{"id":3629610,"url":"https://alion.io/job/wti-labs-senior-ai-platform-engineer","title":"Senior AI Platform Engineer","company":{"id":4495847,"name":"WTI Labs","domain":"wti-labs.com","url":"https://alion.io/company/wti-labs","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","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":["São Paulo, Brazil"],"countries":["BR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude Code","optional":false},{"name":"Cursor","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"Linux","optional":false},{"name":"LLM","optional":false},{"name":"Lovable","optional":false},{"name":"Node JS","optional":false},{"name":"PostgreSQL","optional":false},{"name":"React.js","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"TypeScript","optional":false},{"name":"vLLM","optional":false},{"name":"JavaScript","optional":true},{"name":"Kubernetes","optional":true},{"name":"OCR","optional":true},{"name":"pgvector","optional":true},{"name":"Quantization","optional":true},{"name":"RAG","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-09-28T00:00:00Z","employer_posted_date":"2026-09-28","last_verified_at":"2026-11-10T00:10:10Z","board_verified":true,"closed_at":null,"days_open":43,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":43},"description":"You'll turn AI-built prototypes into secure production systems that run on enterprise data. That means hardening Node, React, and Postgres applications, connecting them to Databricks and Snowflake, and running open-weight LLMs on dedicated GPUs. Sensitive data gets processed at scale without leaving a controlled environment or touching a public model API.\nThis is a hands-on senior role with real ownership. You'll set the technical standards for how our applications reach production, working directly with the Senior Leadership Team and the data teams you integrate with.\nWhat you'll do\nTake apps built quickly with AI coding tools (Cursor, Claude Code, Lovable, and similar) and make them production-ready: architecture, authentication, testing, observability, and CI/CD.\nConnect Node, React, and Postgres applications securely to Databricks and Snowflake, working within their governance and access controls.\nDesign APIs and pipelines that move data between Postgres and Databricks or Snowflake, reliably and with a full audit trail.\nDeploy and operate open-weight LLMs on dedicated GPU servers using vLLM or a similar inference engine.\nBuild batch and real-time pipelines that run LLM extraction, classification, and summarization over large datasets.\nKeep sensitive data inside controlled environments through network isolation, encryption, secrets management, and audit logging. Nothing goes to a public model API.\nMonitor GPU utilization, throughput, latency, and cost, and right-size infrastructure as workloads grow.\nSet the standards for how AI-built prototypes reach production, and document the architecture so others can build on it.\nRequirements\nEvery item below is required.\n6+ years of professional software engineering, including senior-level ownership of production systems.\nStrong Node.js backend experience (TypeScript preferred): APIs, services, and authentication.\nStrong React experience building production front ends.\nDeep PostgreSQL experience: schema design, query tuning, and migrations.\nHands-on production experience with Databricks (for example Unity Catalog, Delta Lake, Databricks SQL).\nHands-on production experience with Snowflake (for example Snowpark, secure views, role-based access control).\nExperience deploying and serving LLMs on GPU infrastructure, including throughput and memory tuning.\nSolid security fundamentals for sensitive data: access control, encryption, network isolation, and secrets management.\nLinux, Docker, and at least one major cloud (AWS, Azure, or GCP).\nComfort reviewing and refactoring AI-generated code, and using AI coding tools yourself.\nProfessional English, written and spoken, for daily work with a US-based team.\nNice to have\nKubernetes, including GPU workloads\nInfrastructure as code (Terraform or similar)\nRetrieval-augmented generation (RAG) and vector search, such as pgvector, Databricks Vector Search, or Snowflake Cortex Search\nDatabricks Mosaic AI Model Serving, Snowflake Cortex, or Snowpark Container Services\nModel quantization and inference optimization\nLarge-scale document processing: OCR, entity extraction, and classification\nWork in regulated or data-sensitive industries such as finance, healthcare, energy, or government\nDatabricks or Snowflake (SnowPro) certifications\nBenefits\nWork From Home\nGenerous Salary Commensurate with Experience\nFlexible Working 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