A2A, or LlamaIndex

• Expertise in microservices architecture, container orchestration (Kubernetes), and cloud platforms (AWS)

• Observability and LLMOps expertise, including metrics, distributed tracing, structured logging, and debugging agent execution runs

• Database and data systems knowledge including relational databases, vector databases, event streaming (Kafka, SQS), and caching patterns

• Demonstrated experience leveraging AI-powered development tools such as Claude Code, GitHub Copilot, or similar agentic coding tools for enhanced productivity and context engineering

• Excellent technical communication with the ability to design and document complex AI architectures and