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Azure Ai Engineer Remote Jobs in Texas (NOW HIRING)

AI Engineer III

San Antonio, TX · On-site +1

$120K - $140K/yr

Azure AI Engineer Associate (AI-102) * Google Cloud Professional Machine Learning Engineer * NVIDIA AI/Deep Learning certification (e.g., NVIDIA Certified Associate: AI Infrastructure) * Databricks ...

AI Solutions Architect

Austin, TX · Remote

$160K - $210K/yr

... Azure AI Foundry at the center of the stack. You will create reusable patterns, shared services ... You will partner closely with engineering, product, infrastructure, and security teams to build ...

Lead Agentic AI Engineer

Austin, TX · Remote

$98K - $129K/yr

Remote, EST Time zone Role Overview We are looking for a Lead Agentic AI Engineer to drive the ... Oversee deployment, scalability, and performance on cloud platforms (AWS or Azure) * Drive adoption ...

Lead Agentic AI Engineer

Austin, TX · Remote

$98K - $129K/yr

Remote, EST Time zone Role Overview We are looking for a Lead Agentic AI Engineer to drive the ... Oversee deployment, scalability, and performance on cloud platforms (AWS or Azure) * Drive adoption ...

Senior Applied AI Engineer

Dallas, TX · On-site +1

$103K - $142K/yr

Deploy and maintain AI systems across Databricks and Microsoft Azure services such as Azure ... This position's work style is remote from any of the locations listed below. You must reside in ...

Senior Applied AI Engineer

Dallas, TX · On-site +1

$103K - $142K/yr

Deploy and maintain AI systems across Databricks and Microsoft Azure services such as Azure ... This position's work style is remote from any of the locations listed below. You must reside in ...

Showing results 21-40

Azure Ai Engineer Remote information

What are the key skills and qualifications needed to thrive as an Azure AI engineer remote, and why are they important?

To thrive as an Azure AI Engineer (Remote), you need expertise in AI/ML concepts, programming languages like Python, and experience with cloud platforms, especially Microsoft Azure, often supported by a degree in computer science or a related field. Familiarity with Azure AI services (such as Azure Machine Learning, Cognitive Services), DevOps tools, and certifications like Microsoft Certified: Azure AI Engineer Associate are typically required. Strong problem-solving, communication, and collaboration skills are essential for remote teamwork and project delivery. These abilities ensure effective design, deployment, and management of AI solutions that meet business objectives in distributed environments.

How do Azure AI engineers typically collaborate with cross-functional teams in a remote setting?

As an Azure AI Engineer working remotely, you'll frequently collaborate with data scientists, software developers, and project managers through virtual meetings and cloud-based project management tools. Effective communication is crucial, as you'll need to translate complex AI solutions into actionable insights for both technical and non-technical stakeholders. You may participate in daily stand-ups, code reviews, and collaborative design sessions to ensure alignment on project goals and integration of AI models into larger cloud architectures. Remote work often requires strong self-management skills and proactive sharing of progress to maintain team cohesion.

What is the difference between Azure Ai Engineer Remote vs Data Scientist Remote?

AspectAzure Ai Engineer RemoteData Scientist Remote
Required CredentialsAzure certifications, AI/ML knowledgeStatistics, programming, data analysis skills
Work EnvironmentCloud platforms, AI development toolsData analysis, modeling, research environments
Employer & Industry UsageTech companies, AI-focused firmsResearch institutions, tech companies, finance
Search & Comparison IntentUnderstanding role differences, job requirementsCareer options, skill overlaps

Azure Ai Engineer Remote focuses on developing and deploying AI solutions using Azure cloud services, requiring certifications like Azure AI Engineer Associate. Data Scientist Remote emphasizes analyzing data, building models, and deriving insights, often with statistical and programming skills. While both roles involve data and AI, Azure Ai Engineers are more cloud and deployment-oriented, whereas Data Scientists focus on analysis and research.

What is an Azure AI engineer?

Azure AI Engineers are professionals who design, build, and deploy artificial intelligence solutions using Microsoft Azure's suite of AI services. They work with data scientists, developers, and stakeholders to integrate AI capabilities such as computer vision, natural language processing, and machine learning into cloud-based applications. Their responsibilities often include managing Azure AI resources, optimizing models for performance and scalability, and ensuring solutions align with business needs, all while working remotely.
What are the most commonly searched types of Azure Ai Engineer jobs in Texas? The most popular types of Azure Ai Engineer jobs in Texas are:
What job categories do people searching Azure Ai Engineer Remote jobs in Texas look for? The top searched job categories for Azure Ai Engineer Remote jobs in Texas are:
What cities in Texas are hiring for Azure Ai Engineer Remote jobs? Cities in Texas with the most Azure Ai Engineer Remote job openings:
Infographic showing various Azure Ai Engineer Remote job openings in Texas as of August 2026, with employment types broken down into 73% Full Time, 23% Part Time, and 4% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution.

Lead/Staff Full Stack Engineer, AI Platform & Agents (US/Canada Hybrid/Remote)

Wolters Kluwer

Austin, TX • On-site, Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 9 days ago


Wolters Kluwer rating

9.0

Company rating: 9.0 out of 10

Based on 28 frontline employees who took The Breakroom Quiz

33rd of 242 rated software companies


Job description

Build the GenAI platform that powers critical decisions in healthcare, legal, tax, and compliance industries. Your work will directly shape the future of these fields, enabling faster, safer, and more impactful decision-making at a global scale.

-Location: : US/Canada, Hybrid or Remote
-Work Hours: Must have 9-11 AM CST overlap

  • Candidates within commuting distance of a Wolters Kluwer office will be considered for hybrid employment, with 2 days per week onsite.
  • Candidates not within commuting distance will be considered for remote employment.

