Senior AI Platform Engineer

Description

The company builds a single system that lets safety, operations, and finance teams manage drivers, vehicles, equipment, and fleet-related spend together, with AI that adds visibility and control and cuts manual work by automating routine tasks.

It serves close to 100,000 customers, from Fortune 500 enterprises to small businesses, in transportation and logistics, construction, energy, field service, manufacturing, agriculture, food and beverage, retail, and the public sector.

This is a senior role for an engineer who ships production software and AI systems on cloud infrastructure that must be reliable, secure, and cost-disciplined. You will design applications and services, run inference platforms and pipelines, and treat tokens, GPU-hours, and idle capacity as real constraints on the design.

You will work with product, engineering, and business teams to deliver working software, improve reliability, and bring down the cost of each unit of AI output.

Responsibilities

• Build, ship, and maintain production services, APIs, and user-facing interfaces where needed, owning implementation, testing, code review, CI/CD, and deployment.
• Write maintainable Python and one other stack from TypeScript/Node, Go, or Java.
• Build and run production AI systems covering retrieval-augmented generation, evaluation, fine-tuning, serving, and inference performance.
• Turn prototypes into shared platform capabilities that include CI/CD, evaluation, and governance.
• Design AWS or GCP environments using Kubernetes, Terraform, and CI/CD for both applications and model pipelines.
• Own monitoring and incident response, and work with others on SOC 2 and SOX compliance and least-privilege access controls.
• Track cloud and AI spend, attribute it to owners, set budgets, and find ways to cut it.
• Tune GPU usage, inference routing, model selection, and instance sizing, and monitor cost per request, cost per token, and GPU idle time.

Requirements

• At least 5 years of professional software development, including owning production systems rather than only scripts or notebooks.
• Experience shipping backend services or APIs and production AI or ML systems, such as LLMs, RAG, or model serving.
• Strong Python plus a second language stack, with experience in PyTorch, TensorFlow, or equivalent serving tools.
• Hands-on experience with AWS or GCP, Kubernetes, Terraform, and CI/CD.
• A proven record of reducing or governing cloud and AI spend.
• Ability to explain technical and cost trade-offs clearly, and to run the systems you build.
• Nice to have: full-stack work with React or Next.js, vector databases, inference optimization, FinOps tooling, SOX or SOC 2 experience, and Copilot or Cursor.
• Success here means production software and AI with defined SLOs and real ownership, not demos. Reliability stays high while GPU and cloud waste falls, and the cost per unit of AI value is visible and improving. Teams reuse libraries, infrastructure-as-code, and cost guardrails.

Conditions

Pay may depend on factors such as education, experience, and certifications. Some roles may include restricted stock units. Benefits include health, pharmacy, optical, and dental coverage, paid and sick time off, short and long term disability, life insurance, and a 401k contribution, subject to eligibility.

Pay depends on where you live. For Canada, the range is $137,000 to $165,000 CAD.

The company is an equal opportunity employer and values a diverse workforce.

You must be authorized to receive and access commodities and technologies controlled under the U.S. Export Administration Regulations, as the company requires for access to its products and technology.

For some US-based roles, candidates may be required to sign a non-compete covenant, depending on the role and primary work location. This does not apply to lawyers, interns, or employees in CA, MN, MT, ND, OK, or where otherwise barred by law. Other jurisdictions follow the applicable statutory rules, including procedures, industry restrictions, and pay thresholds.

These are open positions. Some interviews or new-hire training may take place in person at one of the company's global offices.

Benefits

• Health, pharmacy, optical, and dental coverage, paid time off, sick time off, short and long term disability, life insurance, and a 401k contribution, subject to eligibility.
• Possible restricted stock units for certain roles.