Staff Software Engineer (Tech Lead)

OpenLoop Health

2d•Hybrid

About The Position

OpenLoop is seeking a Technical Lead to take ownership of the architecture, execution, and evolution of their AI-driven platform. This senior, hands-on leadership role is for an individual experienced in building production-scale AI systems with LLMs. The role involves acting as a player-coach, contributing production code, defining technical direction, and guiding a small, senior engineering team. Responsibilities include designing and evolving distributed systems on GCP, leading the integration of AI systems (LLMs, embeddings, speech models), championing operational excellence (observability, reliability, scale), driving delivery and execution of critical technical initiatives, and facilitating cross-functional communication with 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).
ML background preferred, especially applied machine learning or AI infrastructure.
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

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.

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.