Explicitly requires vibe coding: building agentic LLM workflows, using LangChain/LangGraph-like tools, vector DBs and prompt engineering for rapid AI-driven automation.
About the Role
Build and deploy agentic AI workflows to automate business processes by integrating LLMs, enterprise systems, and data stores. Develop backend services, RAG solutions, and orchestrations using Python/Java, LLM APIs, vector databases, and workflow automation platforms to deliver reliable, secure, production-grade AI agents.
Job Description
Role
Design, develop, and deploy agentic AI workflows for business process automation. Implement AI agents capable of planning, multi-step reasoning, tool usage, and human-in-the-loop approvals, and convert manual processes into AI-enabled workflows.
Key Responsibilities
- Design and build agentic AI workflows and orchestration (planning, reasoning, tool calling, memory, approvals).
- Integrate LLMs (OpenAI, Anthropic Claude, Gemini, etc.) via APIs and evaluate new models and frameworks.
- Develop backend services and APIs using Python and Java; implement REST APIs and integrations with ERP, databases, email, documents, and other enterprise systems.
- Implement RAG solutions using organizational data and documents; work with embeddings and vector databases for semantic search.
- Perform prompt engineering and optimize prompts for accuracy, reliability, and cost.
- Implement structured outputs, validation, exception handling, retries, logging, monitoring, and testing for hallucinations and edge cases.
- Ensure security, access control, data privacy, and responsible AI use; document architecture, workflows, and technical specifications.
- Collaborate closely with business teams to translate requirements into technical solutions.
Requirements
- Strong programming skills in Python; good knowledge of Java or a similar backend language.
- Strong understanding of Generative AI and Large Language Models; experience using LLM APIs (OpenAI, Anthropic Claude, Gemini or equivalents).
- Understanding of agentic AI architectures and multi-step workflows; experience with AI orchestration frameworks (LangGraph, LangChain, CrewAI, AutoGen or equivalents).
- Experience with API development (REST), SQL, and MongoDB / NoSQL databases.
- Knowledge of RAG, embeddings, vector databases, semantic search, and prompt engineering.
- Experience with Git/version control and with authentication, authorization, API security, and data security.
- Experience designing, testing, and monitoring AI workflows for accuracy, reliability, and security.
Good-to-have Skills
- Experience with workflow automation platforms (n8n, Make, Power Automate).
- Docker and containerization; cloud platforms (Azure, AWS, GCP).
- Familiarity with vector DBs (Pinecone, Qdrant, Weaviate, Chroma, pgvector).
- Experience integrating AI with ERP/CRM/HRMS/email/document management systems.
- Front-end knowledge (React, JavaScript) and familiarity with OCR, document processing, vision/multimodal models.
- Knowledge of AI observability, evaluation, monitoring, and multi-agent architectures.