{"id":3451405,"url":"https://alion.io/job/neural-concept-platform-deployment-engineer-west-coast","title":"Platform Deployment Engineer - West Coast","company":{"id":7278,"name":"Neural Concept","domain":"neuralconcept.com","url":"https://alion.io/company/neural-concept","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":95,"open_postings":36,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":76,"computed_at":"2026-10-29T05:49:05Z"}},"role":"DevOps","role_family":"DevOps","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":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":200000,"max":250000,"currency":"USD","period":"year","gross":null,"usd_annual":250000},"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"DNS","optional":false},{"name":"GitOps","optional":false},{"name":"Grafana","optional":false},{"name":"HPC","optional":false},{"name":"ISO 27001","optional":false},{"name":"Kubernetes","optional":false},{"name":"Linux","optional":false},{"name":"LLM","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-10-29T09:16:59Z","employer_posted_date":"2026-10-29","last_verified_at":"2026-10-29T20:28:55Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Neural Concept embeds AI into design and simulation workflows so engineering teams make continuous, data-driven decisions instead of waiting on sequential design-simulation-validation cycles. None of that matters until the platform is running inside the customer's environment, on their infrastructure, under their rules.\nThat is this role. You take an enterprise customer and make the platform real for them: architected, deployed, integrated, cleared by their security organisation, and stable enough that their engineers stop thinking about it. You own that outcome end to end for named accounts, as their primary technical counterpart.\nWhat you will do\nThe deployment, from the first architecture conversation through go-live and into steady-state operation.\n\nIts integration with the customer's identity, data and engineering systems, and the infrastructure and model serving layer beneath it.\n\nThe relationship with their IT, security and platform teams: assessments, architecture reviews, and the call when something breaks.\n\nThe diagnosis when it does break, including when the cause sits outside our own software.\n\nThe runbooks, post-mortems and playbooks that make the next deployment easier, and the feedback loop into Product.\n\nWhere you will do it\nManaged Kubernetes across the major clouds. On-premises and fully air-gapped clusters with no route to the internet, GPU infrastructure, self-hosted model serving. Customer HPC environments, schedulers, and shared storage under real load.\nIf installing software with no internet access, on hardware you do not control, reads as the interesting part of the job rather than the obstacle, this will suit you.\nWho you are\nYou will often be the only Neural Concept engineer in the room. We are looking for someone with:\n6+ years deploying and operating enterprise software in production, two of them in environments you did not control.\n\nKubernetes at configuration depth: how chart values become rendered manifests, and why a workload will not start.\n\nIdentity and SSO fundamentals: OIDC and SAML, clients and credential rotation, redirect URIs, group-to-role mapping.\n\nLinux, networking and TLS: DNS, routing, ingress and egress, certificate chains and interception proxies.\n\nKubernetes storage: persistent volumes and CSI, access modes, diagnosing shared storage that degrades under load.\n\nA production deployment you personally carried and then supported. Name it, date it, tell us what went wrong.\n\nProfessional customer-facing English, and willingness to travel and work your customers' hours.\n\nAlso valuable: regulated or air-gapped deployments · private registries and image mirroring · GPU scheduling and LLM serving · enterprise IdP administration · Terraform and GitOps · Prometheus and Grafana · HPC schedulers · ISO 27001 evidence · Python · PLM, CAD or CAE exposure.\nYou Get\nWork with a world-class technology team - our engineers are top-notch, and we always aim for excellence.\n\nBenefit from a competitive salary and rewarding opportunities as we continue to scale.\n\nThrive in a collaborative, multicultural environment where your work is visible and recognized.\n\nDevelop professionally alongside talented colleagues who share knowledge freely and support one another.\n\nMake a global impact by helping customers shift to AI-assisted design, making innovation faster, smarter, and more sustainable.\n\nBalance life and work with remote work or hybrid model (20% remote) -we care about results, not rigid schedules.\n\nEnjoy paid vacations, healthcare (medical/vision/dental), 401K matching\n\nWhere You Will Be\nSan Mateo, California;\n\nTravelling: This position will require travelling to customer locations in the US.\n\nStart date: ASAP\n\nEligibility: ITAR clearance required\n\nWe're proud to be an equal opportunity employer, and we're committed to building a diverse and inclusive environment where you can thrive.","description_format":"text","description_chars":3878,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":true,"languages":[]},"benefits":["401k plan"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Machine Learning","Simulation & Digital Twin Software","Industrial 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