Hi,
Role Title: Senior AI Engineer
Location : Bangalore (Hybrid)
Contract duration: 6 Months
Minium Experience
8+ years engineering, 2+ years applied GenAI/agent experience
Key Skills
AI/ML, GenAI, AI Agents, MuleSoft Agent Fabric, Agent Orchestration, Multi-Agent Systems, RAG, Multistep reasoning, Enterprise AI Integration
Role Summary
We are looking for a Senior AI Engineer to lead the design and implementation of agent integration and orchestration capabilities using MuleSoft Agent Fabric.
This role will focus on onboarding business agents, connecting App to MuleSoft Agent Fabric, defining agent routing patterns, integrating with AI platforms, and ensuring that business groups can safely bring their agents onto the our App platform.
The ideal candidate should have practical experience building agentic AI systems, integrating AI platforms, designing tool-based agents, and applying governance to multi-agent environments.
Key Responsibilities
- Design the agent integration architecture between App and MuleSoft Agent Fabric.
- Define how App routes agent-worthy requests into MuleSoft Agent Fabric.
- Build integration patterns for business agents, domain agents, and specialist agents.
- Create the agent onboarding framework for business groups.
- Define metadata standards for agent registry, ownership, capabilities, permissions, cost tier, and supported actions.
- Integrate agents built on platforms such as Microsoft AI Foundry, AWS Bedrock, Databricks, and custom Python agents.
- Design agent handoff patterns and agent-to-agent collaboration flows where required.
- Work with MuleSoft capabilities for agent orchestration, governance, API connectivity, and enterprise system access.
- Define tool/API usage patterns for agents.
- Ensure agents follow enterprise policies, security rules, and RBAC constraints.
- Collaborate with the Routing Intelligence engineer to ensure App sends only appropriate requests to Agent Fabric.
- Collaborate with the Full Stack Developer to implement backend agent APIs and integration services.
- Design agent observability, evaluation, logging, and traceability patterns.
- Support prompt design, tool definitions, guardrails, and testing for configured agents.
- Help define reusable templates for onboarding HR, IT, Finance, Procurement, Engineering, and other business agents.
Required Skills
- Strong experience building AI agents or agentic AI systems.
- Experience with agent orchestration, tool-calling, function-calling, multi-agent routing, or workflow-based AI systems.
- Strong understanding of enterprise API integration patterns.
- Experience with MuleSoft, API-led connectivity, or similar integration platforms.
- Experience with at least one major AI platform, such as:
- Microsoft AI Foundry / Azure AI
- AWS Bedrock
- Databricks
- OpenAI-compatible APIs
- MoveWorks or similar enterprise AI assistant platforms
- Strong Python experience.
- Experience designing agent tools, prompts, system instructions, and structured outputs.
- Understanding of RAG, embeddings, vector search, knowledge retrieval, and enterprise search patterns.
- Understanding of identity, RBAC, authorization, and secure data access for AI agents.
- Experience with AI governance, guardrails, evaluation, and monitoring.
- Ability to design reusable agent onboarding patterns for business teams.
- Ability to work with enterprise stakeholders and translate business use cases into agent capabilities.
Preferred Skills
- Hands-on experience with MuleSoft Agent Fabric.
- Experience with Anypoint Platform, API Manager, Runtime Manager, or Exchange.
- Experience with MCP, A2A, or agent interoperability standards.
- Experience with ServiceNow, SuccessFactors, Microsoft Graph, or enterprise workflow tools.
- Experience with LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or similar frameworks.
- Experience designing agent evaluation frameworks.
- Experience with prompt/version management.
- Experience with AI safety, content filtering, data leakage prevention, and policy enforcement.
- Experience with enterprise knowledge management and document retrieval systems.
Ideal Candidate Profile
The ideal candidate is a senior AI engineer who understands both AI agents and enterprise integration. They should be able to design practical agent systems that are governed, secure, observable, and reusable across multiple business groups.
Best regards,
Swapnil Thakur
Recruitment & