---
title: 'Staff AI Platform Engineer at Code Metal'
canonical: 'https://feeny.ai/job/staff-ai-platform-engineer-code-metal-boston-cr0dg54w6ape'
type: 'job'
last_seen: '2026-10-18'
---

# Staff AI Platform Engineer at Code Metal

- **Company:** Code Metal
- **Location:** Boston, MA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-10-06
- **Last confirmed live:** 2026-10-18
- **Apply:** https://jobs.ashbyhq.com/code-metal/d940836d-3c14-4ac4-a16b-e0d690320f99

## Job description

## About Code Metal

Code Metal is the leader in automated software engineering you can trust. As AI writes more of the world's code, the bottleneck in software has shifted from writing code to verifying it works, and AI cannot verify its own work with certainty. Code Metal takes a fundamentally different approach: constrain AI to what it does reliably, verify every step independently of the model using formal methods, and keep engineers in the loop on the decisions that matter. The result isn't code that probably works — it's code that is provably correct, with auditable proof. Customers including the U.S. Air Force, L3Harris, RTX, and Toshiba use Code Metal to modernize legacy code, optimize performance on real hardware, and move prototypes to production, fast. Founded in 2023 with offices in Boston and San Francisco, Code Metal is funded by Accel, Salesforce Ventures, B Capital, Smith Point Capital, J2 Ventures, Shield Capital, Overmatch, RTX, and others. Learn more at [codemetal.ai](http://codemetal.ai).

## The Role

Code Metal's engineering teams are building AI-driven code transpilation, modernization, optimization, modeling and simulation solutions. They all need the same foundations: models to serve, agents to run, context to manage, and results to measure. Our AI Platform team builds those foundations. As a Staff AI Platform Engineer, you'll be a technical lead on this team. You'll architect and build the AI enablement stack our engineers depend on, from GPU inference serving and model gateway up through agent harnesses, context engineering, observability, and AI experimentation management. It is an internal platform, but we're building it to product standard. This is an engineering role first. Most of your time goes to designing, building, and operating production systems. You'll also need solid data science and AI research fundamentals: you'll work closely with our AI Research team, and you'll sometimes run experiments yourself when a platform decision needs evidence. Core Responsibilities

- Set the technical direction and architecture for Code Metal's AI platform and the team building it. Own the design docs and RFCs, help with build-vs-buy decisions, and align with other technical stakeholders.
- Deploy, benchmark, and tune elastic, production inference for open-weight models on runtimes such as vLLM, SGLang, and TensorRT-LLM.
- Own the model gateway that teams use to reach self-hosted and commercial models, with consistent auth, routing, failover, quotas, and cost attribution.
- Design reusable agent harnesses and orchestration primitives that product teams can compose into reliable, verifiable workflows.
- Build context-engineering services for memory, retrieval, and data discovery, so agents get the information specific to their tasks.
- Instrument the stack end to end, for example, with OpenTelemetry traces and service metrics. Build the experiment-tracking and artifact layer that lets engineers and researchers reproduce and compare results.
- Design for productization from day one (versioned APIs, security, deployment in customer environments), and communicate with business and product teams about the roadmap.

Required Qualifications

- Production-grade Python and strong platform engineering fundamentals: API and service design, distributed systems, containers and Kubernetes, CI/CD, and testing.
- Shipped production agentic systems, with a clear sense of where they break and how to make them reliable.
- Experience with context engineering: retrieval-augmented generation, embeddings, vector / hybrid search, and memory for agents, ideally over code or large technical corpora.
- Experience instrumenting services (for example, with OpenTelemetry tracing and metrics) and operating AI services against SLOs.
- Solid data science and AI research fundamentals: how transformers and LLM inference work, experiment design, benchmarking, and model evaluation. Working familiarity with PyTorch and Hugging Face, and experience fine-tuning, evaluating, or serving language models.
- Staff-level technical leadership: owned architecture across multiple systems or teams, written design docs and RFCs, turned ambiguous needs from several internal customers into a roadmap, and mentored engineers.

## Preferred Qualifications

- Highly desirable: Production experience running an LLM gateway or proxy such as SMG or Bifrost, or equivalent experience building an API gateway, including routing, auth, rate limiting, quotas, failover, and cost attribution.
- Hands-on experience deploying and tuning LLM inference engines such as vLLM, SGLang, or TensorRT-LLM on GPU infrastructure, with measurable gains in throughput, latency, or cost per token.
- Familiarity with inference optimization: speculative decoding, prefix caching, tensor/pipeline/expert parallelism, disaggregated prefill and decode, GPU profiling.
- Experience building evaluation harnesses for LLMs and agents, and experiment-tracking or artifact management systems such as MLflow or Weights & Biases.
- Experience taking an internal platform to an external product: multi-tenancy, SDKs, versioned APIs, and documentation.
- Experience deploying AI systems on-prem or in regulated domains such as defense or aerospace.

