Senior AI Platform Engineer

Code Metal

. Design, build, and operate AI enablement platform components including GPU inference serving, model gateways, agent harnesses, context engineering, observability, and AI experimentation management .

Posted 10/9/2026full-timeUnited StatesSenior💰 $170,000 - $210,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and operating AI enablement platforms, with a strong focus on production-grade Python, model serving, and observability. Proficient in debugging and improving service reliability while mentoring and onboarding team members.

Highest-signal resume keywords

Production-Grade PythonModel ServingKubernetesPyTorchAI Experimentation

ATS Keywords

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Hard Skills

API DesignService DesignDistributed SystemsBenchmarkingModel EvaluationExperiment DesignDebuggingCode ReviewClean Code PracticesModular Code Development

Soft Skills

MentoringOnboardingCollaborationCommunication

Tools & Technologies

Hugging FaceCI/CDContainersOrchestration

Industry Keywords

AI EnablementGPU InferenceObservabilityAgent InfrastructureSecurity Clearance

Tech Stack

Tools & technologies

Distributed SystemsKubernetesPythonPyTorch

About the role

Key responsibilities & impact

Design, build, and operate AI enablement platform components including GPU inference serving, model gateways, agent harnesses, context engineering, observability, and AI experimentation management
Deploy, benchmark, and tune elastic production inference for open-weight models
Build agent harnesses, orchestration primitives, and context-engineering services such as memory, retrieval, and data discovery
Instrument the stack end to end with traces and service metrics
Build evaluation harnesses and experiment-tracking and artifact layers
Own one or more platform components end to end, from design document through production operation
Build and operate services in a focus area and contribute across the rest of the stack
Write clean, well-tested, correct, modular, and fully tested code
Debug production issues such as tail latency, GPU memory pressure, and failing or looping agent runs
Scope and estimate efforts with internal customers and raise risks early
Review teammates' code and designs and help onboard new engineers
Run focused benchmarks and experiments when platform decisions need evidence

Requirements

What you’ll need

Production-grade Python and solid platform engineering fundamentals: API and service design, distributed systems, containers and orchestration such as Kubernetes, CI/CD, and testing
Production experience in at least 1 focus area: model serving, agentic infrastructure, or observability and experimentation
Solid data science and AI research fundamentals, including transformers and LLM inference, experiment design, benchmarking, and model evaluation
Working familiarity with PyTorch and Hugging Face
Experience owning a service or component in production, including debugging and improving its reliability
Experience writing design docs for focused projects, reviewing code, and mentoring or onboarding teammates
Typically 4+ years of software engineering experience, including 2+ years building and operating ML/AI or LLM systems in production
U.S. Citizenship may be required for certain project assignments involving security clearance
Must be legally authorized to work in the United States
May require eligibility to obtain and maintain a U.S. security clearance

Benefits

Comp & perks

Offers Equity
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