Interested in this AI Software Engineer role at Regal Medical Group?
Apply Now →About This Role
Company: Regal Medical Group is a large, physician\-led medical group based in Southern California, primarily serving patients in the San Fernando Valley, San Gabriel Valley, and surrounding areas. Founded in 1996, Regal operates as an Independent Physician Association (IPA) and works with major health plans including Medicare Advantage and Medi\-Cal. The group focuses on coordinated, value\-based care, emphasizing preventive health and chronic disease management. Regal is part of Heritage Provider Network, which ran the $3M Heritage Health Prize on Kaggle — a pioneer in applying machine learning to patient care.
Background: The Department of Innovation, AI is a small, focused team (5 members) tasked with modernizing a large, multi\-billion\-dollar healthcare business. We're rebuilding core healthcare infrastructure from the ground up to take full advantage of the latest AI models.
Role Summary: As a software engineer, you'll be responsible for embedding with various company teams to spec, build, and maintain new and existing AI applications. This role is close in nature to a forward\-deployed engineering position, where your ability to understand business cases and own product outcomes will be just as important as your raw technical acumen.
Requirements:
- Bachelor's degree required. New graduates and recent alumni are welcome to apply.
- Demonstrated experience in at least one programming language without the use of AI assistance/tools.
- Prior work/school projects showcasing an ability to deconstruct business requirements into a working final application.
- Strong social skills enabling you to operate effectively with a wide variety of personality types and roles.
Preferred Qualifications:
- Prior experience implementing large language models / generative AI in end\-user applications.
- Prior experience using AI\-assisted coding tools to develop and maintain high\-quality codebases.
- Interest or prior experience in the healthcare or healthcare technology industries.
This is a great opportunity for you if:
- You want to work on a small, mission\-driven team to achieve enormous, real\-world patient and business outcomes.
- You're flexible, pragmatic, and want to develop your business and people skills alongside your software engineering talent.
The pay range for this position at commencement of employment is expected to be between $125,000 year to $200,000 year; however, base pay offered may vary depending on multiple individualized factors, including market location, job\-related knowledge, licensure, skills, and experience.
The total compensation package for this position may also include other elements, including a sign\-on bonus and discretionary awards in addition to a full range of medical, financial, and/or other benefits (including 401(k) eligibility and various paid time off benefits, such as vacation, sick time, and parental leave), dependent on the position offered.
Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
If hired, employee will be in an “at\-will position” and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.
Full Time Position Benefits:
The success of any company depends on its employees. For us, employee satisfaction is crucial not only to the well\-being of our organization, but also to the health and wellness of our members. As such, we are firmly dedicated to providing our employees the options and resources necessary for building security and maintaining a healthy balance between work and life.
Our dedication to our staff is evident in our comprehensive benefits package. We offer a very generous mixture of benefits, including many employer\-paid options.
Health and Wellness:
- Employer\-paid comprehensive medical, pharmacy, and dental for employees
- Vision insurance
- Zero co\-payments for employed physician office visits
- Flexible Spending Account (FSA)
- Employer\-Paid Life Insurance
- Employee Assistance Program (EAP)
- Behavioral Health Services
Savings and Retirement:
- 401(k)Retirement Savings Plan
- Income Protection Insurance
Other Benefits:
- Vacation Time
- Company celebrations
- Employee Referral Bonus
- Tuition Reimbursement
- License Renewal CEU Cost Reimbursement Program
- Business\-casual working environment
- Sick days
- Paid holidays
- Mileage
Employer will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the LA City Fair Chance Initiative for Hiring Ordinance.
Requirements:
Requirements:
- Bachelor's degree required. New graduates and recent alumni are welcome to apply.
- Demonstrated experience in at least one programming language without the use of AI assistance/tools.
- Prior work/school projects showcasing an ability to deconstruct business requirements into a working final application.
- Strong social skills enabling you to operate effectively with a wide variety of personality types and roles.
Preferred Qualifications:
- Prior experience implementing large language models / generative AI in end\-user applications.
- Prior experience using AI\-assisted coding tools to develop and maintain high\-quality codebases.
- Interest or prior experience in the healthcare or healthcare technology industries.
Compensation: 125,000/year to 200,000 /year
Salary Context
This $125K-$200K range is below the median for AI Software Engineer roles in our dataset (median: $185K across 231 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 4,317 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Regal Medical Group, 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 in Demand for This Role
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 $218,500 based on 729 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($162K) sits 26% below the category median. Disclosed range: $125K to $200K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Regal Medical Group AI Hiring
Regal Medical Group has 1 open AI role right now. They're hiring across AI Software Engineer. Based in West Hills, CA, US. Compensation range: $200K - $200K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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