Senior ‘Developer Infrastructure’ Engineer

Millennium•New York, NY

8d•$175,000 - $250,000

About The Position

The Systematic Platform Execution & Exchange Data (SPEED) Team is at the core of Millennium’s Equities, Quant Strategies, and Shared Services Technology organization, powering the firm’s lowest‑latency solutions for systematic and high‑frequency trading. SPEED delivers the live trading and market‑data platforms used by portfolio managers and risk systems, including Latency Critical Trading (LCT), DMA OMS (Client Direct), DMA market data feeds, packet capture (PCAPs), enterprise market data, and intraday data services across latency tiers from sub‑100 nanoseconds to millisecond‑sensitive workflows. By building and operating this execution and data infrastructure, SPEED enables portfolio managers and researchers to compete effectively in the most time‑critical markets. As a Senior Developer Infrastructure Engineer on SPEED, you will own and evolve the build and CI/CD infrastructure that underpins these mission‑critical systems. By designing scalable build pipelines, shared tooling, and reliable release workflows, you will directly enhance developer productivity and enable fast, safe iteration on some of the firm’s most performance‑sensitive code. This role offers the opportunity to shape core engineering practices while contributing to platforms that are central to Millennium’s trading edge

Requirements

5+ years of software engineering or DevInfra/Platform/DevOps experience, with significant focus on building systems and CI/CD.
Strong programming skills in one or more languages (e.g., Python, Rust, Go, C++) for automation and tooling.
Hands-on experience with at least one modern build system (e.g., Bazel, Buck2)
Solid understanding of source control (Git), branching strategies, and release management.
Experience scaling build and test infrastructure for growing codebases and teams (parallelization, test sharding, remote execution, caching).
Experience designing or participating in processes, systems, or playbooks that leverage AI to streamline work rather than needing to add more headcount to the team.
Familiarity with containers and cloud infrastructure (Docker, Kubernetes, and major cloud providers such as AWS/GCP/Azure).
Strong communication and collaboration skills; comfortable partnering with multiple teams and driving cross-cutting initiatives.

Nice To Haves

Experience with monorepos is a plus.

Responsibilities

Design, build, and maintain a highly scalable, parallel, and cached build system for a large, performance‑sensitive codebase.
Own and continually optimize CI/CD pipelines to minimize build/test times, reduce flakiness, and improve developer productivity.
Operate with an AI‑first mindset across the SDLC, using automation by default to streamline build, test, and release workflows.
Integrate and operationalize AI tools (e.g., copilots, workflow automation, AI‑driven analytics) to eliminate manual toil, accelerate development, and codify reusable AI‑enabled patterns for the broader engineering organization.
Design and operate containerized environments (e.g., Docker, Kubernetes) to maximize utilization, reliability, and scalability across environments.
Implement and manage artifact storage, dependency management, and versioning strategies for large, distributed systems.
Develop and maintain shared libraries, CLIs, scripts, and internal platforms that reduce friction and enable self‑service for engineers.
Build and enhance test suites and environment provisioning, leveraging AI and automation where appropriate for smarter checks, triage, and observability.
Monitor, instrument, and improve the reliability, observability, and performance of build and CI/CD systems using metrics, dashboards, and alerting.
Partner with trading and engineering teams to understand requirements, remove friction, and champion best practices for building, testing, and releasing software.