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Lead Software Engineer- Gen AI, NLP, ML

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Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting

Lead Software Engineer – Generative and Agentic AI will design and develop algorithms and AI applications that support our Consulting & Insights Technology strategy, with a focus on generative AI and agentic AI.

  • Design and build LLM, NLP and RAG-based AI solutions for knowledge retrieval and summarization

  • Design agent architectures with planning, tool use, memory and multi-step reasoning

  • Build evaluation frameworks to measure LLM and agent accuracy, groundedness, safety, latency and cost

  • Design AI guardrails and hallucination mitigation with security and platform teams

  • Lead technical discussions and mentor team members on AI best practices

From the employer’s posting
Lead Software Engineer – Generative and Agentic AI will design and develop algorithms and AI applications that support our Consulting & Insights Technology strategy, with a focus on generative AI and agentic AI.
Design and develop algorithms and AI solutions using LLMs, NLP, deep learning, generative AI, information retrieval
Design agent architectures, including planning, tool use, memory, orchestration, multi-step reasoning
Build evaluation frameworks and benchmarks to assess LLM and agent performance
Design AI-focused guardrails and mitigation approaches
Lead technical discussions and mentor team members on algorithms, modeling approaches, experimentation, and AI best practices

What you’ll bring

All qualifications

Core experience

  • 6–8 years of professional experience in applied AI/ML, data science, machine learning, algorithms, statistics, or a related technical field, including hands-on experience developing and evaluating AI solutions using NLP, deep learning, LLMs, retrieval, and agentic AI.
  • Hands-on experience developing and evaluating machine learning and NLP solutions, including transformer architectures, deep learning, embeddings, information retrieval, classification, ranking, summarization, question answering, and agent decision-making.
  • Experience working with LLMs and foundation models, such as OpenAI, Anthropic, Cohere, Llama, or equivalent technologies.
  • Experience building generative AI and agentic AI solutions using technologies such as LangChain, LangGraph, RAG, prompt engineering, MCP, or equivalent frameworks.
  • Experience evaluating LLM and agent performance across accuracy, relevance, groundedness, helpfulness, safety, latency, and cost.
  • Experience designing AI-focused guardrails and applying responsible AI practices, including hallucination mitigation, output validation, policy adherence, and human oversight.
Qualification wording
6–8 years of professional experience in applied AI/ML, data science, machine learning, algorithms, statistics, or a related technical field, including hands-on experience developing and evaluating AI solutions using NLP, deep learning, LLMs, retrieval, and agentic AI.
Hands-on experience developing and evaluating machine learning and NLP solutions, including transformer architectures, deep learning, embeddings, information retrieval, classification, ranking, summarization, question answering, and agent decision-making.
Experience working with LLMs and foundation models, such as OpenAI, Anthropic, Cohere, Llama, or equivalent technologies.
Experience building generative AI and agentic AI solutions using technologies such as LangChain, LangGraph, RAG, prompt engineering, MCP, or equivalent frameworks.
Experience evaluating LLM and agent performance across accuracy, relevance, groundedness, helpfulness, safety, latency, and cost.
Experience designing AI-focused guardrails and applying responsible AI practices, including hallucination mitigation, output validation, policy adherence, and human oversight.
Education & alternatives
Must Have - A bachelor’s or master’s degree in Engineering, Data Science, Computer Science, or a related field is required. - Hands-on experience developing and evaluating machine learning and NLP solutions, including transformer architectures, deep learning, embeddings, information retrieval, classification, ranking, summarization, question answering, and agent decision-making.
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Actively hiringFirst seen by us 12 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 26, 202612 days ago
Recorded sightings
18
Last seen by us
Nov 8, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 12

Similar jobs usually come down between day 7 and day 71.

At Gartner, jobs usually come down by about day 39.

From 4,682 similar postings that came down, and 102 of Gartner’s. Coming down is not always a hire.

