Senior AI Platform Engineer

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.

This 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.

• Take 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.
• Connect Node, React, and Postgres applications securely to Databricks and Snowflake, working within their governance and access controls.
• Design APIs and pipelines that move data between Postgres and Databricks or Snowflake, reliably and with a full audit trail.
• Deploy and operate open-weight LLMs on dedicated GPU servers using vLLM or a similar inference engine.
• Build batch and real-time pipelines that run LLM extraction, classification, and summarization over large datasets.
• Keep sensitive data inside controlled environments through network isolation, encryption, secrets management, and audit logging. Nothing goes to a public model API.
• Monitor GPU utilization, throughput, latency, and cost, and right-size infrastructure as workloads grow.
• Set the standards for how AI-built prototypes reach production, and document the architecture so others can build on it.

• 6+ years of professional software engineering, including senior-level ownership of production systems.
• Strong Node.js backend experience (TypeScript preferred): APIs, services, and authentication.
• Strong React experience building production front ends.
• Deep PostgreSQL experience: schema design, query tuning, and migrations.
• Hands-on production experience with Databricks (for example Unity Catalog, Delta Lake, Databricks SQL).
• Hands-on production experience with Snowflake (for example Snowpark, secure views, role-based access control).
• Experience deploying and serving LLMs on GPU infrastructure, including throughput and memory tuning.
• Solid security fundamentals for sensitive data: access control, encryption, network isolation, and secrets management.
• Linux, Docker, and at least one major cloud (AWS, Azure, or GCP).
• Comfort reviewing and refactoring AI-generated code, and using AI coding tools yourself.
• Professional English, written and spoken, for daily work with a US-based team.

• Kubernetes, including GPU workloads
• Infrastructure as code (Terraform or similar)
• Retrieval-augmented generation (RAG) and vector search, such as pgvector, Databricks Vector Search, or Snowflake Cortex Search
• Databricks Mosaic AI Model Serving, Snowflake Cortex, or Snowpark Container Services
• Model quantization and inference optimization
• Large-scale document processing: OCR, entity extraction, and classification
• Work in regulated or data-sensitive industries such as finance, healthcare, energy, or government
• Databricks or Snowflake (SnowPro) certifications

• Work From Home
• Generous Salary Commensurate with Experience
• Flexible Working Environment