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About This Role
Strength in Trust
OneTrust's mission is to enable innovation through the responsible use of data and AI. We believe that ensuring data is trusted shouldn't slow teams down—it should accelerate what's possible. This led us to develop the first technology platform for responsible data use in 2016. Today, with AI representing the latest and most impactful expansion of data yet, OneTrust is once again redefining what responsible innovation looks like. OneTrust, the AI‑Ready Governance Platform™, unifies regulatory intelligence, automation, and connected governance workflows so businesses can continue to move at the speed of AI while ensuring good governance to prevent data misuse at scale. Trusted by thousands of organizations worldwide, OneTrust is shaping the future where trusted data becomes a transformative force for business and society.
The Challenge
As a Senior Staff Software Engineer, you will serve as a technical leader for OneTrust's AI Governance (AIG) platform, driving the design, scalability, and reliability of systems that enable enterprises to deploy and govern AI and LLM-powered applications responsibly. You will deeply understand how customers build, deploy, and operate AI systems, and translate those needs into secure, compliant, and observable platform capabilities.
Your Mission
Development
- Lead the design and development of Java/Python microservices and shared libraries integrating with AI platforms for OneTrust's AI Governance product.
- Design, build, and test cloud-native applications deployed on Microsoft Azure using Core Java, REST, and the Spring ecosystem.
- Lead the architecture and development of reusable AIG reporting and dashboard capabilities that integrate governance data from SQL databases and analytical platforms with runtime observability signals.
- Design reusable semantic-layer and metric-abstraction capabilities, including dataset contracts, metric definitions, query APIs, pre-aggregation, caching, filtering, time-period selection, and drill-down workflows.
- Lead event-driven integrations using Kafka and Apache Flink to consume normalized observability events and produce dashboard-ready datasets and derived metrics.
- Integrate with the AI Observability platform through well-defined APIs and data contracts for runtime metrics, logs, traces, alerts, policy decisions, and evidence.
- Own technical design for critical systems, ensuring scalability, security, and reliability.
- Partner with frontend engineers to build reusable dashboard shells, visualization components, filters, data tables, and entity drill-down experiences.
- Maintain strong automated unit and integration test coverage in line with team standards.
Collaboration
- Work closely with UX, Product Managers and/or Product Owners, as well as other developers to contribute to planning and grooming sessions and drive team discussions on system architecture and component design.
- Partner with Product, UX, and Customer Success to understand customer AI use cases and governance needs.
- Lead architecture discussions and technical planning.
- Drive alignment across teams on platform design and priorities.
- Contribute to sprint planning and delivery.
Support
- Reduce defects by identifying and addressing issues early in the development lifecycle.
- Ensure critical and high-priority CII's are delivered per SLA.
- Promote early defect detection through strong design and testing.
- Improve system monitoring, resilience, and operational maturity.
Code Review
- Set standards for clean, secure, and maintainable code.
- Conduct thorough reviews for distributed and AI-enabled systems.
- Guide engineers on testing, automation, and AI system validation.
Lead
- Help build high-performing teams by mentoring the team on new technical skills.
- Influence technical strategy and long-term platform direction.
- Build a culture of ownership, learning, and engineering excellence.
- Lead multi-quarter technical roadmaps across teams and make practical build-versus-reuse decisions.
You Are
A senior technical leader with strong system design and hands-on execution skills, who understands how enterprises use AI and LLMs in real-world workflows and can translate those needs into scalable, secure, and compliant platform solutions.
Your Experience Includes
- Bachelor's or master's degree in computer science, Engineering, or a related technical or business field.
- 12+ years of professional software engineering and development experience.
- Strong expertise in Java/J2EE, Spring, Python, design patterns, microservices, and cloud-native distributed systems.
- Proven experience leading reusable platform, reporting, analytics, or data products that support multiple teams or dashboards.
- Hands-on experience with Cube.js, semantic layers, metric layers, or comparable metric/query abstraction systems.
- Hands-on experience with Apache Flink for real-time stream processing, windowed aggregation, event correlation, or derived-metric generation.
- Experience designing event-driven services and data-ingestion pipelines using Kafka, including integrations with SQL databases, analytical platforms, APIs, and observability systems.
- Strong experience with data modeling, dataset contracts, pre-aggregation, read models, caching, query optimization, and data-quality controls.
