Role & responsibilities

Summary As a Senior AI Developer, the contractor will lead the end-to-end design, development, deployment, and continuous improvement of autonomous AI workflows and intelligent agents. The role requires strong hands-on engineering capability in Python and Java, deep experience with TensorFlow and PyTorch, and practical delivery experience across up-to-date agentic AI frameworks such as LangChain, LangGraph, CrewAI, and AutoGen. The developer will integrate LLMs such as GPT, Claude, Llama, and Mistral into multi-agent orchestration pipelines, implement RAG solutions using vector stores such as Milvus, Pinecone, and Azure AI Search, and embed AI agents into CI/CD, Docker/Kubernetes, and infrastructure-as-code environments. The role will also champion Model Context Protocol adoption by authoring MCP servers and clients so AI agents can securely interface with enterprise systems, tools, and data stores through bidirectional context exchange. Expertise in Harness and Context Engineering. Key Skills Agentic AI development: hands-on experience designing, building, and deploying AI agents using LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks. Expertise in Architecture and Design for enterprise applications. LLM/RAG engineering: integration of LLMs, prompt strategies, function calling, vector stores, embeddings, RAG pipelines, and long-term memory patterns. Production AI engineering: strong Python/Java, TensorFlow/PyTorch, CI/CD, Docker/Kubernetes, infrastructure as code, observability, logging, monitoring, and debugging. Key Responsibilities Team: AI engineering / software engineering team focused on integrating GenAI and agentic AI capabilities into enterprise SDLC and business workflows.



Key projects include autonomous AI workflow design, multi-agent orchestration, RAG pipeline implementation, MCP server/client development, CI/CD integration, observability, and production readiness for AI agents. Reason for posting: need for senior hands-on AI engineering talent to accelerate delivery of scalable, secure, production-ready AI agent solutions. Typical day includes translating business requirements into AI architectures, building and testing agent workflows, integrating LLMs with tools/APIs/data stores, implementing RAG and memory patterns, debugging model and agent behavior, reviewing code, deploying to containerized environments, and partnering with product, engineering, DevOps, and architecture stakeholders. The contractor will work independently with frequent cross-functional collaboration. This role offers the opportunity to work on cutting-edge AI agent engineering, including LLM orchestration, MCP adoption, production RAG systems, long-term memory, observability, and enterprise-grade AI workflow automation. The candidate will gain experience building scalable GenAI solutions that connect directly to enterprise systems and improve software engineering productivity. Key Requirements 8+ years of hands-on AI/ML development experience and custom app development. Bachelors or Master’s degree in Computer Science, Artificial Intelligence, or a related field. Required background includes Python and Java development, AI/ML frameworks, agentic AI frameworks, LLM integration, RAG/vector databases, CI/CD, Docker/Kubernetes, observability, prompt engineering, function calling, memory management, and production AI deployment.

Preferred candidate profile

📌 Senior AI Developer (Pune)
🏢 Honeybee Tech Solutions
📍 Pune