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Flex Ai Infrastructure Engineer Jobs (NOW HIRING)

Utilidata

AI Infrastructure Engineer

Ann Arbor, MI · Remote

$170K - $210K/yr

The AI Infrastructure Engineer is responsible for designing, building, and owning the end-to-end infrastructure that serves Utilidata's AI and ML models across edge deployments, cloud environments ...

Seekr

Senior AI Infrastructure Engineer

Austin, TX · On-site

$107K - $146K/yr

As a Senior AI Infrastructure Engineer, you will design, build, and operate the platforms that enable large-scale training, serving, evaluation, and deployment of foundation models and autonomous AI ...

BlackRock

AI Infrastructure Engineer

New York, NY · On-site

$117K - $154K/yr

YOUR ROLE AND IMPACT As an AI-Enabled Infrastructure and Systems Engineer, you will combine deep infrastructure expertise with modern software engineering practices to design, build, and operate the ...

Spellbrush

AI Infrastructure Engineer

San Francisco, CA · On-site

$126K - $166K/yr

Spellbrush is the world's leading generative AI studio behind niji・journey, and they are seeking an AI Infrastructure Engineer to build out end-to-end ML infrastructure. The role involves designing ...

vCluster Labs

AI Infrastructure Engineer

New York, NY · Remote

$140K - $165K/yr

As an AI Infrastructure Engineer, your role will include: * Lead Technical Deployments: Drive end-to-end technical deployments for GPU neocloud and AI Factory customers, from initial bare metal ...

Gatik AI

Senior AI Infrastructure Engineer

Santa Clara, CA

$127K - $173K/yr

About the role We are seeking a Senior AI Infrastructure Engineer to design, build, and scale the high-performance AI platform powering our autonomous driving models. While researchers focus on ...

Gatik AI

Senior AI Infrastructure Engineer

Santa Clara, CA · On-site

$127K - $173K/yr

About the role We are seeking a Senior AI Infrastructure Engineer to design, build, and scale the high-performance AI platform powering our autonomous driving models. While researchers focus on ...

Scout Motors

AI Infrastructure Engineer

Charlotte, NC

$140K - $170K/yr

Deploy and manage AI services across cloud and on-prem environments. * Automate infrastructure ... Collaborate with engineering, data, and product teams to support AI initiatives. * Excellent ...

Scout Motors

AI Infrastructure Engineer

Charlotte, NC · On-site

$105K - $137K/yr

Deploy and manage AI services across cloud and on-prem environments. * Automate infrastructure ... Collaborate with engineering, data, and product teams to support AI initiatives. * Excellent ...

Visa Hunt

AI Infrastructure Engineer

San Francisco, CA · On-site

$180 - $240/hr

Spellbrush, the world's leading generative AI studio behind niji・journey, is looking for an AI Infrastructure Engineer to join us in building out end-to-end ML infrastructure to run our models on ...

AMAX

AI Infrastructure Engineer

Fremont, CA · On-site

$117K - $154K/yr

Development and deployment of AI infrastructure workloads on-prem (GPU scheduling, model serving ... infra engineering Benefits * Medical Insurance * Dental Insurance * Vision Insurance * 401(k)

Visa Hunt

$180 - $240/hr

Spellbrush, the world's leading generative AI studio behind niji・journey, is looking for an AI Infrastructure Engineer to join us in building out end-to-end ML infrastructure to run our models on ...

AMAX

AI Infrastructure Engineer

Fremont, CA · On-site

$126K - $165K/yr

Development and deployment of AI infrastructure workloads on-prem (GPU scheduling, model serving ... infra engineering Benefits * Medical Insurance * Dental Insurance * Vision Insurance * 401(k)

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Flex Ai Infrastructure Engineer information

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$46.5K

$127.1K

$182K

How much do flex ai infrastructure engineer jobs pay per year?

As of Sep 4, 2026, the average yearly pay for flex ai infrastructure engineer in the United States is $127,066.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,500.00 and $141,000.00 per year, depending on experience, location, and employer.

What is the difference between Flex Ai Infrastructure Engineer vs Data Center Technician?

AspectFlex Ai Infrastructure EngineerData Center Technician
Required CredentialsBachelor's in Computer Science or related field, certifications like Cisco CCNA or CompTIA Network+High school diploma or equivalent, technical certifications preferred
Work EnvironmentDesigning, deploying, and maintaining AI infrastructure in data centers or cloud environmentsMaintaining and troubleshooting physical data center hardware and network equipment
Industry UsageUsed in AI-focused companies, cloud providers, and tech firmsCommon in data centers, telecom, and enterprise IT facilities
Common Search/ComparisonOften compared for infrastructure roles supporting AI systemsCompared for hardware and network support roles in data centers

The Flex Ai Infrastructure Engineer focuses on designing and maintaining AI infrastructure, often involving cloud and data center environments, while the Data Center Technician handles physical hardware and network troubleshooting within data centers. Both roles require technical skills but differ in scope and responsibilities.

