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About This Role
Job Description
Introduction
As the AI Research Lead for the Office of the Chief Technology Officer, you will lead end\-to\-end research programs that combine industrial\-organizational psychology, data science, and real\-world insights to uncover how individuals, teams, and organizations adapt and thrive.
You will lead end to end research programs that connect individuals, teams, and organizations as we go forward in the Human\+ world.
You will scope research with executives and clients, design and validate measurement instruments, work with complex datasets, and translate findings into clear narratives, metrics, and decision frameworks. You will develop junior researchers, collaborate with cross functional technical and business teams, and represent Avanade in both internal and external forums.
At Avanade, research isn't an ivory tower exercise, it's a client\-facing capability that drives business decisions and has measurable outcomes. You'll work at the pace of consulting, balancing rigor with pragmatism, and translating complex analyses into frameworks that clients can act on and learn from. Your work will directly influence client strategy, product roadmaps, and organizational transformation.
Come Join us
At Avanade, the Research team is focused currently on the future of Human\+. For this role you:
- Are passionate about understanding how AI, digital ecosystems, and organizational systems shape work, performance, and well being.
- Work out in the open, using transparent, reproducible methods, sharing code, frameworks, and insights, and inviting challenge and collaboration.
- Are committed to growth, continuously building new skills in data science, organizational research, and AI, and developing the next generation of researchers.
- Have a bias for evidence backed action, using data, experiments, and people metrics to guide decisions, not hype or assumptions.
- Are hypothesis driven, grounding each project in clear questions about how technology, people, and organizations interact, and testing them rigorously.
The Office of the CTO helps Avanade and its clients understand how AI and emerging technologies reshape work, skills, and organizational design. Through applied research, experimentation, and deep collaboration with product, engineering, and business teams, we generate insights, measurement frameworks, and playbooks that drive smarter workforce and technology decisions. Our team is dedicated to strong scientific rigor and analytics that connect people and technology.
What you’ll do:
Design and Execute Research Projects:
- Design and run research projects from scoping through analysis and insight generation, using mixed methods including surveys, interviews, experiments, and behavioral data analysis
- Develop and validate measurement instruments (scales, surveys, indices) with appropriate reliability and validity testing
- Apply rigorous quantitative methods—regression, multilevel models, factor analysis, experimental and quasi\-experimental designs—to understand how AI and digital tools impact work outcomes
- Document methods, assumptions, and limitations transparently using reproducible, open approaches
Investigate AI's Impact on Work:
- Explore how AI, automation, and digital ecosystems change jobs, skills, workflows, collaboration patterns, and team dynamics
- Analyze datasets including surveys, people analytics, collaboration data, and product usage data to generate evidence\-backed insights
- Partner with engineering, product, and architecture teams to define what to measure, how to instrument systems, and how to evaluate impact
- Separate meaningful effects from hype using robust research design and critical analysis
Translate Data into Action and Thought Leadership:
- Build clear, executive\-ready data visualizations and dashboards using Power BI or Python/R libraries that enable leaders to monitor workforce and AI\-related metrics
- Apply best practices in psychometrics, data storytelling, and visual design so insights are interpretable and actionable for non\-technical audiences
- Develop client\-ready deliverables including white papers, executive briefings, and implementation frameworks that balance analytical rigor with clear business recommendations
- Develop executive briefs, slide narratives, and client one\-pagers tailored to senior stakeholders
- Lead project workstreams within client engagements, facilitating workshops, and building client confidence in research\-driven recommendations
Develop Talent and Build Assets:
- Mentor junior researchers and analysts, coaching them in research design, coding, analytics, visualization, and stakeholder engagement
- Contribute to shared research assets such as survey libraries, scale repositories, analysis templates, and visualization standards
Foster a collaborative and growth\-oriented culture where strong ideas are debated constructively
Qualification
Skills and experiences:
Education:
- PhD strongly preferred, or Master’s degree, in Industrial Organizational Psychology, Organizational Behavior, Data Science, Quantitative Social Science, or a closely related field that combines people research and advanced analytics.
Experience:
- 3\+ years of applied research experience in industry, technology, consulting, or a similar environment conducting data\-intensive, multi\-stakeholder studies
- Proven ability to design and deliver workforce or organization\-focused research using mixed methods (quantitative and qualitative)
- Experience working with or alongside technology and product teams, ideally with exposure to AI\-enabled tools or digital collaboration environments
- Proven ability to work under ambiguity and time pressure while maintaining methodological integrity with comfort presenting to and being challenged by senior executives or clients
- Consulting, client\-facing, or applied research experience strongly preferred
Research and Communication:
- Portfolio of research outputs such as reports, white papers, or analytical articles demonstrating depth and clear storytelling
- Ability to present complex findings to non\-research audiences, including senior leaders and clients
- Strong stakeholder management skills—you build trust and collaborate across disciplines.
