Job Summary
We are seeking a GenAI candidate with 7+ years of experience to build GenAI solutions using LLMs, RAG, and Langchain to address real-world business problems. Design and implement autonomous agents capable of task planning, decomposition, and tool/API invocation

Key Responsibilities
AI Solution Development: Build GenAI solutions using LLMs, RAG, and Langchain to address real-world business problems.
Agentic AI Systems: Design and implement autonomous agents capable of task planning, decomposition, and tool/API invocation.
Backend & Orchestration Services: Develop robust Python-based services and orchestrators for managing model interactions, task workflows, and contextual data.
Cloud-Based Deployment: Deploy and optimize AI models on Azure OpenAI and GCP Vertex AI, ensuring scalability, reliability, and performance.
API Integration: Integrate OpenAI and other GenAI services into enterprise applications via REST APIs and cloud-native SDKs.
Prompt Engineering & Fine-Tuning: Craft effective prompts and collaborate on model fine-tuning to align LLMs with domain-specific tasks.




Performance Tuning: Optimize latency, cost, and throughput of GenAI models running on cloud platforms.
Documentation & Knowledge Sharing: Maintain clear documentation and mentor junior team members on GenAI concepts, tools, and best practices.

Required Qualifications
7+ years of experience in AI/ML, with at least 3+ years hands-on in Generative AI / LLM systems.
Proven expertise in Lang chain, OpenAI APIs, Azure OpenAI, and GCP Vertex AI.
Robust Python programming skills; experience building REST APIs and microservices.
Deep knowledge of LLM chaining, RAG, agent-based systems, and task orchestration.
Experience deploying scalable AI systems in Azure and GCP environments.
Familiarity with tools like FAISS, Chroma, Pinecone, Weaviate, or other vector stores

Disclaimer: The following job description serves as an informative reference for the tasks you may be required to perform. However

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