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Tier-1 brand, mid-level AI/ML role in a metro attracts many qualified applicants.
ML and agent skills transfer across industries, but finance security and enterprise integration increase sensitivity.
Requires 3+ years, ML/LLMOps expertise, secure enterprise practices, and specific tooling, so strict filters apply.
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Design, develop, test, and troubleshoot AI/ML and agentic systems including multi-agent applications and Agentic Retrieval-Augmented Generation (RAG) pipelines.
Build and maintain secure, scalable production code focusing on prompt/tool orchestration, state management, and fallback strategies.
Develop and implement model and agent evaluation processes, telemetry dashboards, and integrate agents with enterprise systems ensuring security and auditability.
3+ years of applied software engineering experience with formal training or certification.
Hands-on experience using enterprise-authorized AI-assisted software development tools with ability to validate AI-generated code.
Proficiency in one or more programming languages such as Python, Java, TypeScript/Node.js, or Go.
Strong knowledge of Software Development Life Cycle including MLOps/LLMOps and experience in agile methodologies, API design, distributed systems, and database querying.
Experienced in AI/ML technologies including LLMs, agent orchestration, and retrieval systems with working knowledge of Agentic RAG concepts and tool/function calling patterns.
Familiar with responsible AI practices addressing data sensitivity, security, and safe automation within engineering workflows.
Skilled in integrating AI agents with enterprise systems including APIs and MCP-based connectors, focusing on security controls and system scalability.