Associate Director | Hybrid cloud | Bengaluru | Engineering | Hybrid Cloud Engineering (Bengaluru, IN)

Partner with architecture and engineering teams to:

Optimize model selection (open vs closed, fine-tuned vs base)

Improve prompt engineering for cost efficiency

Implement caching, batching, and routing strategies

Lead initiatives on:

GPU utilization optimization

Spot/reserved/committed usage strategies

Model distillation and quantization for cost reduction

Drive FinOps maturity across AI lifecycle (build → deploy → scale)

Establish AI cost observability frameworks :

Token usage telemetry

Cost per workload / use case dashboards

Define and implement:

Chargeback / showback models

Cost allocation across BUs, products, or tenants

Leverage tools such as:

Azure Cost Management, AWS Cost Explorer

FinOps platforms (Apptio, CloudHealth, CloudZero)

AI cost tracking tools (e.g., LangChain observability, custom telemetry)

Define policies, guardrails, and KPIs for responsible AI spend

Act as a trusted advisor to CxOs, product leaders, and platform teams

Translate technical AI cost drivers into business impact and financial insights

Lead AI value realization discussions (ROI, TCO, business case development)

Build enterprise GTM narratives around:

Sustainable AI adoption

FinOps for GenAI

Tokenomics-driven cost strategies

Develop frameworks, whitepapers, and POVs on:

AI FinOps maturity models

Tokenomics benchmarks and best practices

AI cost optimization patterns

Contribute to industry forums, client workshops, and internal capability building

12–15+ years of experience across:

Cloud FinOps / Cloud Economics

AI/ML platforms or data engineering

Technology consulting or enterprise architecture

Strong experience with hyperscaler cloud pricing models and cost optimization

Proven exposure to Generative AI / LLM ecosystems and cost drivers