Senior Generative AI Developer (4+ years)

Job Title : Agentic AI Developer

Experience : 4–6 Years

Location : Remote

Employment Type : Contract

Job Summary We are seeking a highly skilled Agentic AI Developer with a strong background in engineering and hands-on experience in building, orchestrating, and deploying intelligent AI agents. The ideal candidate will have deep expertise in Python-based Generative AI (GenAI) development, multi-agent frameworks , and LLM integrations to design autonomous, goal-driven AI systems capable of reasoning, planning, and dynamic tool usage.

Key Responsibilities Design, develop, and deploy agentic AI architectures leveraging multi-agent frameworks and LLMs.

Build autonomous, reasoning-based AI agents capable of tool use, contextual data retrieval, and adaptive decision-making.

Implement and orchestrate AI workflows using frameworks such as LangChain, LangGraph, LlamaIndex, AutoGen, or CrewAI .

Integrate vector databases (Pinecone, FAISS, Weaviate) for efficient context management and semantic knowledge retrieval.

Apply prompt engineering, fine-tuning, and context chaining to optimize model performance.

Collaborate with cross-functional teams to deliver production-ready AI pipelines and microservices .

Develop and integrate APIs and event-driven architectures for LLM operations within cloud environments ( AWS, Azure, or GCP ).

Stay abreast of the latest advancements in autonomous AI agents , GenAI frameworks , and LLM orchestration ecosystems .

Required Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering , or a related field.

4–6 years of experience in AI / ML or software engineering , with a focus on LLM-driven applications .

Strong proficiency in Python , with hands-on experience using LangChain, LangGraph, LlamaIndex, AutoGen, or CrewAI .

Proven expertise in agentic workflows, tool-using agents, or multi-agent orchestration systems .

Experience working with vector databases (Pinecone, FAISS, Weaviate) and knowledge retrieval mechanisms.

Proficiency with OpenAI, Anthropic , or open-source LLMs, including prompt tuning and optimization techniques.

Familiarity with API integration, event-driven design patterns , and cloud platforms (AWS preferred).

Strong analytical, problem-solving, and communication skills .

Nice to Have Experience with RAG (Retrieval-Augmented Generation) pipelines and memory-enabled agent architectures .

Familiarity with AI observability tools and LLM evaluation frameworks .

Contributions to open-source AI projects or research in the field of autonomous agents.