We are looking for a Senior Generative AI Engineer to architect and build production-grade LLM applications using modern GenAI frameworks.
If you have strong hands-on experience with LLMs, Prompt Engineering, RAG, Agentic Workflows, and LangChain/LangGraph, this role is for you.
You will design scalable AI systems deployed on cloud platforms (AWS, Azure, or GCP) and collaborate closely with product and business teams to deliver real-world AI solutions.
What You’ll Do
Build & Optimize LLM Solutions
Design, fine-tune, and deploy large language model (LLM) systems
Implement advanced techniques:
Prompt engineering optimization
Retrieval-Augmented Generation (RAG)
Agent-based AI architectures
Improve accuracy, reduce hallucinations, and optimize cost/performance
Own the Codebase
Write high-quality, scalable Python code
Develop modular workflows using LangChain / LangGraph
Optimize SQL-based data retrieval pipelines
Establish strong testing and performance standards
Cloud & Deployment
Deploy GenAI applications on AWS / Azure / GCP
Build CI/CD pipelines for AI systems
Optimize compute usage (GPU/CPU efficiency)
Ensure production-grade reliability and monitoring
Cross-Functional Collaboration
Work closely with Product Managers, Data Scientists & Business SMEs
Translate business problems into AI solutions
Communicate complex AI concepts clearly to non-technical stakeholders
Leadership (Staff-Level Focus)
Provide technical mentorship
Define architecture best practices
Guide GenAI strategy and innovation roadmap
Required Qualifications
8+ years experience building ML systems (Senior)
10+ years experience (Staff)
2+ years hands-on experience in LLMs & Generative AI
Prompt Engineering
RAG
Agentic workflows
Expert proficiency in:
Python
LangChain / LangGraph
SQL
Experience deploying AI systems on AWS, Azure, or GCP
Strong communication & stakeholder collaboration skills
Nice to Have
Experience with vector databases (Pinecone, FAISS, Weaviate, etc.)
Experience with OpenAI / Anthropic / open-source LLMs
MLOps experience
Enterprise-scale AI deployment experience
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
IT Services and IT Consulting
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