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About This Role
*When applying for roles at Tealium, please use our official careers page or LinkedIn company profile. All other sites where Tealium careers may appear may not be legitimate.*
WHO WE ARE
Tealium is the trusted leader in real\-time Customer Data Platforms (CDP) , helping organizations unify their customer data to deliver more personalized, privacy\-conscious experiences. As the demand for connected, intelligent customer engagement grows, Tealium’s leadership in CDP is translating directly into leadership in enabling enterprise AI strategies . By providing clean, consented, and actionable data, Tealium empowers its customers to accelerate the adoption of AI and machine learning, fueling smarter personalization, predictive insights, and business outcomes at scale.
More than 800 leading global brands trust Tealium to power their customer data strategies and deliver real\-time, personalized experiences at scale.
Team Tealium has team members present in nearly 20 countries worldwide, serving customers across more than 30 countries. We win together with respect and appreciation for the talents required of all positions and the people who contribute to each of these. We are intentional about our WOWs (Ways of Work) culture, our investment in our team members, and how we care and connect.
With an extraordinary portfolio of investors (including Georgian, Silver Lake Waterman, Battery, and others) and deep industry experience, Tealium has the financial backing, profitability, and expertise to continue to outpace competitors and lead the way in innovation. Today, Tealium holds over 50 patents, and a few of the recent industry recognitions include:
- A Leader in the 2025 Gartner® Magic Quadrant™ for Customer Data Platforms
- 2025 TrustRadius Award Winner: Buyer’s Choice
- 2024 Invoca Partner Collaboration Award
- 2024 G2 Leader in Tag Management \& Enterprise Data Governance
- Tealium Customer Data Hub achieved the Top Rated Award by TrustRadius (2024\)
- Named on Destination CRM’s 2024 Top 100 Technologies List for Sales
- Named on the 2024 Best and Brightest in the Nation list
- BuiltIn’s 2024 Best Place to Work
WHAT WE ARE LOOKING FOR
Tealium is seeking a Senior Engineer, AI Developer Tools, to contribute to the vision, design, and rollout of our next\-generation AI\-driven developer tools. This is a high\-impact role at the core of a strategic initiative to modernize Tealium’s engineering ecosystem, enabling teams with intelligent, automated, and scalable tooling.
In this role, you will directly empower Tealium’s development teams to innovate faster, enhance code quality, and dramatically increase engineering productivity through AI. This is a unique opportunity to lead a critical strategic initiative, influence technical direction, and help teams adopt AI\-forward development practices in a measurable, practical way across the engineering organization.
As the driving force behind AI Developer Tools, your work will accelerate both engineering and business velocity by:
- Accelerating Product Modernization, Engineering Velocity and Quality: Designing, building, and owning internal AI\-driven developer platforms and tools (such as code review, test generation, migration automation, and CI/CD copilots) to achieve measurable improvements in engineering productivity and code quality.
- This role involves defining evaluation frameworks, orchestration, and governance (guardrails) for integrating AI safely into the developer workflow to tackle technical debt and accelerate modernization initiatives (e.g., AWS SDK migrations, Java 21 upgrades).
This role is perfect for a visionary technologist passionate about leveraging AI to redefine developer productivity and shape the future of engineering at Tealium.
YOUR DAY TO DAY
- Drive AI\-Powered Refactoring of Monolithic Platform Components: Spearhead initiatives to break up legacy systems, streamline architecture, and reduce production incidents, accelerating modernization across Tealium’s platform.
- Design and Implement AI\-Enhanced Code Review and Test Automation: Develop automated unit tests, improve test coverage, and eliminate manual QA bottlenecks, to enable faster, higher\-quality releases.
- Lead Measurement and Adoption of AI Tools: Establish AI scorecards, adoption KPIs, and metrics to track reductions in time\-to\-market, engineering efficiency improvements, and code quality gains (e.g., tickets closed per release, bug rates, code review cycle times), providing actionable insights to R\&D leadership.
- Evaluate and integrate best\-in\-class AI technologies, from code generation to test automation, to create a seamless and efficient engineering experience.
- Establish and scale repeatable AI\-assisted development workflows, standards, and reusable patterns across the R\&D organization, with a focus on reducing bottlenecks and improving delivery speed and quality.
- Serve as a technical authority and thought leader across the engineering org, promoting best practices and influencing decisions at all levels with a strong sense of ownership.
- Drive large\-scale modernization initiatives, partnering with other senior engineers to ensure adoption, scalability, and measurable impact.
- Stay current with emerging AI and developer productivity trends, continuously pushing the boundaries of what’s possible within our platform.
- Articulate technical vision and strategic decisions to senior stakeholders and leadership across engineering, serving as the connective tissue for cross\-functional initiatives.
- Drive multi\-week implementations of AI\-powered developer tools, ensuring successful delivery and integration.
WHAT YOU BRING TO TEALIUM
- 5\+ years of software engineering experience, with at least 3 years leading large\-scale internal tooling, platform engineering, or modernization efforts.
- Proven success designing and delivering AI\-powered developer tools—beyond experimentation—with real\-world measurable impact on team velocity and quality.
