Agentic AI Developer(4-8 Years)

About Company

Job Summary:

Agentic AI Developer

Key Responsibilities:

• Design and implement

  agentic AI systems

  using state-of-the-art language models (e.g. GPT-4, Claude, Mistral, etc.)
• Architect and manage agent memory, planning, reflection, and tool use capabilities
• Integrate LLMs with APIs, databases, web browsers, vector stores, and custom tools
• Implement feedback loops, autonomy thresholds, and environment sensing
• Build multi-agent or swarm systems for collaborative or competitive task execution
• Monitor, evaluate, and improve agent behavior in live or simulated environments
• Collaborate with research scientists, product engineers, and stakeholders to bring agentic applications to life
• Keep up with latest research in agentic AI, cognitive architectures, and reinforcement learning 

Required Qualifications:

• 5+ years of

  software engineering experience

  , including designing and maintaining production-grade systems
• Proficiency in

  Python

  , with clean coding practices and a deep understanding of software design patterns
• Proven experience with

  system architecture

  , including designing scalable, modular, and maintainable components
• Strong

  debugging skills

  — able to trace complex agent behaviors, diagnose failure modes, and implement robust error handling
• Demonstrated ability to

  solve complex, open-ended problems

  involving multiple interacting components (e.g. memory, planning, tool use, and user input)
• Hands-on experience integrating

  LLMs

  (e.g., GPT-4, Claude, Mistral) via API, including prompt design, chaining, and tuning
• Familiarity with

  agent frameworks

  such as LangChain, AutoGen, CrewAI, or custom-built orchestration systems
• Experience with

  memory systems

  such as vector databases (Pinecone, FAISS, Weaviate, etc.)
• Understanding of

  asynchronous workflows

  , agent state management, and long-running task execution
• Ability to write clean, testable, and well-documented code in collaborative environments (Git, CI/CD, code reviews) 

Nice to Have:

• Experience with

  multi-agent systems

  , simulations, or game-theoretic environments
• Background in

  cognitive architectures

  (e.g., ACT-R, Soar, OpenCog)
• Knowledge of

  RLHF

  , active learning, or autonomous fine-tuning
• Exposure to tools like

  AutoGPT, BabyAGI, ReAct, or Voyager

• Contributions to open-source agentic AI projects