Senior Software Engineer, AI Agentic Platform

Metropolis; Seattle (WA); On-site; USD 177,000 - 216,000; Full time

Benefits offered by this job

Office four days a week

Job summary

Metropolis in Seattle, WA seeks a Senior Software Engineer to architect and build our AI agent swarm, orchestration pipelines, and developer tooling. You will tackle distributed systems at scale, influence build-vs-buy decisions for AI infrastructure, and create low-latency agent orchestration frameworks enabling autonomous workflows across SDLC and business automation.

The ideal candidate has 6+ years in backend distributed systems, 2+ years for agentic AI systems, and strong skills in Python

Qualifications

• 6+ years of backend software engineering with distributed systems experience.
• 2+ years architecting/deploying agentic AI systems or AI platform tooling.
• Proficiency in Python or Java/TypeScript with API design and performance tuning.
• Experience with modern agent orchestration frameworks and protocols.
• Expertise in microservices, Kubernetes, and AWS.
• Observability and LLMOps including tracing and logging.
• Knowledge of relational/vector databases, Kafka or SQS, and caching patterns.
• Experience using AI tooling like Claude Code or Copilot for development productivity.

Responsibilities

• Design and build production-grade agentic platform infrastructure and orchestration pipelines.
• Architect low-latency LLM inference routing and caching strategies.
• Establish observability frameworks to measure accuracy and debug workflows.
• Develop SDKs and CI/CD automation for safe, scalable agent deployment.
• Implement guardrails, security policies, and data-access controls for model execution.
• Make architectural decisions on service boundaries and multi-agent communication protocols.
• Mentor peers on agentic architectural patterns and standards.

Skills

Backend distributed systems

Agentic AI

Python/TypeScript

LLMOps

Kubernetes

AWS

API design

Performance tuning

Observability

Cross-functional communication

Tools

LangGraph

Anthropic MCP

Google ADK

AutoGen

A2A

LlamaIndex

Copilot

Job description

Senior Software Engineer, AI Agentic Platform

Seattle, Washington, United States

Who we are

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.

Who you are

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.

What you'll do

• 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

What we're looking for

• 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 collaborate across cross-functional team

While not required, these are a plus:

• Advanced degree in Computer Science, Machine Learning, or related technical field
• Experience building customized agent harnesses, fine-tuning models, or implementing RLHF/RLAIF optimization loops
• Security compliance expertise regarding data privacy, prompt injection defenses, secrets management, and access controls for financial or mobility data
• Contributions to open-source agent frameworks, MCP servers, or technical writing on agentic system architectures

Our Stack

• Languages + Frameworks: TypeScript, React, Scala (principally), Java (limited)
• Cloud: AWS
• Version control: Git & GitHub
• AI Tooling: Copilot on GitHub and Claude Code

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $177,000.00 USD to $216,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis' total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans, and more. #LI-LR1 #LI-Onsite

Metropolis may utilize an automated employment decision tool (AEDT) to assess or evaluate your candidacy for employment or promotion. AEDTs are used to assist in assessing a candidate’s application relative to the required job qualifications and responsibilities listed in the job posting.

As part of this process, Metropolis retains data relevant to your candidacy, including personal information, for a period that is reasonably necessary for the use of the tool. If you are hired for the position, your data may become part of your employee records.

Metropolis Technologies is an equal opportunity employer. We make all hiring decisions based on merit, qualifications, and business needs — without regard to race, color, religion, sex (including gender identity, sexual orientation, and pregnancy), national origin, disability, veteran status, or any other protected characteristic under federal, state, or local law.

We are committed to providing a welcoming, accessible hiring experience. If you need a reasonable accommodation for any part of the application or interview process, please reach out to us at [e-mail].

Voluntary Self-Identification

For government reporting purposes, we ask candidates to respond to the below self-identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiringprocess or thereafter. Any information that you do provide will be recorded and maintained in a confidential file.

As set forth in Metropolis’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.

If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection. As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measure the effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categories is as follows:

A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service‑connected disability.

A "recently separated veteran" means any veteran during the three‑year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service.

An "active duty wartime or campaign badge veteran" means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense.

An "Armed forces service medal veteran" means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985.