Agentic AI Developer

Location - Bengaluru

Years of Exp - 4 - 7 Years

Role Summary:

Induct team is looking for a highly skilled Agentic AI Developer to join our team. The ideal candidate will have deep experience in building autonomous AI systems that can independently reason, plan, and act to accomplish complex goals. As a specialist in this rapidly evolving field, you will play a crucial role in creating the next generation of proactive, intelligent systems that can automate complex workflows and drive significant business impact.

Responsibilities

• Architect, design, and deploy end-to-end agentic AI systems that enable autonomous decision-making, task decomposition, and adaptive behavior in real-world or simulated environments.
• Orchestrate and manage multi-agent frameworks using tools like LangGraph, LangChain, AutoGen, or CrewAI, enabling agents to collaborate and communicate effectively.
• Integrate LLMs, vector databases (Pinecone, Milvus), and external tools/APIs to provide agents with memory, context, and the ability to perform real-world actions.
• Implement reasoning and planning loops that allow agents to break down complex objectives into executable steps and dynamically adjust plans based on feedback.
• Design and implement robust safety guardrails and ethical AI principles to ensure agents operate within defined boundaries.
• Deploy, scale, and monitor agentic systems in production environments using cloud platforms (AWS, GCP, Azure), containerization (Docker), and MLOps practices.
• Collaborate with cross-functional teams to translate business requirements into effective, AI-driven solutions.
• Stay current with the rapidly evolving fields of agentic AI, LLMs, and related research to drive innovation.

Required qualifications

• Proven experience in software or AI/ML development, with a focus on autonomous agents or multi-agent systems.
• Strong proficiency in Python, including experience with asynchronous programming and AI frameworks.
• Demonstrated experience with agent orchestration frameworks like LangChain, LangGraph, AutoGen, or CrewAI.
• Hands-on experience integrating LLMs with vector databases for Retrieval-Augmented Generation (RAG).
• Solid understanding of system design, distributed systems, and modern API development.
• Proficiency with cloud platforms (AWS, GCP, Azure) and MLOps practices for deploying scalable AI solutions.
• Excellent problem-solving, analytical, and communication skills

Preferred qualifications

• Background in reinforcement learning, cognitive architectures, or symbolic reasoning.
• Experience with GPU programming for ML workloads using frameworks like PyTorch or TensorFlow.
• Familiarity with cybersecurity telemetry or threat intelligence frameworks.
• Advanced degree in Computer Science, Artificial Intelligence, or a related field.