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Tier-1 employer and Bangalore location increase candidate density despite senior, specialized GenAI requirements.
ML/GenAI skills transferable but banking compliance and enterprise-scale requirements raise domain specificity.
Explicit 18+ years, multiple mandatory domain experiences, and cloud certifications create stringent hiring filters.
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Lead cross-functional teams to design, develop, and deploy scalable, production-ready Generative AI (GenAI) applications and services using LLMs across cloud and on-premises environments.
Own architecture and implementation of multi-agent orchestration frameworks, Agentic Engineering frameworks, model validation pipelines, and observability tools for LLM and multi-agent systems.
Define and manage OKRs/KPIs for GenAI programs, enforce best practices in automated testing, responsible AI, security, and compliance, and collaborate with global teams to embed AI capabilities in business workflows.
18+ years of software engineering experience including 3+ years in a management or leadership role.
7+ years experience with Large Language Models and related technologies, plus 2+ years building/deploying GenAI applications in production.
5+ years managing technical teams.
Professional machine learning certifications from multiple cloud providers (preferably Azure or Google).
Experienced technical leader with deep expertise in GenAI, Agentic Engineering, and building enterprise-grade AI systems at scale.
Capable of hands-on contribution in architecture and implementation while managing and guiding cross-functional software and AI teams.
Proven ability to define metrics-driven program goals (OKRs/KPIs) and enforce engineering best practices including AI governance, observability, and responsible AI frameworks.