- Deep understanding of modern software development practices, languages, and environments (e.g., Java, TypeScript, CI/CD, cloud infrastructure).
- Experience using strategic thinking to drive solutions for complex, undefined problems within enterprise\-scale engineering organizations, directly enabling large\-scale AI strategies.
- Strong architecture and system design skills, with the ability to make build\-vs\-buy decisions and scale tooling across orgs.
- Demonstrated ability to influence with authority, collaborate across disciplines, and lead by example in a senior or principal engineering capacity.
- Exceptional cross\-functional communication skills, including the ability to clearly present complex technical concepts and translate engineering efforts into business value for senior management and non\-technical partners.
- A passion for improving the developer experience and a practical mindset toward applying AI to solve real engineering problems.
- Experience evaluating AI tools and models across critical dimensions, including quality, cost, latency, security, and workflow fit.
- Familiarity with tools like Claude Code, GitHub Copilot, AWS Q, or other generative AI platforms—ideally with experience leading their adoption at scale.
- Experience applying AI/automation to software development workflows (such as code review, test generation, migration acceleration, developer assistance, or release automation) with measurable improvements in speed, quality, or reliability.
WAGE TRANSPARENCY
In many U.S. states, employers are required to include a pay range for posted positions. Although this isn't a requirement in every state, communicating transparently is a cornerstone of our operations at Tealium, and we believe in making this information available to all applicants.
The U.S. pay range for this full\-time position is listed below, however, base pay offered may vary depending on job\-related knowledge, skills, and experience. In addition to a competitive base salary, this position is eligible for a robust benefits package that includes the following:
- Employees are eligible to receive an annual bonus and stock options.
- Employees and their families are eligible for medical, dental, vision, life, and disability insurance.
- Employees have the option to enroll in our 401k plan and are eligible to receive contributions for company matching.
- Employees are eligible for flexible paid time\-off and extended paid parental leave.
- We offer 11 paid holidays annually with an additional Healium Be\-Well break for most employees.
- We offer 15 hours of paid work time for volunteer activities and programs.
- Our sick leave accrual is the following for our employees:
+ Exempt CA employees (not including San Francisco) including NY : accrue 40 hours each year. Unused sick leave carries over into the next year. Employees cannot exceed 80 hours in a given year.
+ Exempt Non \- CA employees (not including NY) including SF: Accrue 1 hour every 30 hours worked. Cannot exceed 180 hours in the calendar year.
+ Non\-Exempt: accrue 1 hour every 30 hours worked. Unused carries over to the next year. Not to exceed 108 hours in a calendar year.
An overview of our benefits and perks can be found on our careers page, https://tealium.com/careers/ . Additional details regarding the benefits package will be provided during your interview process.
Compensation Range\- $145,000\- $185,000 \+ Variable \+ Equity Options
\#LI\-KK1
WHY YOU WANT TO WORK HERE
At Tealium, we don’t just offer the ordinary, we provide the extraordinary:
- Tealium WOWs (Ways of Work) , our award winning culture is how with think, act and connect together at Tealium
- Mosaic , our commitment to diversity, equity and inclusion is grounded in our mosaic of diverse perspectives and shared belonging as we live in work across the US and in nearly 20 countries
- Tealium Cares , to promote caring in our communities, 15 hours of paid work time for volunteer activities and programs is offered annually
- Tealium Connects (remote\-first working) , enabling many of us to choose where we do our best work and offering new hire stipends to assist with purchasing things we need to support a successful home office environment
- Tealium Ownership , share in the success of Tealium by becoming an owner of Tealium beginning with new hire equity grants
- Tealium Time , paid time\-off policy to offer flexibility to take time when needed and robust leave programs, including extended paid parental leave and company holidays
- Healium , health and wellness programs to help us be our best selves in the experiences of health, physical, mental, social, and even financial well\-being and wellness
- Tealium LIFT (Learning is Facilitated at Tealium) , offering a myriad of professional development opportunities with over 6,000 courses available on demand to best\-in\-class manager and leadership development programs
- Health and Related Benefits Programs , offering market competitive benefits programs
Collectively, we contribute our individual pieces (identity, experiences, heritage, backgrounds, religions, viewpoints, gender and more ) to form the mosaic of Team Tealium. It is our continuing philosophy to recruit and employ the best qualified individuals without regard to race, color, sex, religion, national origin, disability, age, sexual orientation, gender identity, and/or any other protected characteristic. Tealium does not tolerate unlawful discrimination of any kind and strives to be an inclusive and respectful workplace.
The highly relevant and differentiated positioning of Tealium’s solutions makes this a unique and rewarding career opportunity.
- Offerings vary by level and location.
Salary Context
This $145K-$185K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 1937 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At Tealium, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $181,170 based on 12,692 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($165K) sits 9% below the category median. Disclosed range: $145K to $185K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Tealium AI Hiring
Tealium has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $185K - $185K.
Remote Work Context
Remote AI roles pay a median of $170,000 across 1,926 positions. About 15% of all AI roles offer remote work.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, 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 $275,000 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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