- Experience building secure, multi-tenant SaaS platforms with tenant isolation, authentication, authorization, and secure service-to-service communication.
- Experience working with AI/LLM platforms and production AI workloads, including model orchestration, RAG, evaluation, guardrails, or runtime observability.
- Good understanding of REST, OAuth, JSON, SQL, NoSQL databases, and Python or Bash scripting.
- Experience with CI/CD, automated testing, production monitoring, incident response, and Agile development practices.
- Experience with Azure, AWS, Google Cloud, and open-source technologies.
- Ability to lead multi-quarter roadmaps, make practical build-versus-reuse decisions, and align engineering, product, UX, security, platform, and observability teams.
Extra Awesome
- Experience with OpenTelemetry, VictoriaMetrics, Prometheus/MetricsQL, Grafana Loki/LogQL, Grafana Tempo/TraceQL, Alertmanager, or Open Policy Agent.
- Experience integrating with Databricks, Delta Lake, Power BI, or other analytical data platforms.
- Experience building configurable dashboard systems, data visualization frameworks, or design-system-based frontend platforms.
- Experience with AI governance, model risk management, compliance, GRC, audit evidence, or regulatory reporting.
- Experience with graph data models, dependency maps, entity resolution, or supply-chain analysis.
- Experience designing SDK telemetry, model gateways, runtime instrumentation, or post-market monitoring.
- Proficiency in Kubernetes, including cluster deployment, scaling, and management is highly desirable.
- Background in enterprise, regulated, or security-focused environments.
Where we Work
We are embracing an office-first culture, encouraging three days a week in office for most roles, with meaningful opportunities to collaborate and celebrate in person.
Each role may have specific requirements or flexibility depending on the scope of the position, so we encourage you to verify this with your recruiter during your first interview.
Benefits
As an employee at OneTrust, you will be part of the OneTeam. That means you'll receive support physically, mentally, and emotionally so that you can do your best work both in and out of the office. This includes comprehensive healthcare coverage, flexible PTO, equity RSUs, annual performance bonus opportunities, retirement account support, 14+ weeks of paid parental leave, career development opportunities, company-paid privacy certification exam fees, and much more. Specific benefits differ by country. For more information, talk to your recruiter or visit onetrust.com/careers.
Resources
Check out the following to learn more about OneTrust and its people:
- OneTrust Careers on YouTube
- @LifeatOneTrust on Instagram
Your Data
You have the right to have your personal data updated or removed. You also have the right to have a copy of the information OneTrust holds about you. Further details about these rights are available on the website in our Privacy Overview. You can change your mind at any time and have your personal data removed from our database. In order to do this you must contact us and let us know you wish to be removed. The request should be made on the Data Subject Request Form.
Recruitment fraud warning: OneTrust is aware of scams involving false offers of employment with our company. The fraudulent jobs, interviews and job offers use fake websites, email addresses, group chat and text messages. Be aware that we never ask candidates for personal information, IDs or bank information during the interview process. We do not interview prospective candidates via instant message or group chat, and do not require candidates to purchase products or services, or process payments on our behalf as a condition of any employment offer. Please note that any legitimate interview availability requests will come directly from a OneTrust recruiter with an "@onetrust.com" email address. You may also receive legitimate emails from "@us.greenhouse-mail.io". Recruiters will only reach out to candidates who have applied for a role through our ATS (Greenhouse) or prospects via LinkedIn InMail. Job offers will come from a recruiter and may have a "@docusign.net" email address. For more information or if you have been targeted please reach out to [email protected].
Our Commitment to You
When you join OneTrust you are stepping onto a launching pad — the countdown has begun. The destination? A career without boundaries working alongside a diverse and inclusive crew who is passionate about doing meaningful work. As a pioneer, your voice and expertise will help chart the direction of an entirely new category. Our commitment to putting people first starts with you. Your growth is part of the mission. Our goal is to give you the power to embark on the next phase of your uniquely, unique career.
OneTrust provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by local laws.
Salary Context
This $165K-$247K range is above the median 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 OneTrust, 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 ($206K) sits 6% below the category median. Disclosed range: $165K to $247K.
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.
OneTrust AI Hiring
OneTrust has 3 open AI roles right now. They're hiring across AI Product Manager, AI Software Engineer, AI/ML Engineer. Positions span Atlanta, GA, US, Madrid, Community of Madrid, Spain. Compensation range: $186K - $247K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 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 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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