- Posted 16 hours ago
- Be among the first 10 applicants
Job Description
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
More Info
Key Skills
LangChain
Prompt optimization
Agent orchestration
Cloud-native delivery
LangGraph
Observability frameworks
LLM APIs
Delta Lake
OpenAI
Python v3.11