What cities are hiring for Flex Ai Infrastructure Engineer jobs?

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What are the most commonly searched types of Ai Infrastructure Engineer jobs?

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Flex Ai Infrastructure Engineer jobs near you

AI Infrastructure Engineer

Utilidata

Ann Arbor, MI • Remote

$170K - $210K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 22 days ago

Job description

Utilidata is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically orchestrate power and unlock more compute capacity from existing energy infrastructure. For over a decade, we have applied AI to the electric grid — bringing real-time visibility and power-flow control to complex energy infrastructure. Our Karman platform, built on a custom NVIDIA module, brings that same capability to AI data centers, giving operators a way to better use the power already available to them.
The AI Infrastructure Engineer is responsible for designing, building, and owning the end-to-end infrastructure that serves Utilidata's AI and ML models across edge deployments, cloud environments, and data center integrations. They are also responsible for designing, building, and owning the integration of power data with AI inference software.  This is Utilidata's first dedicated role of this kind, and will serve as the foundational function for how the company deploys and operates AI capabilities in production. The role requires deep technical expertise in ML model serving, distributed systems, and GPU infrastructure, with a strong emphasis on reliability, performance, and scalability. This position works cross-functionally with product, engineering, and data science teams and is open to fully remote candidates, with periodic travel expected for company retreats and key on-site engagements.
Responsibilities
  • Lead the design and build of Utilidata's AI inference platform — establishing architecture patterns, deployment standards, and operational practices that will scale with the company
  • Own end-to-end model serving infrastructure for Utilidata's AI infrastructure (on-prem and datacenter) 
  • Build and maintain fault-tolerant, high-performance systems for serving AI models at scale, with a focus on low latency, reliability, and cost efficiency
  • Collaborate closely with algorithms engineers to integrate AI inference data and configuration with power optimization algorithms 
  • Optimize GPU utilization and inference performance across our hardware fleet, including NVIDIA accelerators central to Utilidata's edge AI platform
  • Establish MLOps best practices including CI/CD pipelines for model deployment, monitoring, and rollback across environments
  • Contribute to infrastructure roadmap decisions, including build vs. buy tradeoffs, tooling selection, and platform evolution as the team grows

Minimum Qualifications 
  • 5+ years of software engineering experience with a strong focus on AI infrastructure, backend systems, or distributed systems
  • Hands-on experience with AI model serving frameworks (e.g., vLLM, SGLang, Triton, TensorRT, TorchServe, or similar)
  • Understanding of container orchestration and cluster management (Kubernetes, Docker)
  • Experience deploying and operating infrastructure across both datacenter and on-prem environments
  • Strong knowledge of GPU workloads and the tradeoffs that come with them — you understand how inference differs from training, and why it matters
  • Proficiency in Python; C++, CUDA, Go, Rust a plus
  • Excellent communication skills and comfort working cross-functionally in a lean, fast-moving environment
  • Willingness to travel up to 10% of time 

Enhanced Qualifications (Nice to Have) 
  • Dynamo experience a plus
  • Experience with edge AI deployments or constrained compute environments
  • Familiarity with infrastructure as code (Terraform, Helm)
  • Experience with observability platforms (Datadog, Prometheus, Grafana)
  • Background in energy, utilities, or industrial IoT
  • Contributions to open-source ML infrastructure projects

Salary Range: $170,000 to $210,000 base compensation depending on experience plus stock options. Salary will be commensurate with an individual's skills, training, years of experience, and in line with internal compensation bands.
Location: This position can be performed remotely from anywhere in the United States. 
Our Commitments:
Utilidata values the diversity of our team. We provide equal employment opportunities without regard to race, color, religion, creed, sex, gender, sexual orientation, gender identity or expression, national origin, age, physical disability, mental disability, medical condition, pregnancy or childbirth, sexual orientation, genetics, genetic information, marital status, or status as a covered veteran or any other basis protected by applicable federal, state and local laws.
We are committed to:
  • Creating a diverse and inclusive workplace that is welcoming, supportive, affirming and respectful
  • Empowering employees to solve problems and work together to make a difference
  • Providing mentorship and growth opportunities as part of a collaborative team
  • A flexible work environment with flexible paid time off
  • Competitive compensation and benefits, including health, dental, vision, and employer-match 401k

 

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