Agentic AI Developer – LLM Systems & Automation
Experience: 3–5 Years
Location: Remote (WFH)
Mode of Engagement: Full-time
No of Positions: 4
Educational Qualification: B.E./B.Tech/M.E./M.Tech in Computer Science, AI/ML, or related
Industry: IT – AI/ML & Automation Services
Notice Period: Immediate Joiner
What 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.