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Mid-level LLMOps/devops role in Mumbai with common title and 5+ years experience increases competition.
Technical LLMOps platform skills are transferable, but financial/regulatory security requirements moderately constrain background fit.
Mandatory 5+ years and required LLMOps, observability, security, and cloud skills increase shortlisting strictness.
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Own and operate the AI platform including model gateway, provider integrations, deployment, routing, quotas, release management, and cost optimization for AI services in production.
Monitor and maintain observability, performance, reliability, security, and incident response processes for AI services integrated with business workflows.
Collaborate with engineering, data, cybersecurity, and product teams to ensure AI services meet service-level objectives, compliance, security standards, and business outcomes.
5+ years in platform engineering, SRE, DevOps, MLOps, cloud engineering or related role managing production services and incident response.
Hands-on experience operating large language models or machine learning services in production with knowledge of token usage, latency, failure modes.
Strong Python or scripting skills; experience with CI/CD, infrastructure-as-code, containers, and cloud-native services.
Experience implementing observability with tools like OpenTelemetry and strong knowledge of cloud/application security including DevSecOps practices.
Experienced in building and managing AI/LLMOps platforms with strong focus on production reliability, cost control, and operational risk management.
Can effectively measure and communicate AI model performance, quality, and business impact to technical and non-technical stakeholders.
Comfortable operating in regulated environments (e.g., financial services) and working cross-functionally with software engineering, cybersecurity, data, and product teams.