{"id":1303333,"url":"https://alion.io/job/neuromorphic-labs-founding-forward-deployed-ai-engineer","title":"Founding Forward Deployed AI Engineer","company":{"id":3797543,"name":"Neuromorphic Labs","domain":"neuromorphiclabs.ai","url":"https://alion.io/company/neuromorphiclabs","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Seattle, United States","Bellevue, United States","San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":151000,"max_usd":285000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":817},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AIOps","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-08-11T01:00:56Z","employer_posted_date":"2026-08-11","last_verified_at":"2026-09-29T19:00:16Z","board_verified":true,"closed_at":null,"days_open":50,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":50},"description":"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.\nThis 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.\nWhat We're Building\nOur mission is to enable every organization to own its AI future.\nAs 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.\nWe 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.\nWhy This Role is Different\nYou 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.\nThe 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.\nYou 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.\nThe 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.\nWhat You'll Do\nYou 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.\nBuild and operate AI, MLOps, and deployment pipelines across internal development as well as customer environments.\n\nLead technical integrations with enterprises, AI labs, and startups.\n\nBuild proof-of-concepts, prototypes, demos, and reference implementations.\n\nDebug complex deployment and integration issues across cloud, on-prem, and hybrid environments.\n\nWork directly with customers to understand technical requirements and turn them into working solutions.\n\nTranslate recurring customer needs into clear feedback for Product and Engineering.\n\nIdentify customer-specific work that should become reusable platform capabilities.\n\nCreate technical content including integration guides, reference architectures, demos, tutorials, and blogs.\n\nPartner with Sales, Business Development, and Product on technical discovery, evaluations, and customer engagements.\n\nHelp define the processes, tooling, and technical standards for forward deployed engineering as the team grows.\n\nWhat We're Looking For\nWe are looking for a deeply technical, customer-oriented engineer who enjoys building in ambiguous environments and solving real-world AI infrastructure problems.\n5+ years of hands-on engineering experience building and deploying production systems.\n\nStrong experience with AI/ML infrastructure, MLOps, model deployment, or AI application pipelines.\n\nExperience integrating complex software into customer or partner environments.\n\nStrong cloud-native fundamentals across containers, Kubernetes, APIs, infrastructure-as-code, and distributed systems.\n\nProficiency in Python and at least one systems or backend language.\n\nStrong debugging skills across application, infrastructure, networking, and deployment layers.\n\nComfortable building prototypes, demos, scripts, and integration code quickly.\n\nStrong customer-facing communication and the ability to work credibly with engineers, architects, and technical leaders.\n\nAbility to translate customer problems into actionable product and engineering requirements.\n\nStrong technical writing skills and the ability to create compelling customer-facing content.\n\nHigh ownership and bias for action in 0-to-1 environments.\n\nStrong Pluses\nExperience as a Forward Deployed Engineer, Solutions Engineer, Customer Engineer, or similar technically hands-on customer-facing role.\n\nExperience with LLM training, inference, model serving, evaluation, or agentic application stacks.\n\nExperience deploying across multi-cloud, on-prem, air-gapped, or hybrid environments.\n\nFamiliarity with security domains such as identity, access control, secrets management, key management, or trusted computing.\n\nExperience working directly with design partners or early customers to shape a technical product.\n\nExperience creating reference architectures, technical blogs, tutorials, workshops, or developer-facing content.\n\nPrior startup or early-stage experience, or a big-company background and strong conviction that it is time for something different.\n\nWhat We Offer\nFounding-team equity with meaningful upside.\n\nCompetitive cash compensation, calibrated for seed stage.\n\nA direct hand in defining the product, the architecture, and the culture.\n\nOpportunity 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.\n\nA founder committed to your growth, and a front-row seat to building a 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