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Reflection AI

Builds AI models and deployment software

Forward Deployed Engineer - Public Sector

Applied Machine LearningConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • Experience delivering software into classified or air-gapped government environments, including familiarity with security controls, accreditation processes, and constraints on offline deployment.
  • Strong technical fluency in reading, writing, and reasoning about code, architecture, and system behavior; strong Python skills and experience shipping production-grade systems.
  • A track record of leading complex technical projects, coordinating contributors across workstreams, making practical tradeoffs, removing obstacles, and owning end-to-end delivery outcomes.
  • Hands-on infrastructure and inference experience, including deploying multi-node GPU clusters using Kubernetes or Slurm, serving large models in production using vLLM or SGLang, and benchmarking quantization, caching, batching, and speculative decoding.
  • Experience shipping LLM-based agents to production within the last 1–2 years, designing agent harnesses involving tool calling and MCP, context management, orchestration, and guardrails, developing evaluations, and understanding when post-training can be used.
  • At least 5 years of relevant experience delivering technical systems, including at least 2 years in a technical leadership role such as tech lead, engineering manager, or founding engineer.
  • Demonstrated ability and interest in customer-facing work, understanding user needs, architecting solutions for business problems, and delivering outcomes; able to move from a whiteboard session to debugging a deployment in the customer’s environment.
  • Ability to work as a self-starter with ownership in a fast-paced startup environment.

Responsibilities

  • Own technical execution of strategic customer engagements end to end, from discovery and solution architecture through proof of concept and production delivery.
  • Deploy and operate agentic systems in air-gapped and classified networks, including fully offline model serving without external services.
  • Work on-site with government customers, including in SCIFs, translating mission requirements into secure AI solutions that meet accreditation and compliance standards.
  • Lead technical discovery with customer teams across inference workloads, agentic applications, and post-training; translate customer needs into feasible technical solutions with clear success criteria.
  • Own proofs of concept end to end by defining evaluation criteria with customers, benchmarking on real workloads, and demonstrating Reflection’s quality, latency, and cost against competing options.
  • Architect and build complex AI systems, including agentic applications, model-serving infrastructure, evaluations, and post-training recipes.
  • Own customer engagements and relationships by defining project plans, sequencing and managing work across workstreams, and aligning customer stakeholders.
  • Identify repeatable field patterns and model gaps to inform platform and model capabilities; build prototypes, validate them against customer needs, and generalize them into platform and research priorities.
  • Help scale the deployment organization by defining playbooks, reference architectures, reusable technical assets, and best practices.

About the Company

Reflection AI

Builds AI models and deployment software

Reflection AI develops language models for software developers, companies and governments that want control over how AI is deployed and adapted. Its research concentrates on coding, reasoning and AI agents that work through tasks with software tools. The lab builds the surrounding software and infrastructure as well as models, letting customers run AI through its hosted platform or in their own computing environments. Its commercial work pairs model access with engineers who design applications and support customized enterprise deployments from development through operation. Reflection AI was founded in 2024 and is headquartered in New York City.

Company size
201-500
Company stage
Late Stage VC
Total funding
$4.6B
Headquarters
New York City, New York
Founded
2024

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