Gartner is hiring

15 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down at a usual pace
Hiring record

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About Gartner

People
About 20,244 in 2025, down 4% from the year before.Annual report (SEC Form 10-K)
Company
Listed as IT.
H-1B visas
14 approved for new hires in fiscal 2025.US Citizenship and Immigration Services

Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 624, the most 1,094, and the latest week had 868.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

About this role:

Lead Software Engineer – Generative and Agentic AI will design and develop algorithms and AI applications that support our Consulting & Insights Technology strategy, with a focus on generative AI and agentic AI.


What You’ll Do:

  • Design and develop algorithms and AI solutions using LLMs, NLP, deep learning, generative AI, information retrieval, and feedback-based techniques for agentic AI, knowledge retrieval, summarization, RAG, and related applications.
  • Design agent architectures, including planning, tool use, memory, orchestration, multi-step reasoning, feedback loops, and execution control.
  • Develop data-processing and representation techniques that transform unstructured text and other data into structured formats for modeling, retrieval, and analysis.
  • Build evaluation frameworks and benchmarks to assess LLM and agent performance across accuracy, relevance, groundedness, helpfulness, safety, latency, and cost.
  • Optimize model performance through prompt engineering, retrieval optimization, reranking, embedding techniques, model selection, and fine-tuning.
  • Design AI-focused guardrails and mitigation approaches, including input and output validation, hallucination mitigation, policy adherence, responsible AI practices, and human-in-the-loop review, in collaboration with security and platform teams.
  • Apply NLP, machine learning, statistical analysis, and information retrieval techniques to identify patterns, relationships, and insights in complex data.
  • Translate business requirements into applied AI approaches, algorithm designs, experiments, and measurable outcomes.
  • Stay current with emerging LLM architectures, foundation models, agent frameworks, retrieval techniques, and AI research.
  • Lead technical discussions and mentor team members on algorithms, modeling approaches, experimentation, and AI best practices.

What You’ll Need:

6–8 years of professional experience in applied AI/ML, data science, machine learning, algorithms, statistics, or a related technical field, including hands-on experience developing and evaluating AI solutions using NLP, deep learning, LLMs, retrieval, and agentic AI.


Must Have

  • A bachelor’s or master’s degree in Engineering, Data Science, Computer Science, or a related field is required.
  • Hands-on experience developing and evaluating machine learning and NLP solutions, including transformer architectures, deep learning, embeddings, information retrieval, classification, ranking, summarization, question answering, and agent decision-making.
  • Experience working with LLMs and foundation models, such as OpenAI, Anthropic, Cohere, Llama, or equivalent technologies.
  • Experience building generative AI and agentic AI solutions using technologies such as LangChain, LangGraph, RAG, prompt engineering, MCP, or equivalent frameworks.
  • Experience evaluating LLM and agent performance across accuracy, relevance, groundedness, helpfulness, safety, latency, and cost.
  • Experience designing AI-focused guardrails and applying responsible AI practices, including hallucination mitigation, output validation, policy adherence, and human oversight.
  • Demonstrated ability to identify emerging AI technologies and apply them to meaningful business use cases.
  • Strong communication and collaboration skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.

Who You Are:

  • You are passionate about applying AI and machine learning to solve complex business problems.
  • You combine strong technical depth in algorithms, NLP, LLMs, retrieval, and agentic AI with practical business judgment.
  • You can explain complex AI concepts clearly to technical and non-technical stakeholders.
  • You take ownership of your work and collaborate effectively with product, data science, engineering, cloud, security, and platform teams.
  • You are comfortable working through ambiguity and delivering solutions through short, iterative Agile development cycles.
  • You are curious about emerging AI technologies and motivated to evaluate their practical business applications.

Don’t meet every single requirement? We encourage you to apply anyway. You might just be the right candidate for this, or other roles.

#LI-JJ3

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.


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 ApplicantAccommodations@gartner.com.

Job Requisition ID:113314

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Gartner Applicant Privacy Link: https://jobs.gartner.com/applicant-privacy-policy


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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.
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Ready to grow your career with Gartner? Join us. 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 ApplicantAccommodations@gartner.com.

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