11:I[832,["669","static/chunks/app/(Engagement)/similar-jobs/%5Bid%5D/page-4943b355e6b5f9b1.js"],"default"] 13:I[5878,["669","static/chunks/app/(Engagement)/similar-jobs/%5Bid%5D/page-4943b355e6b5f9b1.js"],"Image"] 12:T68a,

Location: Bangalore (Hybrid)

ROLE SUMMARY

Engineer, you will own the architecture and delivery of enterprise-grade GenAI

systems that integrate large language models (LLMs), multi-agent workflows, and

embedding-powered retrieval solutions. You will guide engineering pods, define standards,

and drive innovation through scalable, production-ready intelligent applications.

Core Responsibilities

• Architect GenAI systems using LLM APIs, agent orchestration frameworks, and embedding

pipelines at scale

• Design autonomous agent workflows with context management and multi-agent

coordination

• Optimize performance, latency, and accuracy through prompt strategies and retrieval layers

• Lead solution reviews, enforce governance, and ensure alignment with security protocols

• Collaborate with product and platform teams to define reusable patterns and scalable AI

capabilities

• Mentor engineers on design principles, reliability, and prompt lifecycle management

Required Skills

• 4–8+ years in AI/ML engineering with focus on GenAI applications

• Strong expertise in Databricks (Delta Lake, Spark SQL, PySpark) and Snowflake for

scalable data/AI solutions

• Proficiency in Python (v3.11+), LLM APIs (OpenAI, LangChain, LangGraph)

• Hands-on experience with containerization, CI/CD, and cloud-native delivery (Azure

preferred)

• Knowledge of agent orchestration, prompt optimization, and observability frameworks

• Deep understanding of foundational LLM models and their utility

Sr AI Engineer