APA Manager

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.

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).

Mandatory skill sets:

Agentic, LLM, RAG, AIML, LangGchain

Preferred skill sets:

Agentic, LLM, RAG, AIML, LangGchain, Gen AI