Neuromorphic Labs Logo

Neuromorphic Labs

Founding Forward Deployed AI Engineer

Posted Yesterday
Remote or Hybrid
2 Locations
Senior level
Remote or Hybrid
2 Locations
Senior level
Build and operate AI, MLOps, and deployment pipelines across customer and internal environments. Lead technical integrations, prototypes, demos, and production deployments across cloud, on-premises, and hybrid systems. Debug complex infrastructure and application issues, gather customer requirements, translate field insights into product capabilities, and create technical content. Partner with customers, Product, Engineering, Sales, and Business Development while helping establish forward-deployed engineering standards.
The summary above was generated by AI

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.

Similar Jobs

26 Minutes Ago
In-Office or Remote
Mid level
Mid level
Information Technology • Software • Travel
Build and maintain a mature SaaS platform across Rails backend, JSON APIs, MySQL, and Vue.js frontend. Develop travel features, partner integrations, AI-powered functionality, and document generation; optimize performance, write automated tests, upgrade dependencies, address security issues, investigate production incidents, review code, and document work. The role requires autonomous feature ownership, careful work in a large codebase, and collaboration through Git and pull requests.
Top Skills: Amazon CloudfrontAmazon S3Aws EcsAws LambdaCapybaraDockerFactorybotGitGithub ActionsJavaScriptJson ApisMySQLRspecRubyRuby On RailsSentryVueVuetify
2 Hours Ago
Remote
2 Locations
147K-160K Annually
Entry level
147K-160K Annually
Entry level
Artificial Intelligence • Consumer Web • Digital Media • Information Technology • Social Impact • Software
Own growth for Circle’s Discover marketplace by driving traffic, GMV, and transaction volume. Lead experimentation, lifecycle email, subscriber acquisition, SEO/AEO, creator success, funnel reporting, and retention initiatives. Partner with product, paid media, data, brand, partnerships, the GM, and co-founders to shape and execute marketplace growth strategy in a hands-on player-coach role.
2 Hours Ago
Remote
Entry level
Entry level
Events • Food • Travel • Hospitality • Hotels & Resorts
Prépare, monte, démonte et entretient les salles de banquet avant, pendant et après les événements. Collabore avec l’équipe des banquets pour répondre aux standards de l’hôtel et aux besoins des clients. Le poste exige de la flexibilité pour travailler de jour, de soir, de nuit et les fins de semaine, ainsi que la capacité de soulever jusqu’à 50 lb et de communiquer en français et en anglais.

What you need to know about the Seattle Tech Scene

Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.

Key Facts About Seattle Tech

  • Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Amazon, Microsoft, Meta, Google
  • Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
  • Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Madrona, Fuse, Tola, Maveron
  • Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account