Agentic Powered Automation Developer

Job Description

Location: Noida & Gurgaon Total Experience: 4 to 12 years(Senior Associate & Manager) Role Overview The Agentic Automation Engineer will develop and implement intelligent automation solutions using agentic frameworks like LangGraph, AutoGen, and CrewAI, integrating generative AI and Retrieval-Augmented Generation (RAG) techniques. This role requires deep expertise in Python, generative AI, and both open-source and closed-source LLMs, along with proficiency in databases and modern automation tools. The ideal candidate will collaborate with cross-functional teams to deliver scalable, high-impact automation workflows that enhance business processes. Key Responsibilities · Design and develop agentic automation workflows using frameworks such as LangGraph, AutoGen, CrewAI, and other multi-agent systems (e.g., MCP, A2A) to automate complex business processes. · Build and optimize Retrieval-Augmented Generation (RAG) pipelines for enhanced contextual understanding and accurate response generation in automation tasks. · Integrate open-source LLMs (e.g. LLaMA) and closed-source LLMs (e.g., OpenAI, Gemini, Vertex AI) to power agentic systems and generative AI applications. · Develop robust Python-based solutions using libraries like LangChain, Transformers, Pandas, and PyTorch for automation and AI model development. · Implement and manage CI/CD pipelines, Git workflows, and software development best practices to ensure seamless deployment of automation solutions. · Work with structured and unstructured data, applying prompt engineering and fine-tuning techniques to enhance LLM performance for specific use cases. · Query and manage databases (e.g., SQL, NoSQL) for data extraction, transformation, and integration into automation workflows. · Collaborate with stakeholders to translate technical solutions into business value, delivering clear presentations and documentation. · Stay updated on advancements in agentic automation, generative AI, and LLM technologies to drive innovation and maintain competitive edge. · Ensure scalability, security, and performance of deployed automation solutions in production environments. Required Qualifications and Skills · Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field. · Experience: o 5+ years of hands-on experience in AI/ML, generative AI, or automation development. o Proven expertise in agentic frameworks like LangGraph, AutoGen, CrewAI, and multi-agent systems. o Experience building and deploying RAG-based solutions for automation or knowledge-intensive applications. o Hands-on experience with open-source LLMs (Hugging Face) and closed-source LLMs (OpenAI, Gemini, Vertex AI). · Technical Skills: o Advanced proficiency in Python and relevant libraries (LangChain, Transformers, Pandas, PyTorch, Scikit-learn). o Strong SQL skills for querying and managing databases (e.g., PostgreSQL, MongoDB). o Familiarity with CI/CD tools (e.g., Jenkins, GitHub Actions), Git workflows, and containerization (e.g., Docker, Kubernetes). o Experience with Linux (Ubuntu) and cloud platforms (AWS, Azure, Google Cloud) for deploying automation solutions. o Knowledge of automation tools (e.g., UiPath, Automation Anywhere) and workflow orchestration platforms. · Soft Skills: o Exceptional communication skills to articulate technical concepts to non-technical stakeholders. o Strong problem-solving and analytical skills to address complex automation challenges. o Ability to work collaboratively in a fast-paced, client-facing environment. o Proactive mindset with a passion for adopting emerging technologies. Preferred Qualifications · Experience with multi-agent coordination protocols (MCP) and agent-to-agent (A2A) communication systems. · Familiarity with advanced generative AI techniques, such as prompt chaining, tool-augmented LLMs, and model distillation. · Exposure to enterprise-grade automation platforms or intelligent process automation (IPA) solutions. · Contributions to open-source AI/automation projects or publications in relevant domains. · Certification in AI, cloud platforms, or automation technologies (e.g., AWS Certified AI Practitioner, RPA Developer).