Karman
via JazzHR
AI Infrastructure Engineer
still open
verified 1d ago
posted 15d ago seen 6h ago
Apply at karman.applytojob.com
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
First seen 15d ago
No source stated a posting date, so this is when the listing first reached us — which is a floor, not the real age. Last seen at its source 6h ago.
We have tracked this listing since 18 Oct 2026 (15 days). The employer's own board has carried it every time we have read it, most recently 6 hours ago.
Is it remote?
Remote
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
Not stated
The description states no restriction of its own. This is the source's own tag.
Pay
$170k–210k/yr
Read out of the job description by us, not from a structured field. Shown in the posting's own currency and period; we never convert.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
JazzHR employer's own board first seen 15d ago · last seen 6h ago
The listing
Karman 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
Minimum Qualifications
Enhanced Qualifications (Nice to Have)
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:
Karman 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:
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:
Karman 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