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Job Title: Senior AI Lead
Location: Bangalore
Experience: 8-12 Years
Qualification: Any Graduation
Looking for immediate joiners or who can join in 15 days
About the Client
ARAs Client is an innovation-led technology organization focused on delivering enterprise-grade AI solutions powered by cutting-edge generative AI and machine learning technologies. The company emphasizes scalable architecture, rapid experimentation, and real-world AI adoption across industries.
Role Summary
We are hiring a Senior AI Developer with deep expertise in LLM-based and Agentic AI systems. This role combines hands-on development with architectural leadership, focusing on building intelligent AI systems that go far beyond traditional chatbot implementations.
You will design and deliver multi-agent AI systems, integrate LLMs with external tools and data sources, and ensure production-grade scalability and reliability.
Key Responsibilities
Must-Have Qualifications
Nice-to-Have
Job ID: 145370407
Skills:
Python, AWS, Agentic AI frameworks, Agent orchestration on cloud platforms, RAG Retrieval-Augmented Generation, MLOps best practices, semantic search, Low-code No-code agent building, CI CD pipelines, Azure Cognitive Search, Microsoft Bot Framework, Azure Cognitive Services, Google Perplexity
Skills:
Code, Salesforce Agent force, AI coding platforms, Copilot, OpenAI Codex, MCP or agent orchestration patterns, Claude, AI-enabled systems, Oracle AI Agent Studio, LLM-based tooling
Skills:
AWS, Python, Multi-agent orchestration, Azure AI Agent Service Copilot Studio, Azure Cognitive Services, Azure Cognitive Search, Agentic AI frameworks, Advanced RAG Semantic Search implementations, MCP Model Context Protocol, semantic search, Microsoft Bot Framework, Responsible AI principles, RAG Retrieval-Augmented Generation, Google Perplexity, CI CD pipelines, MLOps best practices, Low-code No-code agent building
Skills:
bedrock , Java, Microservices, AWS, Python, Azure, AI pipelines, evaluation frameworks, OpenAI, copilots, safe execution patterns, quality gates, cloud platforms, document intelligence, embeddings, API chaining, DevOps practices, guardrails, LLM-based systems, vector databases, serverless, retrieval agents, workflow orchestration, prompt engineering, workflow automation
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