Agentic AI Developer – LLM Systems

3 weeks ago

Delhi, India AIMLEAP Full time

Agentic AI Developer – LLM Systems & AutomationExperience: 3–5 YearsLocation: Remote (WFH)Mode of Engagement: Full-timeNo of Positions: 4Educational Qualification: B.E./B.Tech/M.E./M.Tech in Computer Science, AI/ML, or relatedIndustry: IT – AI/ML & Automation ServicesNotice Period: Immediate JoinerWhat We Are Looking For- AI & LLM Development: Strong hands-on experience in building and fine-tuning LLM-driven and agentic AI systems using frameworks like LangChain, LlamaIndex, or DSPy, with focus on reasoning, memory, and tool chaining.- Backend Engineering: Solid Python development skills with expertise in designing FastAPI/Django-based APIs, managing data pipelines, and integrating LLM modules into scalable backend systems.- Autonomous Execution: Proven ability to independently design, implement, and deploy GenAI workflows — taking ownership from prototype to production without senior handholding.Responsibilities- Design, build, and optimize LLM-powered agentic systems that leverage memory, context reasoning, and dynamic tool invocation.- Implement multi-agent orchestration workflows integrating APIs, databases, and scrapers using frameworks like LangChain, LlamaIndex, or AutoGen.- Develop modular AI pipelines and integrate them with backend services using Python, FastAPI, or Flask.- Work on model evaluation, context handling, and prompt engineering to enhance reasoning and accuracy.- Deploy, test, and scale models on Dockerized or cloud environments (AWS/GCP).- Stay aligned with emerging trends in LLM reasoning frameworks, agentic design, and open-source AI ecosystems.Qualifications- 3–5 years of experience in AI/ML, backend, or applied LLM system development.- Strong Python programming skills with exposure to Transformers, LangChain, LlamaIndex, or DSPy.- Understanding of LLM architectures, tool chaining, context memory, and reasoning strategies (ReAct, Tree of Thought, etc.).- Experience with FastAPI, Docker, PostgreSQL, Git, and production-grade code practices.- Ability to independently manage AI projects from concept to deployment.- Strong analytical, debugging, and problem-solving skills.- Good communication and collaboration skills in distributed environments.

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