Senior AI Engineer (Agentic Workflows & Multi-Agent Systems)

Role Overview

We are seeking a visionary Senior AI Engineer to spearhead our "Agentic AI" initiative. This role focuses on moving beyond static LLM prompts toward dynamic, autonomous agentic setups that can reason, use tools, and collaborate to solve complex business problems. You will design and implement sophisticated multi-agent architectures that automate end-to-end workflows, ranging from complex financial document analysis to automated customer interactions and fraud detection.

Key Responsibilities

- Agentic Architecture Design: Lead the design and implementation of agentic frameworks (e.g., LangGraph, AutoGen, CrewAI) to create autonomous agents capable of multi-step reasoning and planning.
- Tool Integration & Function Calling: Develop and optimize "tools" for agents to interact with, including internal APIs, databases (SQL/NoSQL), and external web services.
- Multi-Agent Orchestration: Build systems where multiple specialized agents collaborate (e.g., a "Researcher" agent passing structured data to a "Reviewer" agent) to ensure high-fidelity outputs.
- Cognitive Architecture: Implement advanced RAG (Retrieval-Augmented Generation) patterns within agentic loops, ensuring agents have access to relevant, up-to-date context from our document repositories.
- Production Deployment & MLOps: Deploy agentic workflows as scalable microservices within AWS, ensuring robust error handling, observability, and cost-efficient execution.
- Continuous Optimization: Establish evaluation frameworks to measure agent performance, reliability, and "hallucination" rates in production environments.

Required Skills & Qualifications

- Experience:



2-4 years of experience in AI/ML engineering, with a robust focus on LLM-based applications and emerging agentic patterns.
- Agentic Frameworks: Proven experience with frameworks like LangChain/LangGraph, AutoGen, CrewAI, or Semantic Kernel.
- Technical Stack: Expert-level Python skills, with deep knowledge of asynchronous programming (FastAPI) and orchestration tools like Airflow.
- LLM Proficiency: Deep understanding of state-of-the-art LLMs (GPT-4, Claude 3.5, Llama 3) and their specific capabilities regarding function calling and reasoning.
- Infrastructure: Experience with AWS (Lambda, ECS, Bedrock), Docker, and building resilient distributed systems.

Education: Bachelors or Masters degree in Computer Science, AI, or a related technical field.

Disclaimer:
This job description is intended to outline the general nature and key responsibilities of the position. It is not intended to be an exhaustive list of all duties, responsibilities, or qualifications associated with the role. The responsibilities and qualifications described may be subject to change, and other duties may be assigned as needed. Employment is at-will, meaning the employee or the employer may terminate the employment relationship at any time, with or without cause, and with or without notice.

Data Utilization Disclaimer:
By applying for this position, you acknowledge and agree that any personal data you provide may be used for recruitment and employment purposes. The data collected will be stored and processed in accordance with our privacy policy and applicable data protection laws. Your information will only be shared with relevant internal stakeholders and will not be disclosed to third parties without your consent, unless required by law.

📌 Senior AI Engineer (Agentic Workflows & Multi-Agent Systems) (Karnataka)
🏢 Krazy Bee Services
📍 Karnataka