About the Role
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 Youll 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
About the Role 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 d...
About the Role
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 Youll 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
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