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*This is an individual contributor opportunity, based remotely in North America.*
About the role:
Gartner Analysts are industry thought leaders who create must\-have insights, market predictions and best practices for a broad range of world\-leading organizations. A Senior Director serves as a leader within Gartner’s Business and Technology Insights (BTI) group, establishing oneself as a credible voice within their designated market at local, regional and global levels. Utilizing exceptional research and analytical skills, a Senior Director plays a significant role in producing pragmatic and provocative insights which Gartner clients consume and apply to propel their business toward key objectives. They are a trusted source of advice for clients, reinforcing Gartner’s value every day by engaging them via in\-person meetings, virtual meetings, sales support visits and Gartner conferences to discuss complex client challenges and offer appropriate recommendations. This role sits within Gartner’s Software Engineering Practice and advises leaders of software engineering organizations around the world. The focus is on helping organizations develop and scale the next generation of software applications—particularly AI\-powered applications and AI agent\-based systems. The role provides strategic guidance on how to build, manage and operate these applications to enable organizations to successfully adopt and leverage advanced AI capabilities.
What you will do:
- Create innovative, thought provoking, and highly leveraged “must\-have insights” content
- Develop new insights and ideas through thought leadership and offer compelling, actionable approaches to client's needs and requests that accelerate the client's ability to act
- Develop in\-depth analysis to identify the root cause of a client’s barriers or overall needs and reframe thinking to drive strategy forward
- Demonstrate thought leadership in establishing Insights positions across a team of analysts
- Bring provocative, independent insights to Gartner leaders that can evolve the course of a research agenda
- Research, analyze and predict market trends and shifts to provide clients and vendors with actionable insights
- Provide clients and prospects with actionable advice aligned to their designated content area via virtual or face\-to\-face interactions
- Create and deliver high value presentation materials on and off stage for Gartner events, industry and professional association conferences, and client briefings
- Support BTI and Sales: Provide sales support serving as voice of the market to help Insights teams create content and to drive engagement with clients to make progress against their critical priorities to grow their business
- Provide high quality and timely content peer review
- Build credibility as an industry expert to represent Gartner insights, methodology and strategy
- Actively participate in innovation, ideation, and research discussions and collaborate effectively with peers in the Insights community
- Identify research process improvements or develop new processes that help the team and BTI provide excellent service delivery
- Be a mentor and a coach by supporting more junior team members
- Be client\-centric while actively seeking to help clients engage regularly and often with Gartner insights and interactions
What you will need:
- Bachelor's degree or equivalent experience; Graduate degree preferred
- 12\+ years of relevant field or industry experience
- Experience leading teams in the design, development, and deployment of AI\-native applications, including applications powered by large language models (LLMs) and AI agent architectures.
- Deep knowledge and practical experience of agentic AI frameworks, orchestration platforms, model providers, and emerging patterns for building autonomous and semi\-autonomous AI systems.
- Practical knowledge and experience of AI application architectures, including model integration, context management, harnesses, evaluation frameworks, observability, and the management of applications in production
- Knowledge of the leading vendors and platforms in the AI application and agentic AI development ecosystem, with the ability to identify their benefits, limitations, risks, and appropriate use cases.
- Demonstrate executive presence; can immediately establish credibility with executives and additional stakeholders
- Strong organizational skills; ability to work under tight deadlines and produce high quality deliverables
- Demonstrate excellence in research and writing ability
- Strong written and verbal proficiency, analytical and presentation skills; ability to engage clients and respond effectively to questions
- Proficient in analyzing and synthesizing data; can effectively apply critical thinking concepts while drawing and defending conclusions to client challenges
- Strong communication skills \- able to explain complex concepts concisely and simply
- Track record of presenting at large and small\-scale speaking engagements
- Strong business and financial acumen
- Deep knowledge of the global and competitive landscape within subject area as well as the interplay in that market
- Ability to work independently, while also being intrinsically motivated to collaborate across teams and support the workflow of others, in a multicultural global team
- Ability to represent Gartner's research methodology and strategies effectively at all levels
- Willingness and ability to travel up to 25% (where applicable)
\#LI\-Remote
\#LI\-LE2
Who are we?
