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AI Summary
Design, develop, and deploy production-grade Generative AI solutions and RAG pipelines for enterprise applications. Lead the full lifecycle of GenAI POCs, from architecture and prompt optimization to deployment on Azure and Databricks.
Position: GenAI Engineer
Experience: 4 - 12 Years
Location: Bengaluru (Remote)
Notice Period: Immediate Joiners Only
About the Role
We are looking for an experienced GenAI Technical Lead with a proven track record of delivering production-grade Generative AI solutions for enterprise applications. The ideal candidate should possess deep expertise in designing, developing, and deploying end-to-end GenAI solutions, with mandatory exposure to Databricks and Azure environments.
Key Responsibilities:
Design, develop, and deploy end-to-end Generative AI solutions for enterprise use cases.
Architect and implement Retrieval-Augmented Generation (RAG) pipelines.
Lead complete GenAI POC development, including solution architecture, development, testing, and deployment.
Design and optimize prompt engineering strategies for improved LLM performance.
Develop and orchestrate Large Language Model (LLM) workflows and agent-based AI systems.
Build scalable backend services and APIs using Python, FastAPI, or Flask.
Integrate GenAI applications with enterprise platforms, databases, and business systems.
Deploy and manage applications on Microsoft Azure, including Web Apps, Function Apps, and Virtual Machines.
Work with Databricks for data engineering pipelines, model workflows, and AI solution integration.
Collaborate with business stakeholders, architects, and cross-functional teams to deliver AI-driven solutions.
Mentor junior developers and provide technical leadership throughout the project lifecycle.
Design, develop, and deploy end-to-end Generative AI solutions for enterprise use cases.
Architect and implement Retrieval-Augmented Generation (RAG) pipelines.
Lead complete GenAI POC development, including solution architecture, development, testing, and deployment.
Design and optimize prompt engineering strategies for improved LLM performance.
Develop and orchestrate Large Language Model (LLM) workflows and agent-based AI systems.
Build scalable backend services and APIs using Python, FastAPI, or Flask.
Integrate GenAI applications with enterprise platforms, databases, and business systems.
Deploy and manage applications on Microsoft Azure, including Web Apps, Function Apps, and Virtual Machines.
Work with Databricks for data engineering pipelines, model workflows, and AI solution integration.
Collaborate with business stakeholders, architects, and cross-functional teams to deliver AI-driven solutions.
Mentor junior developers and provide technical leadership throughout the project lifecycle.
Required Skills & Qualifications :
Mandatory Technical Skills
4+ years of overall software development experience.
Hands-on experience delivering production-level Generative AI solutions (POCs or personal projects alone will not be considered).
Strong expertise in:
Retrieval-Augmented Generation (RAG)
Prompt Engineering
LLM workflows and orchestration
Enterprise GenAI solution development
Strong programming skills in Python.
Experience building REST APIs using FastAPI, Flask, or similar frameworks.
Proven ability to build complete GenAI solutions from scratch.
Mandatory Technical Skills
4+ years of overall software development experience.
Hands-on experience delivering production-level Generative AI solutions (POCs or personal projects alone will not be considered).
Strong expertise in:
Retrieval-Augmented Generation (RAG)
Prompt Engineering
LLM workflows and orchestration
Enterprise GenAI solution development
Strong programming skills in Python.
Experience building REST APIs using FastAPI, Flask, or similar frameworks.
Proven ability to build complete GenAI solutions from scratch.
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