{"id":1597575,"url":"https://alion.io/job/svitla-systems-senior-aidevops-engineer","title":"Senior AI/DevOps Engineer","company":{"id":2216,"name":"Svitla Systems","domain":"svitla.com","url":"https://alion.io/company/svitla-systems","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"B","score":81,"open_postings":8,"ghost_share":0,"stale_share":0.75,"repost_share":0,"time_to_fill_p50_days":44,"computed_at":"2026-10-23T05:54:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Argentina"],"countries":["AR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":49000,"max_usd":126000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2216},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anthropic","optional":false},{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"Bicep","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Grafana","optional":false},{"name":"IAM","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"OpenAI","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Terraform","optional":false},{"name":"Clean Architecture","optional":true},{"name":"FastAPI","optional":true},{"name":"Hibernate","optional":true},{"name":"Pandas","optional":true},{"name":"Polars","optional":true},{"name":"Prompt Engineering","optional":true},{"name":"Pydantic","optional":true},{"name":"Spring Boot","optional":true}],"status":"live","first_seen_at":"2026-08-25T08:58:12Z","employer_posted_date":"2026-08-28","last_verified_at":"2026-10-23T12:14:11Z","board_verified":true,"closed_at":null,"days_open":59,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":59},"description":"We're looking for a Senior AI/DevOps Engineer who thrives at the intersection of infrastructure, automation, and applied AI. You'll be the person who makes AI-powered features actually ship, scale, and stay healthy in production - building the pipelines, platforms, and guardrails that let the rest of the team move fast with LLMs and ML models. This is a hybrid role: part platform/DevOps engineer, part MLOps practitioner, part AI integrator.\nThis is a full-time, remote role, with flexibility to work from home. This role works across a globally distributed team spanning India and both US coasts, so comfort with asynchronous collaboration and overlapping across time zones is important. Expect some evening hours to overlap with global teams.\nResponsibility\nDesign and operate the infrastructure that powers our AI features: LLM integrations, RAG pipelines, vector stores, and model-serving endpoints.\nBuild and maintain CI/CD pipelines for both traditional services and AI/ML workloads (model deployment, evaluation, rollback).\nOwn observability and monitoring for AI systems - latency, cost, token usage, output quality drift, and failure modes unique to LLM-based features.\nArchitect and manage cloud infrastructure on Azure (compute, networking, storage, IAM) using infrastructure-as-code.\nContainerize and orchestrate services with Docker and Kubernetes.\nIntegrate with AI APIs and platforms (OpenAI, Anthropic, Azure AI/OpenAI Service, or similar) and build internal tooling to make that integration repeatable across teams.\nImplement guardrails, rate limiting, caching, and cost controls for LLM-powered features.\nCollaborate with product, data, and application engineering teams to translate AI-feature designs into reliable, production-grade systems.\nCoordinate effectively with teammates across India, East Coast, and West Coast time zones.\nMentor other engineers and help set technical direction for AI infrastructure practices.\nRequirements\nBachelor's Degree in CS or Engineering.\n5+ years of professional experience in DevOps, platform engineering, or SRE roles.\nHands-on experience deploying and operating systems in production.\nExpert level in Python, and proficient in Java (specifically targeting backend product engineering context).\nStrong experience with Azure cloud infrastructure and infrastructure-as-code (Terraform, Bicep, ARM, or similar).\nSolid grasp of CI/CD pipeline design and automation (Azure DevOps, GitHub Actions, or similar).\nProficiency with Docker and Kubernetes for containerization and orchestration.\nExperience integrating with AI/LLM APIs (OpenAI, Anthropic, Azure AI, or similar) and understanding of RAG architectures, vector databases, and prompt/response evaluation.\nComfort with monitoring and observability tooling (Prometheus, Grafana, Application Insights, or similar), including metrics specific to AI systems (cost, latency, quality).\nComfortable working independently and owning problems end-to-end.\nStrong written communication and async collaboration skills, given the distributed, multi-time-zone team.\nNice to have\nExpertise in some of the following frameworks: FastAPI, Pydantic.AI, Pydantic 2, Polars, Pandas, Spring Boot, Hibernate, JDBC.\nExperience with LLM evaluation frameworks and prompt engineering.\nSecurity/compliance experience around AI systems (data privacy, PII handling, model access controls).\nBackground in SOLID principles, clean architecture, and TDD.\nExperience in retail, pricing, or data-intensive SaaS products is a 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