Agentic AI Developer

We are seeking a Senior Agentic AI Developer to design, build, and deploy enterprise-grade AI agents and intelligent automation solutions. This role will focus on developing agentic AI applications, Retrieval-Augmented Generation (RAG) systems, LLM-powered workflows, and scalable AI platforms using Python and modern AI frameworks. The ideal candidate has hands-on experience building production AI systems, integrating Large Language Models (LLMs), orchestrating multi-agent workflows, and deploying cloud-native applications that support real-world business processes.

Responsibilities

• Design, develop, and deploy agentic AI applications using modern LLM frameworks and orchestration platforms.
• Build Retrieval-Augmented Generation (RAG) solutions leveraging enterprise data sources, vector databases, and semantic search technologies.
• Develop AI agents capable of tool calling, workflow automation, reasoning, and decision support.
• Create scalable APIs and backend services to support AI-enabled products and applications.
• Design and implement document ingestion, knowledge retrieval, embedding generation, and context management pipelines.
• Collaborate with product, engineering, and business teams to identify and deliver AI-driven solutions.
• Evaluate, test, and optimize LLM performance, response quality, latency, and reliability.
• Implement monitoring, observability, security, and governance controls for enterprise AI systems.
• Participate in architecture discussions, proof-of-concept development, and technical design reviews.
• Create and maintain technical documentation, implementation plans, and best practices for AI development.

• Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related technical field.
• 5+ years of software development experience with strong proficiency in Python.
• Experience building and deploying Generative AI, LLM, or Agentic AI solutions in production environments.
• Experience developing RAG architectures and integrating vector databases.
• Strong understanding of prompt engineering, embeddings, semantic search, and LLM evaluation techniques.
• Experience building APIs and microservices using Python frameworks such as FastAPI.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience with containerization and deployment technologies including Docker and Kubernetes.
• Strong troubleshooting, debugging, and problem-solving skills., * Experience with LangChain, LangGraph, CrewAI, AutoGen, or similar agent orchestration frameworks.
• Experience integrating AI agents with enterprise systems, databases, APIs, and workflow platforms.
• Familiarity with OpenAI, Anthropic, Azure OpenAI, Amazon Bedrock, or other enterprise LLM platforms.
• Experience with MLOps, LLMOps, and AI governance practices.
• Experience developing multi-agent systems and autonomous workflow solutions.
• Exposure to Go or other backend programming languages.

Technical Environment

• Python
• FastAPI
• LangChain / LangGraph
• OpenAI, Claude, Azure OpenAI, Amazon Bedrock
• Retrieval-Augmented Generation (RAG)
• Vector Databases
• Docker & Kubernetes
• AWS / Azure / GCP
• REST APIs & Microservices
• Git, CI/CD Pipelines
• LLMOps & Monitoring Frameworks