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Ai Infrastructure Jobs in Rochester, NY (NOW HIRING)

US Tech - AI Engineering Manager

Rochester, NY ยท On-site

$73K - $244K/yr

As a Manager you will combine engineering knowledge with people leadership to deliver resilient platforms that integrate cloud infrastructure, conversational AI, data, and enterprise systems. This ...

DevOps Solutions Engineer

Hopewell, NY ยท On-site

$53.25 - $73/hr

AI-First Thinking at Lovingly We believe AI is not just a tool-it's a strategic partner that enhances our infrastructure, security, and efficiency. As a DevOps Solutions Engineer , you won't just ...

Data Engineer

Rochester, NY ยท On-site

$113K - $135K/yr

The role involves designing, building, and maintaining data pipelines and infrastructure on AWS ... AI-Native Transformation, Application Modernization, Amazon Connect, Cloud Migrations, Data ...

Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real ...

Why Join Us Help build one of the industry's most ambitious enterprise analytics platforms for critical infrastructure while shaping the future of AI-N #LI-MG1 Ralliant Corporation Overview Ralliant ...

Why Join Us Help build one of the industry's most ambitious enterprise analytics platforms for critical infrastructure while shaping the future of AI-Native Product Engineering. #LI-MG1 Ralliant ...

Showing results 21-40

Ai Infrastructure information

See Rochester, NY salary details

$27

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$86

How much do ai infrastructure jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for ai infrastructure in Rochester, NY is $58.41, according to ZipRecruiter salary data. Most workers in this role earn between $47.45 and $68.08 per hour, depending on experience, location, and employer.

What is the difference between Ai Infrastructure vs Data Engineer?

AspectAi InfrastructureData Engineer
Required CredentialsBachelor's in CS, Engineering, or related; knowledge of cloud platforms and AI toolsBachelor's in CS, Data Science, or related; programming and database skills
Work EnvironmentCloud environments, AI model deployment, infrastructure setupData pipelines, database management, data processing
Employer & Industry UsageTech companies, AI startups, cloud providersTech firms, finance, healthcare, e-commerce

Ai Infrastructure professionals focus on building and maintaining the hardware and software systems that support AI models, while Data Engineers develop and manage data pipelines and databases. Both roles require technical skills and often collaborate but serve different core functions within AI and data ecosystems.

How much do AI infrastructure engineers make?

AI infrastructure engineers typically earn between $100,000 and $150,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in cloud platforms and hardware may earn higher salaries, often exceeding $180,000.

What are AI infrastructure jobs?

AI infrastructure jobs involve designing, building, and maintaining the hardware, software, and network systems necessary to support artificial intelligence applications. These roles often require knowledge of cloud computing, data centers, machine learning frameworks, and system optimization to ensure reliable and efficient AI model deployment and operation.

What are the key skills and qualifications needed to thrive in AI infrastructure?

To thrive in AI Infrastructure, you need expertise in software engineering, distributed systems, cloud platforms, and a solid understanding of machine learning workflows, often supported by degrees in computer science or related fields. Familiarity with tools like Kubernetes, Docker, Terraform, and cloud services (AWS, GCP, Azure), as well as experience with CI/CD pipelines and monitoring systems, is essential. Strong problem-solving abilities, effective communication, and adaptability help professionals excel in cross-functional teams and rapidly evolving environments. These skills and qualities are crucial for building scalable, reliable systems that power AI applications and support organizational innovation.

What are common challenges faced by professionals working in AI infrastructure roles, and how can they be addressed?

Professionals in AI Infrastructure roles often encounter challenges related to scalability, system reliability, and integration with existing IT environments. Managing rapidly growing datasets and ensuring seamless deployment of machine learning models can be complex, requiring robust automation and monitoring tools. Collaboration with data scientists, software engineers, and DevOps teams is critical to ensure infrastructure meets the evolving needs of AI projects. Staying updated with the latest cloud technologies and best practices can help address these challenges and drive successful AI implementations.

What is AI infrastructure?

AI infrastructure refers to the combination of hardware, software, and cloud-based solutions that support the development, deployment, and scaling of artificial intelligence applications. It includes components such as GPUs, CPUs, storage systems, networking, data management tools, and machine learning frameworks. The goal of AI infrastructure is to provide the computational power and resources needed to train, test, and run AI models efficiently, whether on-premises or in the cloud. Organizations invest in robust AI infrastructure to accelerate innovation, manage large datasets, and ensure the reliability of their AI systems.

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What cities near Rochester, NY are hiring for Ai Infrastructure jobs?

Cities near Rochester, NY with the most Ai Infrastructure job openings:

Infographic showing various Ai Infrastructure job openings in Rochester, NY 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, with an average salary of $121,494 per year, or $58.4 per hour.

