{"id":3530433,"url":"https://alion.io/job/adaptiq-principal-ai-platform-engineer","title":"Principal AI Platform Engineer","company":{"id":4485822,"name":"Adaptiq","domain":"adaptiq.co","url":"https://alion.io/company/adaptiq","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Ukraine"],"countries":["UA"],"hiring_countries":["UA"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":36000,"max_usd":89000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1286},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Linux","optional":false},{"name":"LLM","optional":false},{"name":"Python","optional":false},{"name":"vLLM","optional":false}],"status":"live","first_seen_at":"2026-10-30T15:07:12Z","employer_posted_date":null,"last_verified_at":"2026-10-30T15:07:12Z","board_verified":false,"closed_at":null,"days_open":3,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":3},"description":"🌍 Who we are:\n\nAdaptiq is a technology hub specializing in building, scaling, and supporting R&D teams for high-end, fast-growing product companies in a wide range of industries.\n\n🧩 About the Product:\n\nOur client develops software that helps engineering teams deploy and manage AI workloads in production. The platform simplifies infrastructure operations and supports reliable, scalable services across different deployment environments.\n\n🌟 About the Role:\n\nWe are looking for a Senior Software Engineer to develop platform capabilities supporting AI model deployment and operation.\n\nYou will combine Python development with hands-on infrastructure engineering, improving the tools and services that help teams bring AI workloads into production. Your work will include performance optimization, automation, and operational reliability.\n\nYou will collaborate with other engineers, contribute to technical decisions, and take ownership of your work from design through deployment and ongoing support. The role includes participation in an on-call rotation.\n\n📈 Key Responsibilities:\n\nDevelop Python services and tools supporting AI workloads.\n\nDeploy, operate, and scale LLM inference services to meet the needs of active users and production traffic.\n\nConfigure and optimize model execution across multiple GPUs and compute nodes.\n\nBuild and improve automated deployment and configuration workflows.\n\nIntegrate and configure model-serving technologies.\n\nAnalyze system performance and improve scalability, resource efficiency, and reliability.\n\nDesign tests to evaluate production readiness and identify performance bottlenecks.\n\nImprove monitoring, diagnostics, and recovery processes.\n\nInvestigate production issues across software and infrastructure components.\n\nContribute to architecture discussions, code reviews, and technical documentation.\n\nCollaborate with engineering teams to translate requirements into maintainable solutions.\n\n💻 Required Competence and Skills:\n\nStrong Python development skills and experience building maintainable production software.\n\nHands-on experience operating LLM inference services in production, supporting active users and real-world traffic.\n\nPractical experience deploying and serving models across multi-GPU configurations and multi-node environments.\n\nExperience configuring and tuning an LLM-serving framework, such as vLLM or a comparable technology.\n\nPractical understanding of GPU memory constraints and how they affect model deployment and execution.\n\nExperience evaluating performance under load and interpreting latency, throughput, and resource usage.\n\nFamiliarity with techniques for reducing model memory requirements and improving inference efficiency.\n\nExperience with infrastructure automation and infrastructure-as-code tools.\n\nStrong Linux troubleshooting skills.\n\nExperience supporting production services, including monitoring and incident resolution.\n\nAbility to work independently, assess technical trade-offs, and communicate decisions clearly.\n\nClear written and spoken English.\n\n➕ Nice to Have:\n\nExperience with distributed systems or large-scale compute environments.\n\nFamiliarity with multiple model-serving technologies.\n\nExperience with container orchestration and cloud infrastructure.\n\nUnderstanding of networking and its impact on application performance.\n\nExperience building tools for resource management, deployment, or operational automation.\n\nBackground in AI platforms, developer tools, or infrastructure software.\n\n🚀 Why Us:\n\n- We provide 20 days of vacation leave per calendar year (plus official national holidays of a country you are based in).\n\n- We provide full accounting and legal support in all countries we operate.\n\n- We utilize a fully remote work model with a powerful workstation and co-working space in case you need 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