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Mid-level ML role in Bangalore with broad LLM/fullstack requirements increases applicant competition.
Core ML/LLM engineering skills are transferable, but preferred regulated-domain experience creates moderate industry bias.
Explicit 5–7 years plus mandatory LLM/MCP/Python, microservices and data platform skills create strict filters.
Design and implement AI/ML solutions using technologies like LangChain, LangGraph, and foundational models to optimize regulatory reporting workflows and reduce manual effort.
Lead development and technical implementation of MCP servers and integrate AI agents with enterprise applications, ensuring scalable microservices-based application architecture.
Provide technical leadership and mentorship on AI, LLM, agentic technologies, and engineering best practices, while applying Responsible AI and AI governance principles across development lifecycle.
5+ years of software engineering experience including application development, frontend/backend engineering, microservices, and architecture/design principles.
Strong hands-on experience with AI/ML technologies: LangChain, LangGraph, Gradient Boosting, Random Forest, and LLM frameworks/APIs such as OpenAI, Claude.
Proficient programming skills in Python and frontend frameworks (Angular, React, Node.js), with strong SQL and database knowledge (Oracle, Snowflake, Databricks).
Work Mode: Hybrid (3 days in office at Bangalore, Chennai or Hyderabad; 2 days WFH); Work Experience Required: 5-7 years.
Experienced in integrating AI agents and LLMs with enterprise systems, APIs, and databases, with knowledge of RAG, vector databases, embeddings, and prompt engineering.
Demonstrated capability to lead teams technically and influence adoption of emerging AI and technology solutions within regulated industries like banking or financial services.
Strong skills in designing scalable microservices applications and applying Responsible AI and AI governance/security standards in development.