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About This Role
Durham, United States of America \| Full time \| Home\-based \| R1545329
AI/ML Architect, MediaOS Platform,IQVIA Digital
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We are seeking a visionary AI/ML Architect to define and lead the next generation of intelligent capabilities within our MediaOS Platform. This is a foundational leadership role, where you will shape the AI strategy, architecture, and execution roadmap from the ground up.
You will work closely with engineering, product, and data teams to embed advanced machine learning and AI\-driven decisioning into a scalable, high\-performance platform. This is a unique opportunity to influence both technical direction and business outcomes in a rapidly evolving domain.
Key Responsibilities
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- Architect and design end\-to\-end AI/ML solutions for the MediaOS platform, including:
+ Personalization and recommendation systems
+ Targeting and optimization models
+ Forecasting and advanced analytics
- Define and implement scalable ML pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring
- Lead the design of cloud\-native, distributed AI systems leveraging modern frameworks and high\-performance computing environments
- Partner with product, data engineering, and platform teams to translate business requirements into robust AI\-driven solutions
- Establish and enforce MLOps best practices, including CI/CD, model versioning, observability, governance, and lifecycle management
- Evaluate and integrate emerging AI technologies, including Generative AI, LLMs, and NLP applications where applicable
- Drive data strategy alignment, ensuring high\-quality, well\-governed datasets to support model development and scalability
- Mentor and guide engineers and data scientists, fostering a culture of innovation, collaboration, and technical excellence
- Architect secure AI platforms, including authentication and authorization models (e.g., RBAC, ABAC)
Required Qualifications
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- 8\+ years of experience in AI/ML, Data Science, or related fields
- Proven track record of designing and deploying production\-grade ML systems at scale
- Strong programming expertise in Python (preferred) and/or Java/Scala
- Hands\-on experience with ML frameworks such as TensorFlow, PyTorch, Scikit\-learn
- Deep understanding of data architecture, distributed systems, and cloud platforms (AWS, Azure, or GCP)
- Experience with real\-time and batch processing systems
- Strong knowledge of MLOps tools, frameworks, and lifecycle practices
- Experience designing secure AI systems, including authentication and authorization frameworks (RBAC, ABAC)
Preferred Qualifications
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- Experience in media, advertising, marketing analytics, or audience platforms
- Hands\-on experience with personalization, recommendation engines, or optimization models
- Familiarity with Generative AI, LLMs, and NLP applications
- Experience building data\-driven platforms or products
- Strong communication and stakeholder management skills, with the ability to influence both technical and business audiences
Why Join Us
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- Build from the ground up – Play a foundational role in shaping AI capabilities within MediaOS
- High\-impact role – Directly influence platform intelligence and customer outcomes
- Cutting\-edge technology – Work with modern AI/ML, data, and cloud ecosystems
- Flexible work environment – Fully remote with optional access to our Austin office
- Leadership opportunity – Partner closely with senior leadership and help scale future AI capabilities
About IQVIA Digital
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IQVIA Digital powers smarter healthcare engagement through advanced analytics, AI, and media solutions. Our platforms help life sciences organizations connect with healthcare professionals and patients more effectively through data\-driven insights and precision targeting.
To learn more about IQVIA Digital and its capabilities, visit:
Discover IQVIA Digital
About the Team
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You will report directly to the Head of Software Development Engineering and collaborate with a high\-performing, cross\-functional team focused on building a next\-generation media and data platform.
If you want, I can also optimize this for Workday posting (with job codes, compliance language, and EEO section) or create a short LinkedIn version for faster sourcing.
IQVIA is a leading global provider of clinical research services, commercial insights and healthcare intelligence to the life sciences and healthcare industries. We create intelligent connections to accelerate the development and commercialization of innovative medical treatments to help improve patient outcomes and population health worldwide. Learn more at https://jobs.iqvia.com
IQVIA is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other status protected by applicable law. https://jobs.iqvia.com/eoe
IQVIA is committed to integrity in our hiring process and maintains a zero tolerance policy for candidate fraud. All information and credentials submitted in your application must be truthful and complete. Any false statements, misrepresentations, or material omissions during the recruitment process will result in immediate disqualification of your application, or termination of employment if discovered later, in accordance with applicable law. We appreciate your honesty and professionalism.
