We are seeking a highly skilled AI Cost Optimization & Workflow Engineer to design, optimize, and scale AI-powered workflows while ensuring cost efficiency across cloud and AI infrastructure environments.
This role focuses on optimizing LLM usage, GPU workloads, cloud spend, and AI orchestration pipelines while improving automation, performance, and reliability. The ideal candidate combines expertise in AI engineering, cloud architecture, MLOps, and FinOps principles.
Key Responsibilities
🔹 AI Cost Optimization
Monitor and optimize LLM API usage (token consumption, model selection, inference cost)
Reduce cloud infrastructure costs across AWS/Azure/GCP AI workloads
Optimize GPU utilization for training and inference environments
Implement autoscaling and workload right-sizing strategies
Build cost observability dashboards for AI workloads
Analyze and reduce redundant AI pipeline executions
🔹 AI Workflow Engineering
Design and implement scalable AI workflows (RAG, agent-based systems, automation pipelines)
Optimize prompt engineering to reduce token usage and latency
Implement caching strategies for AI responses
Build orchestration pipelines using tools like LangChain, Airflow, or similar frameworks
Integrate AI services with enterprise systems (ITSM, CRM, ERP, internal APIs)
Improve throughput, response time, and reliability of AI services
🔹 Governance & Monitoring
Implement model performance monitoring and drift detection
Establish AI usage guardrails and cost governance policies
Collaborate with FinOps and Cloud teams to align AI spend with business KPIs
Document architecture and optimization strategies
Required Qualifications
5+ years in Cloud Engineering, DevOps, MLOps, or AI Engineering
Strong experience with AWS, Azure, or GCP
Hands-on experience integrating and optimizing LLM APIs
Strong Python scripting skills
Experience with Kubernetes and containerized environments
Experience with Infrastructure as Code (Terraform preferred)
Understanding of cloud cost management tools
Experience designing RAG or AI automation pipelines