SDE 3 - AI

We are looking for a highly skilled SDE 3 - AI Engineer to design and build agentic AI systems that orchestrate intelligent decision-making across warehouse automation and supply chain workflows. This role requires hands-on expertise in architecting, developing, and orchestrating multi-agent AI systems that operate in real-time, high-scale environments involving robotics, optimization, and dynamic decisioning.

Responsibilities:

• Architect and develop agentic AI systems for real-time orchestration of workflows, robots, and decision engines.
• Design multi-agent frameworks for planning, reasoning, and execution across distributed systems.
• Build and optimize LLM-powered agents, tool-using agents, and autonomous workflows.
• Develop orchestration layers for AI agents interacting with physical systems (robots, sensors, APIs).
• Implement memory, planning, and reasoning pipelines for autonomous agents.
• Work on real-time decision systems involving scheduling, routing, and optimization.
• Collaborate with product, robotics, and platform teams to integrate AI into core systems.
• Ensure scalability, reliability, and performance of AI-driven systems in production.
• Stay updated with advancements in agentic AI, LLMs, and autonomous systems.

Requirements:

• 5-8 years of experience in backend / AI engineering.
• Strong experience in Agentic AI / Autonomous AI systems (must-have).
• Hands-on experience with LLM frameworks (LangChain, LlamaIndex, Semantic Kernel, etc. ), Multi-agent orchestration frameworks, Prompt engineering, tool use, and agent workflows.
• Strong programming skills in Python (preferred) or Java.
• Experience with distributed systems and system design at scale.
• Knowledge of event-driven architectures, microservices, and APIs.
• Experience with vector databases, embeddings, and retrieval systems.
• Familiarity with real-time systems / optimization problems (plus).

Good to Have:

• Experience in robotics, logistics, or supply chain AI systems.
• Exposure to reinforcement learning, planning systems, or simulation environments.
• Experience integrating AI systems with hardware or IoT systems.
• Knowledge of graph-based reasoning or decision engines.