Why Join us:
- Shape how Avanade and its clients navigate the future of work at the intersection of AI, people, and organizational design
- Work with autonomy on meaningful research questions with access to diverse data sources and cross\-functional partners
- Be part of a team that values transparent methods, evidence\-based decision\-making, and continuous learning
- Build your skills in advanced analytics, data storytelling, and strategic influence with clear growth opportunities
What Success looks like:
- Your research informs product, workforce, and technology decisions at Avanade and with clients
- Clients adopt your recommendations and see measurable business outcomes
- Your research generates follow\-on engagements or expands existing client relationships
- Stakeholders find your insights rigorous, usable, and clearly communicated
- Projects are delivered on time with appropriate methods and well\-documented limitations
- You build capability in junior team members and contribute to team infrastructure
Enjoy your career
Some of the best things about working at Avanade
- Opportunity to work for Microsoft’s Global Alliance Partner of the Year (14 years in a row), with exceptional development and training (minimum 80 hours per year for training and paid certifications)
- Real\-time access to technical and skilled resources globally
- Dedicated career advisor to encourage your growth
- Engaged and helpful co\-workers genuinely interested in you
A great place to work
As you bring your skills and abilities to Avanade, you’ll get distinctive experiences, limitless learning, and ambitious growth in return. As we continue to build our diverse and inclusive culture, we become even more innovative and creative, helping us better serve our clients and communities. You’ll join a community of smart, supportive collaborators to lift, mentor, and guide you, and to lean on your expertise. You get a company purpose\-built for business\-critical, leading\-edge technology solutions, committed to improving the way humans work, interact, and live. It’s all here, so take a closer look!
We work hard to provide an inclusive, diverse culture with a deep sense of belonging for all our employees. Visit our Inclusion \& Diversity page.
Create a future for our people that focuses on
- Expanding your thinking • Experimenting courageously • Learning and pivoting
Inspire greatness in our people by
- Empowering every voice • Encouraging boldness • Celebrating progress
Accelerate the impact of our people by
- Amazing the client • Prioritizing what matters • Acting as one
Learn more
To learn more about the types of projects our Infrastructure team works on check out these case studies:
- VentilatorChallengeUK manufactures 20 years’ worth of ventilators in 12 weeks to help save lives
- Landmark Information Group finds a new home for its data in the cloud
Interested in knowing what’s going on inside Avanade? Check out our blogs:
- Avanade Insights – exchange ideas that drive tomorrow’s innovation
- Inside Avanade – explore what life is like working at Avanade
Compensation at Avanade varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience. As required by local law, Avanade provides a reasonable range of compensation for roles that may be hired as set forth below.
We anticipate this job posting will be posted on 3/6/2026 and open for at least 10 days.
Avanade offers a competitive suite of market benefits including medical, dental, vision, life, and long\-term disability coverage, a 401(k) plan, bonus opportunities, paid holidays, and paid time off.
See more information on our benefits here: U.S. Employee Benefits \| Avanade Role Location Annual Salary Range
California $155,000\- $185,000
Cleveland $140,000\- $165,000
Colorado $140,000\- $165,000
District of Columbia $155,000\- $185,000
Illinois $150,000\- $175,000
Maryland $155,000\- $185,000
Massachusetts $155,000\- $185,000
Minnesota $ 150,000\- $175,000
New York $165,000\- $195, 000
New Jersey $140,000\- $165,000
Washington $155,000\- $185,000
At Avanade, we are committed to ensure our people feel appreciated and empowered to succeed both personally and professionally.
Salary Context
This $140K-$185K range is above the median for AI/ML Engineer roles in our dataset (median: $100K across 15465 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 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Avanade, 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 $166,983 based on 13,781 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. Disclosed range: $140K to $185K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Avanade AI Hiring
Avanade has 4 open AI roles right now. They're hiring across AI Architect, AI/ML Engineer. Positions span Atlanta, GA, US, Seattle, WA, US, Chicago, IL, US. Compensation range: $184K - $230K.
Location Context
AI roles in Chicago pay a median of $202,350 across 310 tracked positions. That's 10% above the national median.
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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. 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: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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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