# Senior AI Platform Engineer

**Company:** [wti-labs](https://jobs.workable.com/companies/nhDXvYLJoVrGmbWmbjkZCJ.md)
**Location:** Remote
**Workplace:** remote
**Employment type:** Full-time

[Apply for this job](https://jobs.workable.com/view/0284a8ef-8649-49c9-9f34-5131d86b7ee6)

## 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.

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.

### What you'll do

-   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.

## Requirements

### Every item below is required.

-   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.

### Nice to have

-   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

## Benefits

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