We are seeking a forward-thinking and detail oriented Agentic AI Developer to join our AI Research and Development team. In this role, you will design, implement, and optimize autonomous AI agents capable of reasoning, decision-making, planning, and interacting with dynamic environments and toolchains. You will be building cutting-edge systems at the intersection of machine learning, cognitive architectures, and software engineering. You will also evaluate, guide, and help evolve agentic AI systems, AI agents with autonomous, goal-driven behaviour and decision-making abilities.

KEY RESPONSIBILITIES

• Design and develop agentic AI systems with capabilities such AS autonomy and goal-directed behaviour, long-term memory and planning, self-reflection and reasoning loops, dynamic tool use and API integrations.
• Implement architectures like ReAct, AutoGPT, BabyAGI, and custom agent frameworks.
• Integrate foundation models (e.g., GPT-4, Claude, Gemini) into agent pipelines.
• Collaborate with product and engineering teams to deploy agents in real-world applications (e.g., customer support, RPA, research assistants).
• Optimize agent performance across reasoning speed, accuracy, and cost.
• Translate complex agent behaviours into clear, actionable reports for technical and non-technical stakeholders.
• Help design test scenarios and benchmark protocols for agent evaluation.
• Contribute to research, papers, or internal documentation on agent design strategies.
• Stay current with emerging trends in LLMs, autonomous agents, and neuro-symbolic AI

EXPERIENCE, SKILLS & COMPETENCIES

• Strong programming skills in Python and experience with LLM toolkits (LangChain, OpenAI API, HuggingFace)
• Solid understanding of agent design patterns: planner-executor loops, tool use, memory, chaining
• Experience with vector databases, embeddings, and semantic retrieval (e.g., Pinecone, Weaviate, FAISS)
• Familiarity with cognitive science or reinforcement learning concepts
• Experience building applications using LLMs or multi-agent systems
• Ability to work independently and iteratively in a fast-paced, exploratory R&D environment
• Research experience in AI, ML, NLP, or multi-agent systems
• Experience with open-source agents (AutoGPT, CrewAI, LangGraph)
• Understanding of ethical and safety considerations for autonomous AI
• Contributions to open-source agentic AI frameworks or community projects