The potential base pay range for this role, when annualized, is $103,300\.00 \- $287,600\.00\. The actual base pay offered may vary based on a number of factors including job\-related qualifications such as knowledge, skills, education, and experience; location; and/or schedule (full or part\-time). Dependent on the position offered, incentive plans, bonuses, and/or other forms of compensation may be offered, in addition to a range of health and welfare and/or other benefits.
Salary Context
This $103K-$287K range is above the median for AI Architect roles in our dataset (median: $172K across 30 roles with salary data).
Role Details
About This Role
This role sits at the intersection of AI and engineering, building systems that bring machine learning capabilities into production environments. The scope varies by company, but the common thread is applying AI technology to solve real business problems at scale. Most AI roles today require a combination of software engineering fundamentals and domain-specific ML knowledge, with the exact mix depending on the team's maturity and the product they're building.
The AI job market is evolving fast. New role categories emerge as companies figure out what they need to ship AI-powered products. What matters most is the ability to learn quickly, build working systems, and iterate based on real-world performance data. The specific title matters less than the skills you bring and the problems you can solve. Companies are past the experimentation phase and want engineers who can deliver production-quality systems that work reliably at scale.
Across the 4,133 AI roles we're tracking, AI Architect positions make up 1% of the market. At IQVIA, this role fits into their broader AI and engineering organization.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
What the Work Looks Like
Day-to-day work involves a mix of building, debugging, and collaborating. You'll write code, review pull requests, participate in design discussions, and work with cross-functional teams (product, design, data) to define what AI features should do and how they should behave. Expect to spend time on both technical implementation and communication. Most AI teams operate in two-week sprint cycles, with regular demos and retrospectives. The ratio of heads-down coding to meetings and reviews varies by seniority, with senior roles spending more time on architecture decisions and mentorship.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
Skills Required
Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.
Beyond the core stack, communication skills matter more than many technical candidates realize. The ability to explain AI capabilities and limitations to non-technical stakeholders is a differentiator at every level. Technical writing, documentation, and clear thinking about tradeoffs are underrated skills in AI roles. Experience with evaluation methodology (how to measure whether an AI system is working well) is becoming a core requirement, especially for roles that involve LLM integration.
Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
Compensation Benchmarks
AI Architect roles pay a median of $215,000 based on 115 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,778. This role's midpoint ($195K) sits 9% below the category median. Disclosed range: $103K to $287K.
Across all AI roles, the market median is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Safety ($274,200) and AI Engineering Manager ($268,700). By seniority level: Entry: $97,760; Mid: $165,778; Senior: $227,400; Director: $250,000; VP: $250,000.
IQVIA AI Hiring
IQVIA has 2 open AI roles right now. They're hiring across AI/ML Engineer, AI Architect. Based in Durham, NC, US. Compensation range: $270K - $287K.
Location Context
Across all AI roles, 14% (583 positions) offer remote work, while 3,532 require on-site attendance. Top AI hiring metros: New York (2,760 roles, $211,000 median); San Francisco (2,258 roles, $253,000 median); Los Angeles (1,841 roles, $195,000 median).
Career Path
Common paths into AI Architect roles include Software Engineer, Data Scientist, Data Analyst.
From here, career progression typically leads toward Senior Engineer, AI Architect, Engineering Manager, Principal Engineer.
Focus on building things that work. A deployed project that solves a real problem is worth more than any certification. Contribute to open-source, build portfolio projects, and invest in fundamentals (software engineering, statistics, systems design) rather than chasing the latest framework. The AI field moves fast, but the engineers who succeed long-term are the ones with strong fundamentals who can adapt to new tools and paradigms as they emerge.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
AI Hiring Overview
The AI job market has 4,133 open positions tracked in our dataset. By seniority: 106 entry-level, 1,901 mid-level, 1,663 senior, and 463 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (583 positions). The remaining 3,532 roles require on-site or hybrid attendance.
The market median for AI roles is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Safety ($274,200 median, 57 roles); AI Engineering Manager ($268,700 median, 42 roles); Research Engineer ($260,000 median, 442 roles).
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
The AI Job Market Today
The AI job market spans 4,133 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,865), Data Scientist (339), AI Software Engineer (313). 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 (106) are outnumbered by mid-level (1,901) and senior (1,663) 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 463 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (583 positions), with 3,532 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 $200,700. Top-quartile roles start at $254,000, 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 Safety roles lead at $274,200 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 (2,128 postings), Aws (1,324 postings), Azure (1,003 postings), Rag (916 postings), Gcp (817 postings), Pytorch (655 postings), Prompt Engineering (639 postings), Claude (571 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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