Job_Description":"

Key Responsibilities

Research and implement Generative AI use cases using LLMs (text, voice, image, or multimodal).

Build prototypes using frameworks such as LangChain, LlamaIndex

Design and optimize prompts for accuracy, safety, and performance.

Implement RAG (Retrieval\u2011Augmented Generation) pipelines using vector databases.

Integrate AI models via APIs or open\u2011source models (OpenAI, Azure OpenAI, Hugging Face, local LLMs).

Work on AI agents , tools, and orchestrations (function calling, workflows).

Evaluate model outputs using metrics like relevance, hallucination rate, latency, and cost.

Assist in deploying GenAI applications using Docker and cloud platforms preferably Azure.

Collaborate with product, data, and engineering teams

Document experiments, findings, and best practices.

Mentor engineers and drive best practices

Requirements
Required Skills

3+ years of professional experience and 2+ years of experience in GenAI.

Strong experience in Python or Java

Hands-on with LLMs, prompt engineering, and RAG

Experience with LangChain, LlamaIndex, or similar

Knowledge of vector databases (FAISS, Pinecone, etc.)

Experience with cloud platforms (Azure preferred)

Understanding of microservices and distributed systems

Basic experience with Git and REST APIs.

Ability to read research blogs or documentation and implement ideas quickly.

Benefits
Benefits

Hands\u2011on exposure to modern GenAI stacks

Certificate / Letter of Recommendation

Access to real\u2011world datasets and use cases

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Staff Software Engineer - GenAI

Job Description

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