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.
Experience :
4+ years of hands-on experience in AI / ML, generative AI, or automation development.
Proven expertise in agentic frameworks like LangGraph, AutoGen, CrewAI, and multi-agent systems.
Experience building and deploying RAG-based solutions for automation or knowledge-intensive applications.
Hands-on experience with open-source LLMs (Hugging Face) and closed-source LLMs (OpenAI, Gemini, Vertex AI).
Technical Skills :
Advanced proficiency in Python and relevant libraries (LangChain, Transformers, Pandas, PyTorch, Scikit-learn).
Strong SQL skills for querying and managing databases (e.g., PostgreSQL, MongoDB).
Familiarity with CI / CD tools (e.g., Jenkins, GitHub Actions), Git workflows, and containerization (e.g., Docker, Kubernetes).
Experience with Linux (Ubuntu) and cloud platforms (AWS, Azure, Google Cloud) for deploying automation solutions.
Knowledge of automation tools (e.g., UiPath, Automation Anywhere) and workflow orchestration platforms.
Soft Skills :
Exceptional communication skills to articulate technical concepts to non-technical stakeholders.
Strong problem-solving and analytical skills to address complex automation challenges.
Ability to work collaboratively in a fast-paced, client-facing environment.
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).
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