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Technology Consultant - Data & AI

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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
  • Architect and deliver enterprise Data, GenAI, and Agentic AI solutions

  • Build AI agents, multi-agent workflows, and RAG grounding patterns

  • Engineer data platforms on Azure, Microsoft Fabric, and Azure AI

  • Move solutions from prototype to secure, reliable production

  • Lead technical workshops and co-development with customer teams

From the employer’s posting
Architect and deliver enterprise-scale Data, Generative AI, and Agentic AI solutions
Design and implement AI agents, multi-agent workflows, reusable skills, tool integrations, RAG, grounding, and orchestration patterns.
Design and implement data engineering, analytics, lakehouse, search, knowledge, and AI architectures using Microsoft Azure, Microsoft Fabric, Azure AI, and related technologies.
Move solutions from prototype to production with appropriate security, Responsible AI, observability, evaluation, reliability, performance, and cost controls.
Lead technical workshops, architecture discussions, design reviews, and co-development with customer architects and engineering teams.
Education & alternatives
Qualifications Required/Minimum Qualifications - Bachelor's degree in Computer Science, Engineering, Data Science, Information Technology, Business, or a related field AND 6+ years of relevant technical consulting, architecture, engineering, Data & AI, or technology delivery experience, OR equivalent experience. - Experience designing and delivering enterprise Data, Analytics, AI, Generative AI, or cloud solutions.
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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

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Nov 4, 2026today
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Microsoft is hiring

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Where the posting names them
- Experience designing or developing AI agents and Agentic AI solutions, including tool/function calling, grounding, skills, workflows, orchestration, and evaluation. - Strong programming and engineering experience using Python and/or modern development languages, APIs, Git, CI/CD, and cloud-native development practices. - Experience taking technical solutions from architecture and prototype through secure, scalable production deployment.
- Build Agentic AI solutions: Design and implement AI agents, multi-agent workflows, reusable skills, tool integrations, RAG, grounding, and orchestration patterns. - Engineer modern data platforms: Design and implement data engineering, analytics, lakehouse, search, knowledge, and AI architectures using Microsoft Azure, Microsoft Fabric, Azure AI, and related technologies. - Drive production readiness: Move solutions from prototype to production with appropriate security, Responsible AI, observability, evaluation, reliability, performance, and cost controls.
- 12+ years of relevant technology, consulting, architecture, engineering, Data & AI, or solution delivery experience. - Deep experience with modern cloud and Data & AI technologies such as Microsoft Azure, Microsoft Fabric, Azure AI, Azure OpenAI, Azure AI Search, and/or Databricks. - Experience delivering enterprise-scale Generative AI or Agentic AI solutions, including multi-agent architectures, enterprise knowledge solutions, or intelligent process automation.
- Understanding of Responsible AI, AI security, identity, data governance, privacy, observability, and enterprise compliance. - Relevant technical certifications aligned to the solution area, such as Azure, Data, AI, Security, or cloud architecture certifications. - Delivery or engineering methodology certifications such as Agile, Scrum, DevOps, Change Management, or Project Management are advantageous.

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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 ↗

Overview

Microsoft Industry Solutions Delivery brings together strategic sellers, industry and security experts, engineers, data scientists, architects, consultants, and delivery specialists to help Microsoft’s most strategic customers solve complex business challenges. Together with our partners, we deliver industry-specific solutions that accelerate customers’ digital and AI transformation using Microsoft Cloud and AI.

As a Technology Consultant – Data & AI, you will help enterprise customers design, build, and operationalize modern Data, Generative AI, and Agentic AI solutions. You will combine deep technical expertise, architecture, hands-on engineering, and customer consulting to translate complex business challenges into secure, scalable, and production-ready solutions.

You will lead complex technical workstreams and collaborate with customer teams to build modern data platforms, AI-powered applications, and enterprise agents. You will apply AI-native engineering practices, including agents, reusable skills, copilots, orchestration, retrieval-augmented generation (RAG), and modern Data & AI platforms to accelerate solution delivery and business value.

As an experienced individual contributor, you will provide technical leadership across the solution lifecycle, from architecture and design through implementation, productionization, optimization, and adoption. You will mentor technical professionals, influence engineering decisions, and develop reusable solutions, patterns, and practices that scale impact across customers.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. We come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. We build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.



Responsibilities
  • Lead Data & AI solutions: Architect and deliver enterprise-scale Data, Generative AI, and Agentic AI solutions that address complex business and technology challenges.
  • Build Agentic AI solutions: Design and implement AI agents, multi-agent workflows, reusable skills, tool integrations, RAG, grounding, and orchestration patterns.
  • Engineer modern data platforms: Design and implement data engineering, analytics, lakehouse, search, knowledge, and AI architectures using Microsoft Azure, Microsoft Fabric, Azure AI, and related technologies.
  • Drive production readiness: Move solutions from prototype to production with appropriate security, Responsible AI, observability, evaluation, reliability, performance, and cost controls.
  • Apply AI-native engineering: Use copilots, agents, automation, DevOps, MLOps, and GenAIOps practices to accelerate engineering and customer delivery.
  • Partner with customers: Lead technical workshops, architecture discussions, design reviews, and co-development with customer architects and engineering teams.
  • Provide technical leadership: Influence architecture and engineering decisions, solve complex technical challenges, mentor technical professionals, and establish engineering practices.
  • Scale impact: Develop reusable architectures, accelerators, agent skills, engineering patterns, and intellectual property that can be applied across customer engagements.


Qualifications

Required/Minimum Qualifications

  • Bachelor's degree in Computer Science, Engineering, Data Science, Information Technology, Business, or a related field AND 6+ years of relevant technical consulting, architecture, engineering, Data & AI, or technology delivery experience, OR equivalent experience.
  • Experience designing and delivering enterprise Data, Analytics, AI, Generative AI, or cloud solutions.
  • Hands-on experience with modern Data & AI architectures, including data engineering, analytics, lakehouse, RAG, semantic/vector search, machine learning, and Generative AI.
  • Experience designing or developing AI agents and Agentic AI solutions, including tool/function calling, grounding, skills, workflows, orchestration, and evaluation.
  • Strong programming and engineering experience using Python and/or modern development languages, APIs, Git, CI/CD, and cloud-native development practices.
  • Experience taking technical solutions from architecture and prototype through secure, scalable production deployment.
  • Strong customer-facing consulting, problem-solving, communication, and stakeholder-management skills, with the ability to independently lead complex technical workstreams.

Additional or Preferred Qualifications

  • 12+ years of relevant technology, consulting, architecture, engineering, Data & AI, or solution delivery experience.
  • Deep experience with modern cloud and Data & AI technologies such as Microsoft Azure, Microsoft Fabric, Azure AI, Azure OpenAI, Azure AI Search, and/or Databricks.
  • Experience delivering enterprise-scale Generative AI or Agentic AI solutions, including multi-agent architectures, enterprise knowledge solutions, or intelligent process automation.
  • Experience leading customer co-development and engineering engagements and influencing architecture and technology decisions.
  • Understanding of Responsible AI, AI security, identity, data governance, privacy, observability, and enterprise compliance.
  • Relevant technical certifications aligned to the solution area, such as Azure, Data, AI, Security, or cloud architecture certifications.
  • Delivery or engineering methodology certifications such as Agile, Scrum, DevOps, Change Management, or Project Management are advantageous.
  • Demonstrated ability to mentor technical professionals and create reusable reference architectures, accelerators, agent skills, and engineering patterns.

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.



Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

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Work authorization
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

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