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Brand recognition, metro Bangalore location, and specialized ML role create medium applicant competition.
Highly domain-specific ML and agentic systems expertise reduces cross-industry transferability.
Explicit 6–9 years and mandatory LLM/agent production experience enforce strict filtering.
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Translate advanced LLM and multi-agent AI research into reliable, enterprise-scale production systems.
Design and deploy scalable multi-agent workflows, runtime environments, and data pipelines for low-latency, high-efficiency autonomous decision-making.
Own end-to-end agentic frameworks, including API microservices, telemetry systems, and integration of AI primitives into product ecosystems.
6–9 years of professional experience in software engineering and machine learning development, with hands-on production deployment of LLM-based or agentic systems.
Degree in Computer Science, Artificial Intelligence, Data Science, or a related quantitative field.
Proven experience building and maintaining large-scale Machine Learning and backend architectures.
Not explicitly mentioned in the JD: Notice period requirement.
Experienced in productionizing autonomous, stateful software applications built on LLMs with deterministic guardrails.
Strong in distributed systems architecture managing asynchronous workflows, message queues, and low-latency API microservices for multi-agent systems.
Capable of leading technical AI initiatives including prototyping new AI stacks, LLM benchmarking, vector database evaluation, and cross-functional alignment.