Medical Director, AI Safety

Remote Mid Level AI Safety

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About This Role

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About Avo

Avo is the leading AI platform for healthcare enterprises, helping clinicians make better decisions, move faster, and improve the quality of patient care. Serving as a central hub for care teams, Avo brings together patient data, clinical knowledge, and AI-powered workflows to support diagnosis, care planning, documentation, orders, and evidence-based decision-making at the point of care. Clinicians today navigate dozens of tabs, applications, datasets, hospital protocols, medical guidelines, and payer policies to deliver high-quality care. Avo changes that.

We are product-obsessed, collaborative, and scrappy, united by a mission to improve healthcare delivery through AI. Our investors include Noro-Moseley Partners, AlleyCorp, Scrub Capital, and several leading hospitals and universities.

The Role

We are seeking a Medical Director, AI Safety that will own the safety of Avo's AI-generated clinical content. That means deciding what "safe enough to ship" means for a discharge summary, a pre-visit summary, or a decision-support module, building the tests that enforce it, and signing off before it reaches a clinician. You will design the grading rubrics, run the evaluations, classify failures by clinical severity, and turn the findings into changes the Studio and engineering teams make.

Roughly 85% of your time goes to safety. The remaining 15% splits two ways: building clinical modules yourself in Avo's Studio, so your safety judgments are grounded in how the content is actually produced, and joining sales and customer conversations as the physician who can explain how we test and why a CMIO should trust the output.

You report to the CMIO, with a dotted line to the Chief Commercial Officer.

What You'll Do

  • AI safety (core of the role)

+ Define the safety standard for each product line: what counts as a hallucination, an omission, or a clinically material error, and how severe each is + Design and run evaluation protocols for clinical AI modules, including hallucination detection, omission analysis, and accuracy checks against source records and evidence-based guidelines + Build and maintain a clinical harm taxonomy and grading rubric (NCC MERP-style severity scoring) and apply it across benchmark sets + Review AI-generated clinical content directly, and grade the automated graders so we know when to trust them + Own the release gate: write the go/no-go safety assessment for new modules and major prompt or model changes + Investigate reported clinical errors from customers, trace root cause, and drive the fix through Studio and engineering + Write the safety reports, validation summaries, and white papers that buyers and their clinical governance committees ask for + Track the regulatory and standards landscape for clinical AI (FDA, ONC, CHAI, Joint Commission) and translate it into internal requirements*Clinical builder (~5-10%)*

+ Build or revise clinical modules in Avo's Studio, applying evidence-based guidelines and your own practice experience + Feed what you learn from building back into the safety protocols, and vice versa*Sales-forward clinician (~5-10%)*

+ Join prospect calls and pilot evaluations as the physician who can speak to how Avo's content is validated + Present the safety program to CMIOs, CIOs, and clinical quality leaders, and answer their hardest questions about failure modes + Challenge the status quo in the room: name where legacy documentation and CDS workflows fail patients, and show how a tested AI alternative does better

What You Bring

  • Active clinical license (MD/DO, NP, or PA) with hands-on patient care experience
  • 3-7 years of clinical practice; you can read a discharge summary and spot the missed anticoagulation plan in under a minute
  • Experience with or strong interest in clinical AI, CDS, or health informatics
  • A testing mindset: you like designing the rubric, arguing about edge cases, and finding the error nobody else caught
  • Ability to write a clear, defensible safety report for a clinical governance committee
  • Comfort presenting to C-suite clinical leaders and answering pointed questions about AI failure modes
  • Willingness to define the role's scope as the product and company grow
  • Travel: Some travel expected for customer meetings and demos, up to 10%

Nice to Have

  • Experience with EHR systems (Epic, Meditech, Athena)
  • Background in clinical informatics, quality improvement, or patient safety
  • Prior experience in a sales engineering, solutions, or customer-facing clinical role
  • Familiarity with AI/LLM evaluation methodologies

Why Join Avo

Impact: Avo's products run inside hospitals, helping clinicians make better calls at the point of care. The work is real, and the mission is meaningful.

Ownership: We have a bias for action; you'll work alongside teams who take initiative, follow through on commitments, and take accountability for results.

High Agency: We move fast, trust our people, and avoid bureaucracy.

Great Team: Work alongside a talented, low-ego group of clinicians, engineers, and product folks who care deeply about craft.

Remote-First: Work from anywhere in the US. The company has offices in NYC, so if you're in the area we'd love the chance to work in-person together 2 days/week.

How We Take Care of Our Team

  • Generous Time Off: Flexible and generous PTO
  • Comprehensive Health Plans: Medical, dental, and vision coverage for you and your family
  • 401K Matching: Contribution matching to help invest in your future
  • Personal Device Allowance: Tax-free funds for personal device usage
  • Compensation and Equity: $175,000 - $200,000 OTE and equity

Role Details

Company AVO
Title Medical Director, AI Safety
Location Remote, US
Category AI Safety
Experience Mid Level
Salary Not disclosed
Remote Yes

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 9,079 AI roles we're tracking, AI Safety positions make up 1% of the market. At AVO, 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 in Demand for This Role

Python (18% of roles) Aws (10% of roles) Azure (8% of roles) Rag (7% of roles) Gcp (6% of roles) Pytorch (5% of roles) Claude (5% of roles) Kubernetes (4% of roles)

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 Safety roles pay a median of $256,000 based on 66 positions with disclosed compensation. Director-level AI roles across all categories have a median of $272,300.

Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include Research Engineer ($252,000) and AI Engineering Manager ($251,622). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.

AVO AI Hiring

AVO has 1 open AI role right now. They're hiring across AI Safety. Based in Remote, US.

Remote Work Context

Remote AI roles pay a median of $188,000 across 2,316 positions. About 6% of all AI roles offer remote work.

Career Path

Common paths into AI Safety 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.

The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.

Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. 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: Python (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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

Based on 66 roles with disclosed compensation, the median salary for AI Safety positions is $256,000. Actual compensation varies by seniority, location, and company stage.
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.
About 6% of the 9,079 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
AVO is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from AI Safety positions include Senior Engineer, AI Architect, Engineering Manager, Principal Engineer. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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