At Gartner, Inc. (NYSE:IT), we guide the leaders who shape the world.
Our mission relies on expert analysis and bold ideas to deliver actionable, objective business and technology insights, helping enterprise leaders and their teams succeed with their mission\-critical priorities.
Since our founding in 1979, we’ve grown to 20,000 associates globally who support over 13,000 client enterprises in \~90 countries and territories. We do important, interesting and substantive work that matters. That’s why we hire associates with the intellectual curiosity, energy and drive to want to make a difference. The bar is unapologetically high. So is the impact you can have here.
What makes Gartner a great place to work?
Our vast, virtually untapped market potential offers limitless opportunities – opportunities that may not even exist right now – for you to grow professionally and flourish personally. How far you go is driven by your passion and performance.
We hire remarkable people who collaborate and win as a team. Together, our singular, unifying goal is to deliver results for our clients.
Our teams are inclusive and composed of individuals from different geographies, cultures, religions, ethnicities, races, genders, sexual orientations, abilities and generations.
We invest in great leaders who bring out the best in you and the company, enabling us to multiply our impact and results. This is why, year after year, we are recognized worldwide as a great place to work.
Gartner is the world authority on AI
At Gartner, you’ll join a company at the very center of the AI revolution. Gartner has proactive, objective guidance throughout clients’ AI journeys. We set the standard for how organizations leverage artificial intelligence to drive meaningful impact. You’ll have access to unmatched resources, expertise, and technology, and play a key role in helping Gartner and our clients innovate and grow as we leverage AI to transform business and technology landscapes.
It’s an exciting time to be at Gartner, with limitless opportunities to make a real impact, grow your skills, and build a lasting, meaningful career in a field that’s reshaping the way we operate. If you’re passionate about AI and want to be part of a team that’s guiding the leaders who shape the world, Gartner is the place for you.
What do we offer?
Gartner offers world\-class benefits, highly competitive compensation and disproportionate rewards for top performers.
In our hybrid work environment, we provide the flexibility and support for you to thrive — working virtually when it's productive to do so and getting together with colleagues in a vibrant community that is purposeful, engaging and inspiring.
Ready to grow your career with Gartner? Join us.
Gartner believes in fair and equitable pay. A reasonable estimate of the base salary range for this role is 172,000 USD \- 202,500 USD. Please note that actual salaries may vary within the range, or be above or below the range, based on factors including, but not limited to, education, training, experience, professional achievement, business need, and location. In addition to base salary, employees will participate in either an annual bonus plan based on company and individual performance, or a role\-based, uncapped sales incentive plan. Our talent acquisition team will provide the specific opportunity on our bonus or incentive programs to eligible candidates. We also offer market leading benefit programs including generous PTO, a 401k match up to $7,200 per year, the opportunity to purchase company stock at a discount, and more.
The policy of Gartner is to provide equal employment opportunities to all applicants and employees without regard to race, color, creed, religion, sex, sexual orientation, gender identity, marital status, citizenship status, age, national origin, ancestry, disability, veteran status, or any other legally protected status and to seek to advance the principles of equal employment opportunity.
Gartner is committed to being an Equal Opportunity Employer and offers opportunities to all job seekers, including job seekers with disabilities. If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to use or access the Company’s career webpage as a result of your disability. You may request reasonable accommodations by calling Human Resources at \+1 (203\) 964\-0096 or by sending an email to [email protected] .
Job Requisition ID:112559
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Salary Context
This $172K-$202K range is above the median for AI Software Engineer roles in our dataset (median: $185K across 231 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 4,317 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Gartner, 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 in Demand for This Role
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 $218,500 based on 729 positions with disclosed compensation. Director-level AI roles across all categories have a median of $274,554. This role's midpoint ($187K) sits 14% below the category median. Disclosed range: $172K to $202K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Gartner AI Hiring
Gartner has 4 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer. Positions span Chicago, IL, US, TX, US, Remote, US. Compensation range: $133K - $202K.
Remote Work Context
Remote AI roles pay a median of $180,000 across 1,196 positions. About 15% of all AI roles offer remote work.
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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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