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Salary
≈ $153k – $279k per year (Estimated)
Location
Hybrid (Seattle, Bellevue, San Francisco, United States)
Seniority
Senior · 5+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Sep 28, 2026. First seen by Alion on Aug 11, 2026.

Overview
Company
Impact
Profile match
Neuromorphic Labs helps teams build, own, and deploy production AI with verifiable trust across models, data, agents, and compute.

Neuromorphic Labs is a Seed stage AI Startup, backed by top-tier VCs. We are looking for a Founding Forward Deployed AI Engineer to help customers integrate our platform into their production AI environments, from initial proof-of-concept through deployment and support.

This is not a conventional solutions engineering or AIOps role. You will be deeply hands-on, building integrations, standing up AI and MLOps pipelines, creating prototypes and demos, debugging customer environments, and turning what you learn in the field into product improvements. You will sit at the intersection of customers, Product, Engineering, and GTM, helping us turn early deployments into a platform that scales.

What We're Building

Our mission is to enable every organization to own its AI future.

As intelligence becomes something companies build, own, and continuously improve, models, data, agents, and AI systems are becoming a new strategic moat. But production AI is still too fragmented, complex, and difficult to trust.

We are building the trust layer for production AI, a foundational platform that makes security, governance, and control intrinsic to every model, artifact, and deployment, so organizations can move faster and scale AI with confidence.

Why This Role is Different

You are not just demonstrating the product. You are making it work in the real world. As a Founding Forward Deployed AI Engineer, you will work directly with customers to integrate our platform into their AI stacks, build proof-of-concepts, solve deployment challenges, and identify the capabilities that should become part of the core product. You will move fluidly between writing code, debugging infrastructure, working with customers, and shaping product direction.

The equity is real. The pace of progress in AI has created a once-in-a-lifetime window, and where you spend the next few years matters more than it ever has. You can spend them supporting someone else’s mature platform, or you can help define how a new AI infrastructure company gets deployed in the world and have meaningful ownership in what you build.

You will work directly with a founder who has done this at scale. Our CEO has nearly two decades of experience building and scaling AI infrastructure businesses. He scaled a business from about $100M into a multi-billion-dollar segment at a leading cloud provider, and served as Chief Product Officer of a company he helped take public, now valued at over $50B. He leads by example, stays hands-on, and invests heavily in developing people and helping them do the best work of their careers.

The timing is now. AI is rapidly moving into production, and the infrastructure patterns underneath it are still being defined. The companies that win will be the ones that work in real customer environments, learn faster than everyone else, and turn those lessons into product.

What You'll Do

You will own the technical path from customer interest to a working deployment, helping customers integrate our platform while turning field learnings into reusable product capabilities.

  • Build and operate AI, MLOps, and deployment pipelines across internal development as well as customer environments.

  • Lead technical integrations with enterprises, AI labs, and startups.

  • Build proof-of-concepts, prototypes, demos, and reference implementations.

  • Debug complex deployment and integration issues across cloud, on-prem, and hybrid environments.

  • Work directly with customers to understand technical requirements and turn them into working solutions.

  • Translate recurring customer needs into clear feedback for Product and Engineering.

  • Identify customer-specific work that should become reusable platform capabilities.

  • Create technical content including integration guides, reference architectures, demos, tutorials, and blogs.

  • Partner with Sales, Business Development, and Product on technical discovery, evaluations, and customer engagements.

  • Help define the processes, tooling, and technical standards for forward deployed engineering as the team grows.

What We're Looking For

We are looking for a deeply technical, customer-oriented engineer who enjoys building in ambiguous environments and solving real-world AI infrastructure problems.

  • 5+ years of hands-on engineering experience building and deploying production systems.

  • Strong experience with AI/ML infrastructure, MLOps, model deployment, or AI application pipelines.

  • Experience integrating complex software into customer or partner environments.

  • Strong cloud-native fundamentals across containers, Kubernetes, APIs, infrastructure-as-code, and distributed systems.

  • Proficiency in Python and at least one systems or backend language.

  • Strong debugging skills across application, infrastructure, networking, and deployment layers.

  • Comfortable building prototypes, demos, scripts, and integration code quickly.

  • Strong customer-facing communication and the ability to work credibly with engineers, architects, and technical leaders.

  • Ability to translate customer problems into actionable product and engineering requirements.

  • Strong technical writing skills and the ability to create compelling customer-facing content.

  • High ownership and bias for action in 0-to-1 environments.

Strong Pluses

  • Experience as a Forward Deployed Engineer, Solutions Engineer, Customer Engineer, or similar technically hands-on customer-facing role.

  • Experience with LLM training, inference, model serving, evaluation, or agentic application stacks.

  • Experience deploying across multi-cloud, on-prem, air-gapped, or hybrid environments.

  • Familiarity with security domains such as identity, access control, secrets management, key management, or trusted computing.

  • Experience working directly with design partners or early customers to shape a technical product.

  • Experience creating reference architectures, technical blogs, tutorials, workshops, or developer-facing content.

  • Prior startup or early-stage experience, or a big-company background and strong conviction that it is time for something different.

What We Offer

  • Founding-team equity with meaningful upside.

  • Competitive cash compensation, calibrated for seed stage.

  • A direct hand in defining the product, the architecture, and the culture.

  • Opportunity to be part of a fast-paced environment that values distinctive expertise, emphasizes ownership along with high standards, and fosters open-minded collaboration with exceptional builders.

  • A founder committed to your growth, and a front-row seat to building a company.

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