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About This Role
Omada Health is on a mission to bend the curve of chronic disease.
Job overview:
We are seeking a Senior Software Engineer to help design, build, and scale modern data platform capabilities using cloud\-native technologies and AI\-driven solutions.
In this role, you will develop reusable frameworks, platform services, and engineering patterns that enable teams to build reliable, scalable data\-products and AI\-powered workflows. You will also leverage Generative AI to enhance data discovery, governance, developer productivity, and self\-service access to trusted data. Working closely with cross\-functional teams, you will help shape a modern data platform that accelerates innovation while ensuring security, reliability, and operational excellence.
Your Impact:
- Design, build, and operate scalable Data \& AI platform capabilities for analytics, data science, and Generative AI use cases with strong practices around data quality, lineage, observability, security, and governance.
- Develop reusable abstractions, templates, services, and workflows that standardize how teams build and manage data pipelines and data products.
- Partner with Analytics, Applied\-AI, Data\-engineering and application teams to deliver platform capabilities that support business and clinical decision\-making
- Evaluate and integrate modern data and AI technologies with a focus on scalability, reliability, developer experience, and cost efficiency
- Apply Generative AI technologies to improve data enablement, documentation, discovery, workflow automation, and platform usability
- Promote software engineering best practices, including clean code, automated testing, CI/CD, infrastructure\-as\-code, monitoring, and secure data handling
About you:
- 5\+ years of professional software engineering or data engineering experience building scalable data platforms, services, pipelines, or analytics infrastructure
- Hands\-on experience with modern data architectures, including data lakes, lakehouses, warehouses, analytical datastores, and batch or real\-time processing systems
- Strong programming skills in Python and SQL, with experience building production\-grade data systems
- Working knowledge of distributed computing and cloud\-native technologies such as Spark, Kubernetes etc
- Hands\-on experience with Infrastructure as Code using Terraform (or a similar tool such as Pulumi, CloudFormation/CDK) to provision and manage cloud infrastructure.
- Experience applying data engineering best practices around data quality, lineage, governance, reliability, observability, and operational excellence
- Practical experience using Generative AI tools or technologies to improve engineering workflows, automation, analytics, or data platform capabilities
- Strong problem\-solving, communication, and collaboration skills, with the ability to work effectively across technical and non\-technical teams
- Self\-directed, pragmatic, and comfortable working through ambiguity in a fast\-moving environment
Bonus Points for:
- Hands\-on experience with Databricks, including Delta Lake, Unity Catalog, Workflows, Delta Live Tables, MLflow, Model Serving.
- Experience with NoSQL datastores, including document databases, graph databases, key\-value stores, wide\-column stores, or search\-oriented systems
- Experience with Generative AI application patterns such as RAG, knowledge\-graph, etc.
- Experience working with sensitive data in regulated environments such as healthcare, privacy, fintech, or other compliance\-heavy industries
Benefits:
- Competitive salary with generous annual cash bonus
- Equity grants
- Remote first work from home culture
- Flexible Time Off to help you rest, recharge, and connect with loved ones
- Generous parental leave
- Health, dental, and vision insurance (and above market employer contributions)
- 401k retirement savings plan
- Lifestyle Spending Account (LSA)
- Mental Health Support Solutions
- ...and more!
It takes a village to change health care. As we build together toward our mission, we strive to embody the following values in our day\-to\-day work. We hope these hold meaning for you as well as you consider Omada!
- Cultivate Trust. We listen closely and we operate with kindness. We provide respectful and candid feedback to each other.
- Seek Context. We ask to understand and we build connections. We do our research up front to move faster down the road.
- Act Boldly. We innovate daily to solve problems, improve processes, and find new opportunities for our members and customers.
- Deliver Results. We reward impact above output. We set a high bar, we're not afraid to fail, and we take pride in our work.
- Succeed Together. We prioritize Omada's progress above team or individual. We have fun as we get stuff done, and we celebrate together.
- Remember Why We're Here. We push through the challenges of changing health care because we know the destination is worth it.
About Omada Health: Omada Health (Nasdaq: OMDA) is reverse engineering the way healthcare is delivered in America, putting the space between doctor visits–where health is won or lost–at the center of care. Today's healthcare system poorly serves chronic conditions that require ongoing support outside of the exam room, like obesity, diabetes, hypertension, cholesterol, and musculoskeletal conditions. Omada's virtual\-first model combines human\-led care teams, connected devices, and AI\-enabled technology to deliver personalized care at scale, including support for GLP\-1 therapy. Omada has served more than two million members since launch across 2,000\+ employers, health plans, pharmacy benefit managers, and health systems. Learn more at omadahealth.com.
Omada is thrilled to share that we've been certified as a Great Place to Work! Please click here for more information.
We carefully hire the best talent we can find, which means actively seeking diversity of beliefs, backgrounds, education, and ways of thinking. We strive to build an inclusive culture where differences are celebrated and leveraged to inform better design and business decisions. Omada is proud to be an equal opportunity workplace and affirmative action employer. We are committed to equal opportunity regardless of race, color, religion, sex, gender identity, national origin, ancestry, citizenship, age, physical or mental disability, legally protected medical condition, family care status, military or veteran status, marital status, domestic partner status, sexual orientation, or any other basis protected by local, state, or federal laws.
Below is a summary of salary ranges for this role in the following geographies:
California, New York State and Washington State Base Compensation Ranges: $179,400 \- $224,300\*, Colorado Base Compensation Ranges: $171,600 \- $214,500\*. Other states may vary.
This role is also eligible for participation in annual cash bonus and equity grants.
- The actual offer, including the compensation package, is determined based on multiple factors, such as the candidate's skills and experience, and other business considerations.
Please click here for more information on our Candidate Privacy Notice.
Salary Context
This $171K-$224K 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 Omada 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. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($197K) sits 10% below the category median. Disclosed range: $171K to $224K.
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.
Omada Health AI Hiring
Omada Health has 2 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer. Based in Remote, US. Compensation range: $224K - $338K.
Remote Work Context
Remote AI roles pay a median of $185,334 across 717 positions. About 14% of all AI roles offer remote work.
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.
Frequently Asked Questions
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