Job Description:

- Autonomous AI Agent Development: Robust conceptual grasp of leveraging LLMs and agentic AI frameworks to develop collaborative AI agents and orchestrate agent interactions.

- Stateful Agents: Clear understanding of designing agents with long and short-term memory capacities, data handling, and knowledge retention.

- Agent Contextualization: Comprehensive knowledge of methods for adapting LLMs or using RAG (Retrieval-Augmented Generation) to incorporate organisation-specific context and manage nuanced requirements.

- Self-Learning and Reinforcement: Ability to articulate how AI agents can be designed for self-improvement and continuous learning.

- Comprehensive Interface Development: Awareness of end-to-end interface requirements, including support for multi-modal inputs (voice, video), browser automations, and seamless user interaction.

- Traceability and Explainability: Capability to ensure, demonstrate and communicate transparency and explainability within the AI process.

- Ideal Candidate Profile

- Education:



Degree in Computer Science, AI, Machine Learning, Data Science or similar.

- Experience: Minimum 5 years, with at least 3 years focused on AI/machine learning, GenAI, RAG, or agentic platforms. Deep technical understanding is essential; hands-on implementation is desirable but not mandatory.

- In-depth knowledge of LLM/agent frameworks like Azure OpenAI, Langchain, Autogen, Langgraph, Crew AI.

- Understanding of how RAG-based GenAI solutions are developed, and how knowledge layers for AI agents are structured (e.g., vector db, knowledge graphs,etc.,).

- Familiarity with design and operation of sandbox environments, browser automations, and workspace tools for agentic solutions.

- Prior experience as a Business Analyst or Project Manager in AI/tech projects; familiarity with project delivery life cycles such as Agile.

- Banking experience is beneficial.

📌 AI Business Analyst (Bengaluru)
🏢 Acme Services Private
📍 Bengaluru