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About This Role
Blossom Health exists to solve the mental health epidemic in America by partnering with psychiatrists to expand access toaffordable, timely, clinically\-effective mental healthcare. Our AI\-native care platform is loved by hundreds of clinicians and thousands of patients.
We’re a Series A company with $20M\+ raised from Headline, Village Global, and the founders of General Catalyst, Flatiron Health, Sword Health, Grow Therapy, Fay, Elemy, Zip, Blank Street, Assured, Bridge, Birches Health, and Enzo Health.
Why you should work here:
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- Hyper\-growth environment: Get firsthand exposure to how a startup scales from 0 1 n, with visibility across product, engineering, and operations
- High trust and autonomy: You’ll own meaningful projects from day one and shape both technical decisions and product direction. We trust engineers to figure out the best path forward \- without micromanagement.
- Talent\-dense team: Work with a top\-percentile team built on mutual respect and admiration, with shared goals, motivations, and vision for the future.
- Real impact: Your code will directly improve access to mental health care for thousands of patients and clinicians
What we're looking for:
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- Highly motivated, ambitious, and capable \- looking to tackle a large, meaningful problem area
- Ownership mindset \- thinking for the long\-term and placing the business and our customers first
- High velocity and high excellence \- have a real sense of urgency to move quickly and take pride in the quality of your work
- An explorer \- comfortable with ambiguity and autonomy, seeking to answer questions previously unasked, to leap into the unknown
- An optimist \- you believe in a tomorrow better than today
- A builder \- you take joy in bringing new creation to the world, in leveraging technology to make useful things
- Humble \- you use your gifts in the service of others and understand that success is an output, not an input
What you'll do:
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- Design and build scalable, reliable systems powering core product workflows
- Ship high\-quality code that balances speed and technical rigor
- Proactively identifying and resolving system reliability risks, owning uptime, observability, and performance as first\-class engineering concerns
- Leverage cutting\-edge AI to create intuitive and novel clinician and patient experiences
- Conduct thoughtful code reviews and provide technical mentorship, raising the bar for engineering excellence across the team and beyond
You'll thrive here if you:
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- Have a bachelor's degree or equivalent experience in Computer Science or related field
- Have 2\+ years of professional working experience outperforming in high\-quality environments
- Excel at building production systems end\-to\-end with minimal oversight
- Are fluent in TypeScript and/or Python (experience with LLM\-powered apps preferred)
- Are comfortable with traversing the software stack and picking up the latest technologies to drive technical outcomes
- Love autonomy, ambiguity, and ownership
- Are authorized to work in the U.S. and excited to be in\-person in NYC 5 days a week
Benefits:
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- Competitive salary, equity, growth opportunities
- Best\-in\-class health, dental, and vision insurance
- A focus on outcomes, not hours, with unlimited PTO
- Team outings, offsites, and a sunny NYC office stocked with snacks
Compensation Range: $150K \- $220K
Salary Context
This $150K-$220K range is above the median for AI Software Engineer roles in our dataset (median: $183K across 194 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 3,708 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Blossom Health, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $219,250 based on 424 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($185K) sits 16% below the category median. Disclosed range: $150K to $220K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Blossom Health AI Hiring
Blossom Health has 1 open AI role right now. They're hiring across AI Software Engineer. Based in New York, NY, US. Compensation range: $220K - $220K.
Location Context
AI roles in New York pay a median of $220,000 across 1,045 tracked positions.
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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.
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