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This role requires deep expertise in Python development, AI-driven application architectures, and cloud-native technologies to build robust, scalable, and production-ready agentic solutions.\nYou will be responsible for developing backend services, implementing agent orchestration workflows, integrating LLMs and external tools, and building resilient platforms that support enterprise AI use cases.\nKey Responsibilities:\nBackend Development: Design, develop, and maintain scalable backend services and APIs using Python and modern development frameworks.\nAgentic AI Development: Build and support agent orchestration workflows that enable autonomous decision-making, task execution, and multi-step reasoning.\nLLM Integration: Develop integrations with LLM providers such as OpenAI, Gemini, Anthropic, and open-source models to power AI-driven applications.\nRAG Implementation: Build and optimize Retrieval-Augmented Generation (RAG) pipelines leveraging vector databases and enterprise knowledge sources.\nPlatform Engineering: Develop resilient, high-performance platform services that support secure and scalable AI deployments.\nTool Integration: Create Python-based tools and connectors that enable agents to interact with APIs, databases, enterprise applications, and external services.\nTesting & Evaluation: Implement automated testing, evaluation frameworks, and quality controls to ensure reliability and consistency of AI systems.\nPerformance Optimization: Optimize application performance, latency, scalability, and infrastructure utilization across AI workloads.\nRequired Skills & Qualifications:\n10+ years of experience in software engineering with strong expertise in Python development.\nStrong experience developing REST APIs, microservices architectures, and event-driven systems.\nHands-on experience with Agentic AI frameworks such as LangGraph, CrewAI, AutoGen, or Agent Development Kit (ADK).\nExperience building and supporting RAG-based applications and enterprise AI solutions.\nStrong knowledge of LangChain, LlamaIndex, LangSmith, and LangFlow.\nExperience working with LLMs including OpenAI, Gemini, Anthropic, Llama, or similar models.\nDeep understanding of prompt engineering, function calling, tool integration, agent orchestration, and evaluation techniques.\nExperience with vector databases such as Pinecone, Weaviate, Chroma, or Milvus.\nStrong proficiency in PostgreSQL, MySQL, MongoDB, Redis, and database optimization techniques.\nExperience with cloud platforms (AWS, Azure, or GCP) and cloud-native application development.\nFamiliarity with Docker, Kubernetes, and containerized deployment patterns.\nExperience implementing CI/CD pipelines using tools such as Jenkins, GitHub Actions, or GitLab CI.\nExperience with monitoring, logging, and observability tools for production systems.\nCompensation, Benefits and Duration\nMinimum Compensation: USD 39,000\nMaximum Compensation: USD 137,000\nCompensation is based on actual experience and qualifications of the candidate. 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