AI Agentic Developer

Vibehackers; Hyderabad; On-site; INR 1,500,000 - 2,800,000; Full time

Job summary

Vibehackers in Hyderabad seeks an AI Agentic Developer to design, build, and deploy agentic AI solutions in enterprise environments. You will specialize in MuleSoft-based integration, LLM agents, and RAG pipelines, delivering production-ready components.

You will work with Python automation, vector stores, and deployment platforms like Databricks/MLflow, ensuring robust API design, testing, and monitoring across time zones.

Qualifications

• Extensive enterprise integration experience with API-led design and MuleSoft patterns.
• Hands-on experience with MuleSoft Anypoint Platform, DataWeave, connectors, CloudHub.
• Strong API fundamentals: REST, SOAP, JSON, XML, OAuth, API security.
• Exposure to AI/ML concepts including LLM-based agents, multi-agent orchestration, and autonomous workflows.
• Experience with RAG pipelines, vector databases, and context/memory management for agents.
• Python scripting for automation and tooling.

Responsibilities

• Design and implement enterprise integrations using MuleSoft Anypoint Platform and API-led design.
• Build or integrate agentic AI solutions: LLM-based agents and multi-agent orchestration.
• Implement RAG pipelines with vector DBs, manage context and memory for agents.
• Deploy and serve agent components on platforms like Databricks and MLflow.
• Develop automation tooling using Python and maintain CI/CD pipelines.
• Document architectures, support testing/UAT, and coordinate go-live activities.

Skills

MuleSoft

DataWeave

APIs

Python scripting

CI/CD

Automated testing

Monitoring

Documentation

Stakeholder management

Multi-agent orchestration

Prompt engineering

Vector stores

RAG pipelines

Databricks

MLflow

OAuth

REST

SOAP

Education

Tools

MuleSoft Anypoint Platform

DataWeave

CloudHub

Databricks

MLflow

Job description

Directly related to vibe coding: building and integrating agentic AI (LangChain/LangGraph, RAG, vector DBs) and using Python for automation—relevant for AI-driven prototyping and agent tooling.

About the Role

AI Agentic Developer role focused on designing, building, and integrating agentic AI solutions within enterprise environments using MuleSoft for integrations, RAG pipelines and vector stores for retrieval, and Python for automation; ensures production-ready deployments and strong API and integration engineering practices.

Job Description

Role

AI Agentic Developer responsible for delivering production integrations and agentic AI capabilities in an enterprise environment. The role combines MuleSoft-based integration engineering with building and integrating LLM-based agents, RAG pipelines, and deployment/serving of agent components.

Key Responsibilities

• Design and implement enterprise integrations using MuleSoft Anypoint Platform (API-led design, connectors, DataWeave, error handling, CloudHub deployment).
• Build or integrate agentic AI solutions: LLM-based agents, multi-agent orchestration, tool-use patterns, autonomous task execution.
• Implement RAG (Retrieval-Augmented Generation) pipelines with vector databases and manage caching, memory, and context for agents (conversation history, session persistence, vector stores).
• Deploy and serve agent/ML components on platforms such as Databricks and MLflow or similar, and work with MCP (Model Context Protocol) or AI-assisted automation.
• Develop automation tooling and scripts using Python.
• Apply engineering best practices: CI/CD, version control, automated testing, monitoring, technical documentation, support UAT and go-live activities.
• Collaborate and communicate with global stakeholders across overlapping time zones.

Requirements

• Extensive enterprise software and integration engineering experience; role text references very senior experience levels and expects proven delivery of production integrations.
• Hands-on experience with MuleSoft Anypoint Platform, DataWeave, connectors, CloudHub, API-led design, and MuleSoft-specific patterns.
• Strong API fundamentals: REST, SOAP, JSON, XML, OAuth, API security, and connectivity patterns for email, file, and databases.
• Exposure to AI/ML concepts including LLM-based agents, prompt engineering, agent architectures, multi-agent orchestration, and autonomous workflows.
• Experience with RAG pipelines, vector databases/vector stores, caching strategies, and context/memory management for conversational agents.
• Experience with deployment/serving platforms (Databricks preferred) and ML lifecycle tools such as MLflow.
• Python scripting experience for automation and tooling.
• Familiarity with integration domains such as SAP order entry/pricing/drop-ship/customer master data is a strong plus.
• Strong written technical documentation skills and effective communication for cross-time-zone collaboration.

Nice to Have

• MuleSoft Developer or Integration Architect certification.
• Experience with EDI, cXML, Coupa and B2B onboarding integrations.
• Experience with document extraction and evaluation of agent accuracy.

Skills

Integration Engineering API Design Automation Prompt Engineering AI/ML Concepts Multi-agent Orchestration CI/CD Version Control Automated Testing Monitoring Technical Documentation Communication Stakeholder Management Python Scripting