Interested in this AI Engineering Manager role at Talkiatry?
Apply Now →Skills & Technologies
About This Role
Talkiatry is seeking a Senior Manager of AI Engineering to drive AI innovations that make high quality mental healthcare more accessible. In this role, you’ll be the founding member of our AI technical team, defining and executing its roadmap, and lead cross\-functional efforts spanning engineering, clinical, compliance, and product teams.
About Talkiatry:
Talkiatry transforms psychiatry with accessible, human, and responsible care. We’re a national mental health practice co\-founded by a patient and a triple\-board\-certified psychiatrist to solve the problems both groups face in accessing and providing the highest quality treatment.
60% of adults in the U.S. with a diagnosable mental illness go untreated every year because care is inaccessible, while 45% of clinicians are out of network with insurers because reimbursement rates are low, and paperwork is unduly burdensome. With innovative technology and a human\-centered philosophy, we provide patients with the care they need—and allow psychiatrists to focus on why they got into medicine.
You will:
- 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.
You have \- Technical Skills:
- 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.
You have:
- 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.
Why Talkiatry:
- Top\-notch team: we're a diverse, experienced group motivated to make a difference in mental health care
- Collaborative environment: be part of building something from the ground up at a fast\-paced startup
- Flexible location: work where you want to, either remotely across the U.S. or from our HQ in NYC
- Excellent benefits: medical, dental, vision, effective day 1 of employment, 401K with match, generous PTO plus paid holidays, paid parental leave, and more!
- Grow your career with us: hone your skills and build new ones with our Learning team as Talkiatry expands
- It all comes back to care: we’re a mental health company, and we put our team’s well\-being first
*Talkiatry participates in E\-Verify and will provide the federal government with your Form I\-9 information to confirm that you are authorized to work in the U.S. only after a job offer is accepted and Form I\-9 is completed. For more information on E\-Verify, please visit the following:* *EVerify Participation* *\&* *IER Right to Work**.*
*At Talkiatry, we are an equal opportunity employer committed to a diverse, inclusive, and equitable workplace and candidate experience. We strive to create an environment where everyone has a sense of belonging and purpose, and where we learn from the unique experiences of those around us.*
*We encourage all qualified candidates to apply regardless of race, color, ancestry, religion, national origin, sexual orientation, age, citizenship, marital or family status, disability, gender, gender identity or expression, pregnancy or caregiver status, veteran status, or any other legally protected status.*
Compensation Range: $190K \- $240K
Salary Context
This $190K-$240K range is below the median for AI Engineering Manager roles in our dataset (median: $270K across 27 roles with salary data).
Role Details
About This Role
This role sits at the intersection of AI and engineering, building systems that bring machine learning capabilities into production environments. The scope varies by company, but the common thread is applying AI technology to solve real business problems at scale. Most AI roles today require a combination of software engineering fundamentals and domain-specific ML knowledge, with the exact mix depending on the team's maturity and the product they're building.
The AI job market is evolving fast. New role categories emerge as companies figure out what they need to ship AI-powered products. What matters most is the ability to learn quickly, build working systems, and iterate based on real-world performance data. The specific title matters less than the skills you bring and the problems you can solve. Companies are past the experimentation phase and want engineers who can deliver production-quality systems that work reliably at scale.
Across the 26,159 AI roles we're tracking, AI Engineering Manager positions make up 0% of the market. At Talkiatry, this role fits into their broader AI and engineering organization.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
What the Work Looks Like
Day-to-day work involves a mix of building, debugging, and collaborating. You'll write code, review pull requests, participate in design discussions, and work with cross-functional teams (product, design, data) to define what AI features should do and how they should behave. Expect to spend time on both technical implementation and communication. Most AI teams operate in two-week sprint cycles, with regular demos and retrospectives. The ratio of heads-down coding to meetings and reviews varies by seniority, with senior roles spending more time on architecture decisions and mentorship.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
Skills Required
Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.
Beyond the core stack, communication skills matter more than many technical candidates realize. The ability to explain AI capabilities and limitations to non-technical stakeholders is a differentiator at every level. Technical writing, documentation, and clear thinking about tradeoffs are underrated skills in AI roles. Experience with evaluation methodology (how to measure whether an AI system is working well) is becoming a core requirement, especially for roles that involve LLM integration.
Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
Compensation Benchmarks
AI Engineering Manager roles pay a median of $293,500 based on 28 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($215K) sits 27% below the category median. Disclosed range: $190K to $240K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Architect ($292,900) and AI Safety ($274,200). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Talkiatry AI Hiring
Talkiatry has 3 open AI roles right now. They're hiring across AI Engineering Manager, AI/ML Engineer. Positions span Remote, US, New York, NY, US, US. Compensation range: $160K - $240K.
Location Context
AI roles in Austin pay a median of $212,800 across 317 tracked positions. That's 16% above the national median.
Career Path
Common paths into AI Engineering Manager roles include Software Engineer, Data Scientist, Data Analyst.
From here, career progression typically leads toward Senior Engineer, AI Architect, Engineering Manager, Principal Engineer.
Focus on building things that work. A deployed project that solves a real problem is worth more than any certification. Contribute to open-source, build portfolio projects, and invest in fundamentals (software engineering, statistics, systems design) rather than chasing the latest framework. The AI field moves fast, but the engineers who succeed long-term are the ones with strong fundamentals who can adapt to new tools and paradigms as they emerge.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
AI Hiring Overview
The AI job market has 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 roles).
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
The AI Job Market Today
The AI job market spans 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (2,416) are outnumbered by mid-level (16,247) and senior (5,153) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.