Senior AI Engineer

Tala Health was built to transform a healthcare system that remains slow, expensive and inefficient. Today’s patients often face a fragmented system that requires juggling doctor visits, lab work, referrals and long wait times just to reach a diagnosis. With Tala Health, patients will receive a new kind of care experience that brings AI agents and clinicians together from the start to deliver accurate, personalized care faster. We are building AI agents to support the full arc of the patient journey.

The Opportunity: Senior AI Engineer

Healthcare is adopting AI at record speed, and we need an engineer who can guide that transition. As a Senior AI Engineer, owning the journey from early-stage AI ideas to scalable, production-grade systems that clinicians can trust and use daily.

Along the way, performance, security, and cost efficiency remain top of mind, and you’ll design for each from the outset. Research insights won’t sit on a shelf—you’ll distill them into clean, maintainable code. Close collaboration with product managers and designers ensures every release addresses real clinical workflows. Ultimately, the standards you set will define the quality bar for our entire AI stack.

What You'll Do

Ship AI agents end-to-end which help ease clinical workflows: integrate existing infrastructure or architect new pipelines when necessary.

Continuously improve product performance through experiments, user research, and usage analytics.

Translate research into scalable systems: pick the right models, design rigorous evaluations, optimize for speed and cost, monitor in production.

Own 0 to 1 breakthroughs: Prototype and launch first-of-their-kind AI features—from fine-tuned LLM workflows to novel clinical documentation tools.

Co-author the roadmap: partner with product & design while retaining ownership of the technical stack and long-term AI architecture.

What You'll Bring

5+ years software engineering, including 2+ years building AI systems (1+ year in generative AI is a big plus).

Fluency in Python or TypeScript.

Proven experience designing and scaling ML-powered systems, ideally in regulated or high-stakes environments.

Experience with cloud platforms (AWS/GCP/Azure)

Familiarity with CI/CD pipelines (e.g., GitHub Actions).

Comfort with Docker, Kubernetes, and serving infra (Triton, TorchServe, FastAPI).

Comfort with MLOps tools: MLflow, Weights & Biases, Kubeflow, Airflow, etc.

Familiarity with data anonymization, access control, and encryption standards.

Understanding of regulatory frameworks like HIPAA (US), DPDP (India), or MDR (EU).

Ability to design AI systems with auditing and explainability in mind.

Bonus: Familiarity with EHR systems, medical ontologies, or clinical workflows.

Strong communicator who thrives in ambiguity—able to align stakeholders across product, design, and clinical teams.