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About This Role
At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.
The Position
A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche.
The Position:
TheAI Full Stack Engineer is a pivotal role within the Service Intelligence team, responsible for designing and deploying the software solutions that turns Roche Support Network (RSN) operational data into actionable tools. This individual will bridge the gap between complex AI models and the daily operations of field and depot service teams, ensuring that intelligence is not just generated, but accessible and intuitive for the enterprise. Your mission is to design, craft, deploy, and sustain software solutions that are tailored to business requirements and objectives using a combination of frontend, backend, full\-stack, and mobile development expertise. You adhere to in\-depth domain knowledge and promote a DevOps and Cloud\-focused approach. You will also act as a technical lead for projects and lead employees and processes in programming activities.
You have an overall understanding of the key challenges in our industry. You are passionate about the application of software engineering practices and their advanced application to data science to drive insights and value within a business\-centric environment.
The Opportunity:
- Drives End\-to\-End Service AI Applications: Oversees the full lifecycle of applications that support service performance, from initial design to the deployment of tools used by the RSN organization.
- Integrate Service Ecosystems: Design and deploy production\-grade APIs and interfaces that connect AI insights with core service systems like Salesforce® FSM and SAP®.
- Engineers for the Full Stack: Designs, crafts, and deploys production\-grade AI solutions using Python (Flask/FastAPI), SQL, and modern front\-end frameworks (like React or Vue.js with JavaScript). This includes building backend APIs, managing data pipelines as needed, and creating interactive user interfaces.
- Implements and Manages MLOps Infrastructure: Establishes and maintains the CI/CD/CT (Continuous Integration/Delivery/Training) pipelines necessary for automating the deployment, monitoring, and retraining of machine learning models in a cloud environment.
- Champions Service Intelligence Architecture: Ensures all solutions are built with scalability, reliability, and security in mind. Promotes best practices in version control (Git), containerization (Docker and Kubernetes), and cloud services (AWS, GCP, or Azure).
- Agile Prototyping for Service Excellence: Use agile methodologies to rapidly prototype and iterate on solutions based on feedback from service stakeholders and field leadership.
- Regulatory Alignment: Ensure all developed code and documentation adhere to the Roche Quality Management System (QMS) and regulatory standards such as ISO 13485
- Leads with Change Agility: Acts as a catalyst for transitioning the team from a project\-based support function to a product\-driven AI platform team, driving the adoption of new technologies from IT, and methodologies in a positive manner.
Who You Are:
- Bachelor’s degree in Computer Science, Information Systems, Business Administration, or other related field or equivalent work experience
- 7 years experience with previous business application system implementations / ERP system configuration or AI or data science applications
Preferred Requirements:
- Master’s or PhD degree in Computer Science, Statistics, Bioinformatics, Mathematics or equivalent preferred.
- Previous software engineering management and project management experience.
- Extensive stakeholder management and technical leadership experience.
- Expert understanding of software engineering best practices and their application in Data Science organizations.
- Solution\-oriented and agile approach to solving business problems.
- Ability to collaborate with peers and provide effective, enterprise\-wide capabilities and solutions.
- Expert understanding of key technologies including, but not limited to, Python, Javascript, and Web Frameworks.
- Expert understanding of key Cloud technologies and services (AWS, Azure, GCS)..
- Strong problem solving and consistent decision making skills.
- Strong written and verbal communication skills, particularly relating to conveying technical information to senior leadership.
This position is based in Indianapolis, IN and has an in office requirement of 3 days/wk.
Relocation benefits are not available for this job posting.
The expected salary range for this position based on the primary location of Indiana is $114,300 \- $212,300\. Actual pay will be determined based on experience, qualifications, geographic location, and other job\-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
Benefits
Who we are
A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life\-changing healthcare solutions that make a global impact.
Let’s build a healthier future, together.
Roche is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this formAccommodations for Applicants.
Salary Context
This $114K-$212K range is below the median for AI Software Engineer roles in our dataset (median: $190K across 193 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 3,824 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Roche, 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 $234,620 based on 682 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $160,000. This role's midpoint ($163K) sits 30% below the category median. Disclosed range: $114K to $212K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,380; Mid: $160,000; Senior: $227,400; Director: $243,000; VP: $250,000.
Roche AI Hiring
Roche has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Indianapolis, IN, US. Compensation range: $212K - $212K.
Location Context
Across all AI roles, 16% (613 positions) offer remote work, while 3,187 require on-site attendance. Top AI hiring metros: New York (2,448 roles, $210,000 median); San Francisco (1,990 roles, $253,000 median); Los Angeles (1,686 roles, $189,000 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 3,824 open positions tracked in our dataset. By seniority: 119 entry-level, 1,813 mid-level, 1,472 senior, and 420 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (613 positions). The remaining 3,187 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 31 roles); AI Safety ($274,200 median, 51 roles); Research Engineer ($260,000 median, 401 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 3,824 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,702), Data Scientist (281), AI Software Engineer (258). 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 (119) are outnumbered by mid-level (1,813) and senior (1,472) 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 420 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (613 positions), with 3,187 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 $200,000. Top-quartile roles start at $253,000, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $142,800. 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 (1,968 postings), Aws (1,203 postings), Azure (882 postings), Rag (877 postings), Gcp (735 postings), Prompt Engineering (587 postings), Pytorch (586 postings), Claude (554 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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