Senior AI Engineer

Talkiatry•,

22h

About The Position

We're looking for an Senior AI Engineer to join a new AI Engineering team building foundational AI capabilities for mental healthcare at Talkiatry. You'll work across the AI lifecycle — from prototyping to production rollout, observability, and continuous improvement — building backend APIs, frontend interfaces, orchestration services, and internal tools that make AI useful, trustworthy, and actionable. You'll collaborate with senior engineers, product, clinical stakeholders, and data teams where your work directly impacts how AI is safely deployed in healthcare. This role is ideal for engineers with early LLM/agentic AI experience who want to deepen their skills on real production systems and grow into ownership of AI capabilities over time. About Talkiatry: Talkiatry is transforming mental health care by making high-quality psychiatry more accessible, human, and sustainable for both patients and clinicians. Co-founded by a patient and a triple-board-certified psychiatrist, we were built to solve one of healthcare’s most urgent challenges: millions of people struggle to access mental health care, while clinicians face growing administrative burden and burnout. Through our technology-powered, in-network platform, we’re changing that, creating a better experience for patients and empowering clinicians to focus on delivering exceptional care. Today, Talkiatry is the largest dedicated psychiatry practice in the U.S., with 750+ psychiatrists, 250+ therapists, and more than two million patient visits delivered nationwide. At our scale, every innovation has real impact. Every workflow we improve, every technology solution we build, and every patient experience we redesign helps thousands of clinicians provide better care to hundreds of thousands of patients. We’re not just growing quickly — we’re redefining how behavioral healthcare is delivered in America. Joining Talkiatry means joining a mission-driven team that is solving complex problems at scale, driving meaningful change in healthcare, and building the future of mental health care with compassion, innovation, and purpose.

Requirements

2+ years of software engineering experience, including building, testing, and maintaining production software systems.
1+ year of experience building with LLMs, agentic AI, or production AI systems, ideally beyond simple chatbot or prompt-only use cases.
Strong programming skills in Python and/or TypeScript, with experience building backend services, APIs, integrations, data flows, or full-stack product features.
Experience with modern frontend or full-stack development using technologies such as React, Next.js, TypeScript, Node.js, or similar frameworks.
Experience contributing to AI systems involving retrieval, tool use, workflow orchestration, structured outputs, context management, or multi-step execution.
Familiarity with agentic frameworks and orchestration tools such as LangGraph, CrewAI, OpenAI Agents SDK, or similar frameworks.
Familiarity with RAG systems, vector databases, semantic search, retrieval infrastructure, model serving, or knowledge pipelines.
Familiarity with cloud-native development, containerized services, Kubernetes, CI/CD workflows, or scalable production environments.
Strong debugging, communication, and collaboration skills, with the ability to work through ambiguity and make steady progress with guidance from senior engineers.

Nice To Haves

Experience building AI systems in healthcare, clinical, safety-critical, or other regulated environments.
Familiarity with HIPAA, clinical AI safety, FDA AI/ML guidance, or compliance-aware software development.
Experience using tests, evaluation methods, quality metrics, experiments, observability, or release checks to improve system reliability and performance.

Responsibilities

Build frontend interfaces, backend services, APIs, integrations, and data flows that make AI capabilities usable in patient, clinician, and internal workflows.
Build and iterate on agentic systems that use reasoning, tool use, retrieval, memory, and multi-step workflows to solve healthcare problems.
Build and maintain RAG pipelines, ingestion workflows, retrieval tuning, semantic search, and knowledge quality improvements.
Implement evaluation frameworks, automated tests, experiments, regression checks, and quality metrics to improve AI system performance over time.
Implement guardrails, fallback flows, human-in-the-loop workflows, access controls, tracing, monitoring, and diagnostics for production AI systems.
Contribute to reliable production rollouts, CI/CD workflows, debugging, incident response, performance improvements, and operational efficiency.
Work with senior engineers, product, clinical, design, and data partners to translate real workflows into safe, reliable AI-powered experiences.