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Senior AI Platform Engineer ( Enterprise Systems)
Motive (company site, opens in a new tab)5+ yrsRemoteDirect career pageEst. 28–45 LPA
Posted on 11 Sept
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Job description
Structured overview of role & requirements
About This Role
- Design, build, ship, and maintain production AI and backend services on cloud infrastructure with focus on reliability, security, and cost optimization.
- Own full lifecycle of AI systems including RAG, fine-tuning, serving, inference optimization, plus cloud architecture and incident response.
- Manage cloud and AI spend as engineering constraints by optimizing usage metrics like GPU-hours and cost per token, driving reductions in waste and cost per AI value unit.
Minimum Requirements
- 5+ years professional software development experience owning production backend services and AI/ML systems (LLMs, RAG, serving).
- Proficient in Python plus a second language (TypeScript/Node, Go, or Java); experience with PyTorch or TensorFlow serving frameworks.
- Experience with AWS or GCP cloud platforms, Kubernetes, Terraform, and CI/CD pipelines.
- Demonstrated experience in controlling or governing cloud and AI expenditures.
Ideal Candidate Profile
- Strong engineering discipline with hands-on ownership of production AI infrastructure and application lifecycle management.
- Experienced in integrating AI systems into scalable cloud services with observability, security (SOC 2/SOX), and cost governance.
- Skilled in balancing operational reliability with cost efficiency in AI platform environments using FinOps practices and infrastructure automation.