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About This Role
NYU Langone Health is a fully integrated health system that consistently achieves the best patient outcomes through a rigorous focus on quality that has resulted in some of the lowest mortality rates in the nation. Vizient Inc. has ranked NYU Langone the No. 1 comprehensive academic medical center in the country for three years in a row, and U.S. News & World Report recently placed nine of its clinical specialties among the top five in the nation. NYU Langone offers a comprehensive range of medical services with one high standard of care across 6 inpatient locations, its Perlmutter Cancer Center, and over 320 outpatient locations in the New York area and Florida. With $14.2 billion in revenue this year, the system also includes two tuition-free medical schools, in Manhattan and on Long Island, and a vast research enterprise with over $1 billion in active awards from the National Institutes of Health.
For more information, go to NYU Langone Health, and interact with us on LinkedIn, Glassdoor, Indeed, Facebook, X, YouTube and Instagram.
Position Summary:
We have an exciting opportunity to join our team as a Lead Software Engineer - AI Coding.
As a Lead Software Engineer in AI Coding, you will be responsible for creating software applications using advanced AI coding tools and techniques. You will play a crucial role in the design, development, and maintenance of our custom software development projects. Your expertise will ensure the successful delivery of high-quality, scalable, and secure web solutions.
Job Responsibilities:
- Use AI coding tools to create source code as required to implement features as assigned during sprint planning activities.
- Develop test harnesses and quality gates for AI generated code.
- Perform production deployments as needed.
- Participate in daily standups and scrum ceremonies estimating story points for requested work.
- Provide support and guidance for junior developers and offshore engineers
- Implement code with best practices for operational support error handling, logging, graphing of key metrics, graceful failure, tuning timeouts appropriately.
- Lead, direct, delegate work and serve as a liaison to a team of engineers (both onshore and offshore) to accomplish sprint goals.
- Encourage adherence to standards & best practices - graceful failure, security, unit testing, devops, instrumentation drive the build to operate strategy.
- Encourage and facilitate continuous improvement strategies to improve operational viability and overall maturity of custom software products based on published maturity model
- Evaluate tools and technologies and provide analysis and recommendations
- Participate in a 24x7x365 on-call rotation. Provide support as needed during production outages off-hours.
Minimum Qualifications:
- BS or MS in engineering or computer science related discipline or equivalent experience.
- 8+ years of building custom software solutions using at least two modern, object-oriented programming and/or scripting languages using a web application framework.
- 2+ years serving as a tech lead on a team directing engineering efforts, delegating work and serve as a liaison to a team of engineers (both onshore and offshore) to accomplish sprint goals.
- Expert knowledge of web technologies including HTTP 2, TLS encryption, caching, web browsers, cookies, http headers, html ,javascript and CSS (web only).
- Expert knowledge of using at least one advanced AI coding tool using spec driven development (SDD) and building harnesses for coding agents.
- Expert knowledge of the Unix operating system (RHEL/Centos, Ubuntu).
- Expert knowledge of GIT version control including using branches, code reviews, tags, etc.
- Expert knowledge of using Unit testing frameworks and experience writing unit tests as part of the development process.
- Expert Knowledge of agile scrum methodology and experience working on a scrum team.
- Expert knowledge of relational database technologies designing normalized relational schemas, creating schemas, indexes, writing sql queries and troubleshooting performance issues (web and service).
- Expert knowledge of creating REST APIs and REST standards using standard tools that automatically create API documentation (web and service)
- Full stack development capabilities - Expert knowledge of both front end (HTML, CSS, Javascript, React) and backend (Python, PHP) scripting languages for feature development, unit testing, instrumentation and debugging.
- Expert troubleshooting capabilities
- Working knowledge of one cloud computing platform creating cloud-based infrastructure and managing with infrastructure as code tools (web and service)
- Working knowledge of devops tools creating code pipelines using Jenkins (or equivalent) to automatically deploy and validate deployments(web and service)
- Working knowledge of test automation tools and ability to integrate testing into pipelines. Types of tests include functional, service, contract and networking failure mode.
- Ability to troubleshoot and resolve production issues application, networking and OS level and provide Teir 2 production support.
- Positive and growth-oriented mindset. Flexible personality, comfortable with collaboration, open communication and reaching across functional borders.
- Verbal and oral communication skills. Ability to collaborate with team members to complete team goals.
Preferred Qualifications:
Preferred Qualifications:None.
Qualified candidates must be able to effectively communicate with all levels of the organization.
NYU Langone Health provides its staff with far more than just a place to work. Rather, we are an institution you can be proud of, an institution where you'll feel good about devoting your time and your talents.
At NYU Langone Health, we are committed to supporting our workforce and their loved ones with a comprehensive benefits and wellness package. Our offerings provide a robust support system for any stage of life, whether it's developing your career, starting a family, or saving for retirement. The support employees receive goes beyond a standard benefit offering, where employees have access to financial security benefits, a generous time-off program and employee resources groups for peer support. Additionally, all employees have access to our holistic employee wellness program, which focuses on seven key areas of well-being: physical, mental, nutritional, sleep, social, financial, and preventive care. The benefits and wellness package is designed to allow you to focus on what truly matters. Join us and experience the extensive resources and services designed to enhance your overall quality of life for you and your family.
NYU Langone Health is an equal opportunity employer and committed to inclusion in all aspects of recruiting and employment. All qualified individuals are encouraged to apply and will receive consideration. We require applications to be completed online.
View Know Your Rights: Workplace discrimination is illegal.
NYU Langone Health provides a salary range to comply with the New York state Law on Salary Transparency in Job Advertisements. The salary range for the role is $121,792.21 - $166,950.00 Annually. Actual salaries depend on a variety of factors, including experience, specialty, education, and hospital need. The salary range or contractual rate listed does not include bonuses/incentive, differential pay or other forms of compensation or benefits.
To view the Pay Transparency Notice, please click here
Salary Context
This $121K-$166K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $193K across 172 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 9,653 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At NYU Langone 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 $220,000 based on 1,448 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $228,700. This role's midpoint ($144K) sits 34% below the category median. Disclosed range: $121K to $166K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
NYU Langone Health AI Hiring
NYU Langone Health has 5 open AI roles right now. They're hiring across AI Software Engineer, Research Scientist, Research Engineer, AI/ML Engineer. Positions span New York, NY, US, New York, NY. Compensation range: $166K - $166K.
Location Context
AI roles in New York pay a median of $221,000 across 2,878 tracked positions. That's 4% above the national median.
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 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 $253,100 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 (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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
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