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Niche senior MLOps role in Bengaluru with regulated-domain and LLMOps focus limits broad applicant competition.
Regulated healthcare/fintech experience plus LLMOps and Azure ML expertise make cross-industry transfers difficult.
Explicit 7+ years, 5+ years leading ML initiatives, and mandated regulated-domain and tooling experience enforce strict filters.
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Own and establish enterprise-grade MLOps and LLMOps practices including automated model lifecycle management, monitoring, compliance, and deployment in regulated environments.
Lead knowledge transfer and operational governance so AI teams can operate independently and maintain audit trails.
Transition to research and innovation leadership focusing on emerging AI architectures, agentic AI workflows, and translating research into production capabilities.
7+ years of software engineering experience; 5+ years leading AI/ML initiatives at production scale.
Strong hands-on expertise in at least 4 of these areas: MLOps, LLMOps, evaluation frameworks, drift monitoring, CI/CD for ML, model governance.
Proficient in Python for production systems development and debugging.
Experience deploying AI solutions in regulated domains such as healthcare, fintech, or benefits administration.
Builder-first with a pragmatic approach prioritizing operational foundation before advanced research.
Operations-oriented with experience in production readiness, compliance, monitoring, and establishing governance frameworks.
Experienced in applied AI research with a strategic outlook to influence product roadmap and AI platform evolution.