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This role requires a strong blend of backend engineering expertise, AI application development, and problem-solving skills to deliver scalable, secure, and production-ready solutions.\nYou will be responsible for developing AI-powered services, implementing agent workflows, integrating enterprise systems and external tools, and contributing to the evolution of the platform.\nKey Responsibilities:\nBackend Development: Design, develop, and maintain scalable backend services, APIs, and platform components using Python and related frameworks.\nAgent Development: Build and implement agent orchestration workflows using modern frameworks such as LangGraph, CrewAI, AutoGen, or similar technologies.\nLLM Integration: Integrate and optimize LLM-powered capabilities using platforms such as OpenAI, Gemini, Anthropic, and open-source models.\nRAG Implementation: Develop and maintain Retrieval-Augmented Generation (RAG) solutions leveraging enterprise knowledge bases and vector databases.\nTool Integration: Create tools, connectors, and APIs that enable agents to interact with databases, business systems, and third-party applications.\nPlatform Development: Contribute to the development of scalable, resilient, and secure AI platform capabilities that support enterprise deployments.\nTesting & Evaluation: Develop testing strategies and evaluation frameworks to measure agent accuracy, reliability, performance, and overall effectiveness.\nPerformance Optimization: Optimize AI workflows, token utilization, model selection, and infrastructure to improve latency and cost efficiency.\nRequired Skills & Qualifications:\n6-9 years of experience in software development with strong expertise in Python.\nHands-on experience with Python frameworks such as FastAPI, Flask, or Django.\nStrong experience in developing REST APIs, microservices, and backend applications.\nExperience working with Agentic AI frameworks such as LangGraph, CrewAI, AutoGen, Agent Development Kit (ADK), or similar technologies.\nExperience building and supporting RAG-based applications and AI-powered solutions.\nHands-on experience with LangChain, LlamaIndex, LangSmith, or LangFlow.\nWorking knowledge of LLMs including OpenAI, Gemini, Anthropic, Llama, or equivalent models.\nStrong understanding of prompt engineering, function calling, tool integration, and agent orchestration patterns.\nExperience with vector databases such as Pinecone, Weaviate, Chroma, or Milvus.\nProficiency in relational databases (PostgreSQL, MySQL) and NoSQL databases (MongoDB, Redis).\nExperience with cloud platforms such as AWS, Azure, or GCP.\nFamiliarity with Docker, Kubernetes, and containerized application deployments.\nExperience working with CI/CD pipelines and tools such as Jenkins, GitHub Actions, or GitLab CI.\nCompensation, Benefits and Duration\nMinimum Compensation: USD 35,000\nMaximum Compensation: USD 123,000\nCompensation is based on actual experience and qualifications of the candidate. 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