AI Solutions Design Manager - Hybrid

Mindex

Rochester, NY โ€ข Hybrid

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 4 days ago


Job description

Mindex is looking for an AI Solutions Design Manager to lead the strategy, design, and delivery of AI and Generative AI solutions that solve real business challenges and improve operational performance. This role blends hands-on technical expertise with strategic leadership - you'll guide cross-functional teams to identify high-value opportunities, architect scalable AI/GenAI systems, and drive successful adoption across the organization.

You'll be equally comfortable setting direction at the roadmap level and getting into the weeds on solution architecture, model selection, and RAG/agent design - while also serving as a trusted advisor who can translate complex AI concepts into language business leaders can act on.

Compensation

$160,000 - $180,000, plus a 20% bonus based on company performance goals.

What You'll Accomplish

Strategy & Innovation

  • Develop and maintain an AI/GenAI vision and roadmap aligned to business goals, identifying high-value use cases across business units.
  • Evaluate emerging AI technologies - LLMs, copilots, multimodal models, autonomous agents, automation platforms - and recommend practical, prioritized applications.
  • Establish standards and reusable design patterns for prompt engineering, model tuning, and GenAI solution architecture.

Solution Architecture & Delivery

  • Lead end-to-end design of AI/ML and GenAI solutions from concept to production, translating business requirements into technical specifications, data flows, and architectures.
  • Architect GenAI-powered applications such as chatbots, copilots, summarization engines, and content-generation workflows.
  • Oversee development of reusable GenAI components - prompt libraries, embeddings, vector search, knowledge models, and RAG systems - and guide model selection and fine-tuning decisions.
  • Partner with data engineering and IT teams to ensure solutions are scalable, maintainable, and meet enterprise standards for security, privacy, and governance.

Project & Team Leadership

  • Manage the AI/GenAI project portfolio, including scoping, planning, resourcing, and execution.
  • Lead cross-functional teams of data scientists, engineers, analysts, and business stakeholders through agile delivery cycles.
  • Serve as a trusted advisor to business leaders on AI capabilities, risks, and best practices, and support change management for organization-wide adoption.

Governance & Responsible AI

  • Ensure AI/GenAI solutions meet ethical, fairness, privacy, and regulatory standards, including content filtering, hallucination mitigation, and usage guardrails.
  • Define acceptable-use policies and risk frameworks for internal GenAI tools, and maintain documentation, monitoring, and lifecycle management processes.
  • Oversee adoption and governance of enterprise GenAI platforms (Microsoft 365 Copilot, Azure OpenAI, GitHub Copilot, etc.) in partnership with security and infrastructure teams.

Enablement & Operationalization

  • Develop training programs on responsible AI/GenAI usage and coach teams on effective prompt engineering and human-in-the-loop workflows.
  • Define KPIs to measure GenAI performance and business value, and monitor for model drift, usage patterns, hallucination rates, and user satisfaction.
  • Lead continuous improvement cycles for AI/GenAI systems based on data-driven insights.

Requirements

  • Bachelor's or Master's degree in Computer Science, AI/ML, Engineering, Data Science, or a related field.
  • 7+ years of experience in AI/ML, data analytics, or software engineering, including 3+ years leading technical teams or designing enterprise AI solutions.
  • Strong understanding of machine learning, LLMs, NLP, deep learning, and automation technologies.
  • Hands-on experience with modern AI platforms (Azure ML, Databricks, OpenAI, AWS, etc.).
  • Proven ability to translate business needs into scalable technical solutions.
  • Strong leadership, communication, and stakeholder engagement skills.

Preferred

  • Experience deploying enterprise GenAI or LLM-based applications.
  • Cloud certifications (Azure, AWS, GCP).
  • Experience with MLOps, RAG, vector databases, and prompt engineering.
  • Previous leadership experience across hybrid technical/business teams.

Success Indicators

  • Delivery of AI/GenAI solutions with measurable business impact.
  • Strong adoption and satisfaction across business teams.
  • Advancement of organizational AI maturity and literacy.
  • Demonstrated innovation and ROI from AI-enabled transformation.

Benefits

  • Hybrid
  • Medical, Dental, and Vision Insurance
  • 401(k) with Company Match
  • Company-Paid Life and Disability Insurance
  • Professional Development Opportunities

Additional Information

  • Applicants must be authorized to work for any employer in the United States. Mindex is unable to sponsor employment visas at this time.

Physical Requirements/Conditions

  • Prolonged periods sitting at a desk and working on a computer.
  • No heavy lifting is expected. Exertion of up to 10 lbs.