## Experience Level

Typically 8+ years of software engineering experience, including 4+ years building and operating ML/AI or LLM systems in production, with demonstrated Staff-level scope and impact.

## Benefits

- Pay depends on experience, but we strive to be at the upper end of the salary range
- Health care plan with 100% premium coverage, including medical, dental, and vision
- 401k with 5% matching
- Paid Time Off (uncapped vacation, plus sick and public holidays)
- Flexible hybrid or remote work arrangement
- Relocation assistance for qualifying employees

Wage Transparency - The salary range for this role is not a guarantee of compensation or salary, as the final offer amount may vary based on factors including, but not limited to, individual proficiency, skills, experience, and location.

We are an equal opportunity employer. US Citizenship may be required for certain project assignments involving security clearance.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

## About Code Metal

## Company Overview
- **One-liner**: Code Metal provides an AI-powered platform for verifiable code translation, enabling mission-critical industries to safely move software to different hardware architectures and languages with formal verification.
- **Entity Type**: Private (Series B)
- **Headquarters**: Boston, Massachusetts, United States
- **Founded**: 2023
- **Founders**: Not publicly disclosed

## Core Business
- **Primary industry/industries**: Software development tools; defense, automotive, aerospace, robotics, logistics
- **Target customers**: B2B enterprise – engineering teams in safety-critical sectors (defense, automotive, aerospace, medical devices)
- **Mission or purpose statement**: "Make AI trustworthy by safely delivering the last mile for mission critical industries" ([codemetal.ai](https://codemetal.ai/))

## Products & Services
- **Verifiable Code Translation Platform**: An AI-driven tool that automatically translates source code to a target architecture/language while generating a full test suite (functional and MCDC coverage) and formally verifying functional equivalence. Designed for safety-critical and compliance-heavy environments.

## Market Standing
- **Valuation**: Not disclosed directly; latest round implies a post-money valuation in the hundreds of millions (conflicting reports).
- **Key Metric – Total Funding**: Conflicting data – $178.45M or $184.45M (see sources). Latest round was a $125M Series B in February 2026, led by **Salesforce Ventures**. ([cbinsights.com](https://www.cbinsights.com/company/code-metal) and [pitchbook.com](https://pitchbook.com/profiles/company/548367-58))
- **Notable Investors/Partners**: J2 Ventures, Shield Capital, Overmatch Ventures, Smith Point Capital, RTX Ventures, Salesforce Ventures (lead Series B), and 20+ others.
- **Growth Signals**: 
  - Headcount of 63 (as of mid-2026), growing 182.8% YoY.
  - Active job postings: 57, up 714% YoY. 
  - Customers include a top‑5 global automotive OEM, a top aerospace company, and L3Harris.
  - Patents filed for code translation and program synthesis using LLMs.

## Competitive Advantages
- **Formal verification + AI**: Unlike typical AI code assistants, Code Metal guarantees functional equivalence through automated testing and compliance checks, making it suitable for systems where failure is not an option.
- **Chip portability**: Allows customers to avoid vendor lock-in by maintaining a single source-of-truth codebase deployable to any chip (ARM, RISC‑V, GPUs, etc.).
- **Track record in defense/aerospace**: Already deployed with L3Harris and major aerospace/automotive firms, providing a strong reference base.

## Strategic Focus
- **Go‑to‑market**: Deepening relationships with defense primes and automotive OEMs while expanding into robotics, telecommunications, and medical devices.
- **Product development**: Investing in compiler and AI tooling, modeling & simulation, formal methods, and GPU/accelerator support (evident from open positions).
- **Scaling team**: Aggressively hiring across engineering, research, and go‑to‑market roles (Boston, San Francisco, remote).

## Why Work Here
- **Culture & impact**: "Building a global team of exceptional builders" – focus on solving hard problems at the intersection of AI, compilers, and safety-critical systems.
- **Work policy**: Offers roles in Boston, San Francisco, and fully remote (US). Many engineering/research positions list "Boston, Remote, San Francisco".
- **Notable perks/engineering culture**: Exposure to cutting-edge AI and formal methods; opportunity to work with top defense contractors; high autonomy and a flat structure (only 63 employees).
- **Growth trajectory**: 182.8% headcount growth and fundraising momentum signal rapid scaling and career advancement potential.

## Sources
1. [codemetal.ai – Homepage](https://codemetal.ai/)
2. [codemetal.ai – Careers](https://www.codemetal.ai/careers)
3. [CBInsights – Company Profile & Financials](https://www.cbinsights.com/company/code-metal)
4. [LinkedIn – Company Page](https://www.linkedin.com/company/code-metal)
5. [PitchBook – Valuation & Funding](https://pitchbook.com/profiles/company/548367-58)

## Other roles at Code Metal

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- [Senior AI Platform Engineer](https://feeny.ai/job/senior-ai-platform-engineer-code-metal-boston-v5jz647ej1yn) — Boston, MA
- [Proposal Coordinator](https://feeny.ai/job/proposal-coordinator-code-metal-remote-hcvtev4wg0ts)
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