About this role

Our team is building a central GenAI Platform to empower hundreds of product teams across the organization with scalable capabilities for rapid development, validation, and deployment of AI agents. We also drive the development of the most impactful AI agents, ensuring faster delivery and greater impact across multiple domains. With over 20 agents already launched and many more in progress, our work accelerates innovation and improves outcomes in critical industries.

You'll join a 100-engineer remote-first team within a larger organization that combines the stability of an established company with the agility of a startup. In this high-autonomy, high-impact role, you'll take problems from concept to production. You'll design and ship full-stack systems, shape platform capabilities to empower hundreds of product teams, and directly contribute to the development of the most impactful AI agents.

Flagship Agent: UpToDate Expert AI

In Health, we're launchingUpToDate Expert AI-a medical research and clinical reasoning agent that transforms the world's most widely used pointofcare knowledge resource into a realtime medical assistant. Millions of physicians will rely on it to accelerate differential diagnosis, refine treatment decisions, and reduce cognitive load-while maintaining rigorous safety, privacy, and guideline fidelity. Improvements you ship (latency, reliability, hallucination reduction) will translate directly into faster, higher-quality patient care at global scale.

Tech stack

You don't need to know all of these on day one, but you should be ready to learn quickly.

  • TypeScript, Node.js, React, Python, LangChain/LangGraph, MCP/A2A, Rust
  • AWS (primary), Azure, GCP; Docker, Terraform, GitHub Actions
  • DocumentDB, DynamoDB, OpenSearch, Azure AI Search
  • Azure OpenAI, AWS Anthropic, Google Gemini
  • GitHub, Confluence, Slack

What you'll do

  • Design and implement fullstack applications, AI agents, and platform components that enable rapid GenAI agent development, validation, and deployment.
  • Build developer tooling, CI/CD, and observability for safe, fast iteration (evals, canaries, rollout/rollback, cost and quality telemetry).
  • Apply secure SDLC and privacybydesign practices (threat modeling, least privilege).
  • Collaborate with product, UX, and domain experts to deliver customerfocused solutions with measurable outcomes.
  • Apply current LLM patterns (RAG, retrieval, routing, tool-use, evals) to deliver measurable customer value-faster, more reliable AI systems; reduced time-to-decision; improved trust/safety metrics; and lower cost per query.
  • Lead by example through writing high-quality, maintainable code that demonstrates engineering craftsmanship.

Team context

  • Org and Sub-teams: Central GenAI Platform within Wolters Kluwer, driving innovation across businesses by creating re-usable platform services and components. Sub-teams are fewer than 10 engineers, focused on platform services or customer-facing agents.
  • Culture and Reporting: We value a "manager of one" mindset, where outcomes matter more than optics. Authority is earned through demonstrated impact, not tenure or title. You'll report directly to the VP of Engineering, AI Platform.
  • Team Size and Impact: Our globally distributed team of ~100 engineers combines the stability of an established company with the agility of a startup. We are moving fast, and there are many areas where you can have a big impact.
  • Work setup: Remote-first in US or EU, with hybrid options near major offices. Collaboration requires 9-11 AM CST overlap. Occasional travel for team onsites/offsites as needed.

Minimum qualifications

  • 5+ years of professional software engineering experience.
  • Strong fullstack development skills and cloud experience (AWS/Azure/GCP).
  • Expert in at least one, and proficient across the others:
    • AI Agent development and evaluation
    • Backend development
    • Frontend development
    • Cloud services (AWS/Azure/GCP)
    • CI/CD and Infrastructure as Code
    • Site Reliability Engineering (SRE)
    • Quality engineering / testing strategy
    • Secure SDLC and privacy by design
  • Proven track record delivering secure, reliable, cloudnative systems to production.
  • Excellent problemsolving, ownership, and crossfunctional communication.

Nice to have

  • Proven ability to deliver software products independently or as part of a small, fast-paced team.
  • Experience of taking AI agents from concept to production, including safety evaluations, iterative testing (e.g., A/B testing), and continuous improvement.
  • Experience with LangChain/LangGraph and MCP; vector/RAG systems; OpenSearch.
  • Worked on traditional ML tasks like training, deployment, and monitoring.
  • Understand how LLMs work, their failure modes, and techniques like fine-tuning and model adaptation.
  • Familiarity with regulatory frameworks such as SOC2, HIPAA, etc.

To apply:

Please submit your resume along with a brief cover letter that includes a "Statement of Exceptional Work." In your cover letter, highlight one of your most impactful projects by addressing the following:

  • Your role and the problem space you were working in
  • The technical and product challenges you faced, and how you addressed them
  • The measurable impact of your work (e.g., metrics, outcomes, improvements)

This will help us better understand your approach to solving complex problems and the value you bring to the team.

Please do not include any proprietary or confidential information in your submission

Our Interview Practices

To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we're getting to know you-not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process.

Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.

Compensation:

$97,400.00 - $174,050.00 USD

Compensation range listed is based on primary location of the position. Actual base salary offer is influenced by a wide array of factors including but not limited to skills, experience and actual hiring location. Your recruiter can share more information about the specific offer for the job location during the hiring process.

Additional Information:

Wolters Kluwer offers a wide variety of competitive benefits and programs to help meet your needs and balance your work and personal life, including but not limited to: Medical, Dental, & Vision Plans, 401(k), FSA/HSA, Commuter Benefits, Tuition Assistance Plan, Vacation and Sick Time, and Paid Parental Leave. Full details of our benefits are available upon request.


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