Agentic ai developer – llm systems

7 days ago

Ahmedabad, 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 ForAI & LLM Development: Strong hands-on experience in building and fine-tuning LLM-driven and agentic AI systems using frameworks like Lang Chain, Llama Index, or DSPy, with focus on reasoning, memory, and tool chaining.Backend Engineering: Solid Python development skills with expertise in designing Fast API/Django-based APIs, managing data pipelines, and integrating LLM modules into scalable backend systems.Autonomous Execution: Proven ability to independently design, implement, and deploy Gen AI workflows — taking ownership from prototype to production without senior handholding.ResponsibilitiesDesign, 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 Lang Chain, Llama Index, or Auto Gen.Develop modular AI pipelines and integrate them with backend services using Python, Fast API, 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.Qualifications3–5 years of experience in AI/ML, backend, or applied LLM system development.Strong Python programming skills with exposure to Transformers, Lang Chain, Llama Index, or DSPy.Understanding of LLM architectures, tool chaining, context memory, and reasoning strategies (Re Act, Tree of Thought, etc.).Experience with Fast API, Docker, Postgre SQL, 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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