# Staff Software Engineer

**Company:** [OpenLoop](https://hotfix.jobs/companies/openloop)
**Location:** Remote
**Role:** ML Engineering
**Experience:** 8+ years
**Skills:** Go, Python, TypeScript, LLMs, GCP, Kubernetes, Docker, langfuse, BigQuery, Pub/Sub, RAG, FHIR, vLLM, ollama
**Posted:** 2026-07-30

> Technical Lead owning architecture, execution, and evolution of an AI-driven telehealth platform built on GCP. Hands-on player-coach role integrating production LLMs, leading a small senior team, and driving scalable distributed systems in a healthcare setting.

## Job Description

## Responsibilities
- Own System Architecture: Design and evolve distributed systems on GCP (Cloud Run, Pub/Sub, BigQuery), making final decisions on service boundaries, data models, and technology trade-offs across Go, Python, and TypeScript.
- AI & LLM Strategy: Lead hands-on integration of AI systems, including open-source LLMs, embeddings, and speech models. Define prompt optimization, evaluation strategies, and safety practices using tools like LangFuse.
- Operational Excellence: Champion observability, reliability, and scale. Oversee event-driven ingestion and automated QA pipelines for call transcripts and healthcare data (FHIR / Medplum).
- Delivery & Execution: Contribute code to critical paths while leading major technical initiatives. Identify gaps, unblock teams, and drive projects to completion.
- Cross-Functional Leadership: Translate complex technical constraints into clear options and trade-offs for Product, Design, and Clinical Operations.

## Requirements
- 8+ years of software engineering experience, with 2+ years leading projects or serving as a Tech Lead.
- Staff-level scope or equivalent technical impact.
- Strong LLM experience in production environments (hands-on required).
- Expert-level proficiency in Go, Python, or TypeScript/Node, with the ability to review code across the stack.
- Deep experience with distributed systems, containerized deployments (Docker, Kubernetes, Cloud Run), and event-driven architectures.

## Nice-to-Haves
- ML background, especially applied machine learning or AI infrastructure.
- Experience hosting or integrating open-source models (e.g., vLLM, Ollama), with a strong understanding of RAG architectures.
- Background in regulated environments (HIPAA, SOC 2) or healthcare data standards (FHIR, HL7).
- Strong written and verbal communication skills, including writing RFCs and explaining technical strategy to non-technical stakeholders.

## Compensation and Benefits
- Competitive compensation, equity, and real perks.
- Medical, Dental, and Vision plans.
- Flexible Spending/Health Savings Accounts.
- Flexible PTO.
- 401(k) + Company Match.
- Life Insurance, Pet insurance, and more.

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