Senior Manager of AI Engineering

Talkiatry is a national mental health practice focused on making high-quality mental healthcare more accessible. They are seeking a Senior Manager of AI Engineering to lead the development of AI innovations, define the AI roadmap, and collaborate with cross-functional teams to enhance mental healthcare delivery.

Responsibilities:

• Define and lead the AI roadmap across experimentation, model evaluation, deployment, and iteration
• Architect systems to support safe and scalable LLM interactions—including prompt chaining, memory retention, and RAG pipelines
• Develop strategies for model selection (e.g., Azure OpenAI, AWS Bedrock, open-source) and cost-effective inference at scale
• Design and implement experiments to evaluate the efficacy, safety, and impact of AI innovations
• Build and scale a high-performing AI team across machine learning, data science, MLOps, and backend infrastructure
• Serve as the AI technical authority in conversations with external vendors, cloud partners, compliance officers, and executive stakeholders
• Partner with legal and clinical teams to ensure HIPAA compliance, BAA alignment, and safe handling of sensitive patient data

Requirements:

• Expert in large language models (OpenAI, Anthropic, Mistral, etc.), including fine-tuning, prompt engineering, embeddings, and context window optimization
• Hands-on experience with RAG frameworks, vector databases (Pinecone, FAISS, Redis), and memory architectures
• Strong programming background in Python and ML stack (PyTorch, HuggingFace Transformers, LangChain, Weights & Biases)
• Proficiency with cloud platforms (AWS, Azure), containerization (Docker, Kubernetes), and orchestration tools (Airflow, FastAPI, etc.)
• Deep familiarity with model evaluation frameworks—automated and human-in-the-loop—for conversation safety, empathy, and hallucination detection
• 5+ years of experience in AI/ML roles, with at least 3 years leading cross-functional teams including engineering, product, and research
• A successful track record of shipping production-grade AI systems—ideally in healthcare, mental health, or another mission-critical domain
• Deep technical fluency in LLMs, retrieval systems, and safe interaction design—with an ability to lead architectural decisions and implementation
• Experience building or managing AI teams from 0→1, with a strong recruiting eye and mentorship skills
• Familiarity with ethical AI, including red-teaming, bias mitigation, explainability, and escalation protocols for risky outputs
• Strong understanding of healthcare compliance (e.g., HIPAA, PHI), including how to architect systems with auditability and patient safety in mind
• A pragmatic approach to experimentation and iteration—balancing cutting-edge AI with operational feasibility and clinical guardrails
• Exceptional communication skills—you can convey technical decisions to both engineers and executives, and lead strategic conversations with confidence