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Azure Ai Engineer Remote Jobs in Romeoville, IL (NOW HIRING)

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Azure Ai Engineer Remote information

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How much do azure ai engineer remote jobs pay per hour?

As of Jul 30, 2026, the average hourly pay for azure ai engineer remote in Romeoville, IL is $54.68, according to ZipRecruiter salary data. Most workers in this role earn between $44.13 and $63.46 per hour, depending on experience, location, and employer.

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 are Azure AI Engineers?

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 popular job titles related to Azure Ai Engineer Remote jobs in Romeoville, IL? For Azure Ai Engineer Remote jobs in Romeoville, IL, the most frequently searched job titles are:
What cities near Romeoville, IL are hiring for Azure Ai Engineer Remote jobs? Cities near Romeoville, IL with the most Azure Ai Engineer Remote job openings:
Azure Ai Engineer Remote jobs near you

Principal AI Engineer (Remote)

Inspira Financial

Oak Brook, IL • On-site, Remote

Full-time

Re-posted 19 days ago

Inspira Financial rating

7.2

Company rating: 7.2 out of 10

Based on 20 frontline employees who took The Breakroom Quiz

Job description

The Director, AI Solutions Architect is a senior technical leader responsible for translating enterprise AI strategy into scalable, secure, and production-ready solutions. Reporting to the Senior Director, Software Engineering, this role serves as the connective tissue between strategy and execution-owning solution architecture, technical standards, and delivery excellence for AI-enabled products across the organization.
This leader works side by side with Product, Design, Engineering, Security, and Platform teams to deliver AI-driven solutions that delight customers and accelerate time to value-while balancing feasibility, scalability, cost, and compliance. The Director sets architectural direction, coaches teams, and remains hands-on where it matters most, ensuring the organization applies AI responsibly and effectively to real business problems.
You will guide engineering teams on when and how to apply AI capabilities-copilots, agents, and vendor integrations-while enforcing architectural guardrails and elevating engineering maturity. You translate vision into architecture, patterns, and working software that deliver measurable outcomes. You are equally comfortable influencing executives and diving into code with teams to unblock delivery.
Key Responsibilities
  • Own end-to-end solution architecture for AI and AI-enabled products (discovery → design → deployment), ensuring security, reliability, cost efficiency, and maintainability across cloud and on-prem environments.
  • Serve as the architecture authority for GenAI and applied AI solutions, approving designs and ensuring alignment with enterprise standards set by the AI CoE.
  • Establish and evolve reference architectures and reusable patterns for GenAI and applied AI (RAG, agents/orchestration, vector search, prompt & tool design, event-driven microservices, API gateways).
  • Select fit-for-purpose models and services (e.g., Azure OpenAI, Bedrock, Vertex, OSS LLMs, embedding models), articulating clear tradeoffs across performance, latency, privacy, and cost.
  • Partner with product and platform teams to ship production-grade solutions, guiding teams from prototype → pilot → scaled production.
  • Define and enforce best practices for CI/CD, Infrastructure as Code, and MLOps/LLMOps, including model versioning, prompt/config management, evaluation frameworks, drift detection, and safety monitoring.
  • Ensure observability and operational readiness (tracing, guardrails, red-teaming, cost dashboards, SLOs, runbooks) before production cutover.
  • Review critical pull requests, architecture decisions, and platform changes to raise overall engineering quality.
  • Act as a technical leader and multiplier, coaching engineers and architects on responsible, pragmatic AI adoption.
  • Build and mentor a small group of senior architects and technical leads, helping grow the next generation of AI leaders.
  • Evangelize effective use of copilots, agent frameworks, and integration SDKs to improve developer velocity without compromising quality or security.
  • Raise the bar on engineering excellence through design reviews, threat modeling, coding standards, and documentation discipline.
  • Lead architecture discovery with business stakeholders: frame problems, quantify constraints, and translate business goals into technical roadmaps.
  • Define and track outcome-based KPIs (time to first value, cost to serve, task success, accuracy, CSAT/NPS, deflection).
  • Communicate architectural tradeoffs, risks, and roadmaps in clear, executive-ready language.
  • Publish and maintain architecture decision records (ADRs) and platform documentation to ensure

Education & Experience
  • Bachelor's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or equivalent practical experience.
  • 10+ years in software engineering, solution architecture, or platform engineering, including 3-5+ years delivering applied ML/GenAI solutions in production.
  • Demonstrated experience leading architecture across multiple teams or products, not just contributing as an individual architect.
  • Extensive hands-on experience with cloud platforms (GCP preferred), including:
  • Vertex AI, BigQuery, Dataflow, Pub/Sub
  • Cloud-native microservices, APIs, event streaming
  • Containers and orchestration (Kubernetes/GKE)
  • Infrastructure as Code (Terraform)
  • Deep practical expertise with GenAI patterns: RAG, vector databases, prompt engineering & evaluation, agent design, function/tool calling, and orchestration.
  • Strong command of MLOps/LLMOps, including CI/CD for models and prompts, offline/online evaluation, telemetry, drift detection, and safety monitoring.

Skills & Abilities
  • Experience operating in regulated industries (financial services, healthcare, public sector) or similarly high-trust environments.
  • Strong background in security, privacy, and compliance-by-design, including OAuth/OIDC, secrets management, data protection, and AI safety controls.
  • Proven ability to influence without authority, aligning product, engineering, security, and business stakeholders.
  • Exceptional written and verbal communication skills, with demonstrated executive presence.
  • Certifications (nice to have): Cloud Architect, Security (e.g., CISSP/CCSK), or equivalent.

Other Requirements:
  • Ability to work occasional overtime.
  • Occasional travel (up to ~15%).
  • Occasional after-hours work to support releases or incident response.
  • Prolonged periods of sitting at a desk and working on a computer.

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