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.