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Motive is a fleet operations and safety platform serving nearly 100,000 customers across transportation, logistics, construction, energy, field service, manufacturing, and other industries. The platform combines safety, operations, and finance management with industry-leading AI to give customers complete visibility and control over drivers, vehicles, equipment, and fleet spend.
As a Senior AI Platform Engineer, you will design, build, and operate production AI systems and cloud infrastructure that is reliable, secure, and cost-disciplined. You will own the full lifecycle of software and AI systems—from design through implementation, testing, deployment, and maintenance—while treating unit economics (tokens, GPU-hours, idle capacity) as core engineering constraints.
Key responsibilities include:
**Software Development:** Design and ship production services, APIs, and user-facing interfaces. Own the complete lifecycle including implementation, tests, code review, CI/CD, deployment, and maintenance. Write maintainable code in Python plus one additional stack (TypeScript/Node, Go, or Java).
**AI Engineering:** Build and operate production AI systems including RAG, evaluation, fine-tuning, serving, and inference optimization. Transform prototypes into reusable platform capabilities with CI/CD, evaluation frameworks, and governance.
**Cloud Infrastructure:** Architect AWS/GCP environments using Kubernetes, Terraform, and CI/CD for applications and model pipelines. Own observability and incident response; partner on SOC 2/SOX compliance and least-privilege IAM.
**Cost Control:** Treat cloud and AI spend as an engineering problem. Implement visibility, attribution, budgets, and cost reduction strategies. Optimize GPUs, inference routing, model selection, and resource right-sizing; track cost per request/token and GPU idle time.
You will partner with product, engineering, and business stakeholders to deliver working software, improve reliability, and reduce cost per unit of AI value. Success means shipping production software and AI with clear SLOs and real ownership, maintaining high reliability while reducing GPU and cloud waste, and making cost per unit of AI value visible and continuously improving across teams.
**Requirements:**
- 5+ years of professional software development, owning production systems (not scripts or notebooks)
- Shipped backend services/APIs and production AI/ML systems (LLMs, RAG, serving)
- Strong Python plus a second stack; experience with PyTorch, TensorFlow, or equivalent serving frameworks
- AWS or GCP experience with Kubernetes, Terraform, and CI/CD
- Proven track record reducing or governing cloud/AI spend
- Clear communication of technical and cost tradeoffs; you run what you build
**Preferred:**
- Full-stack capabilities (React/Next.js)
- Vector databases
- Inference optimization
- FinOps tooling
- SOX/SOC 2 compliance experience
- AI-assisted development tools (Copilot/Cursor)
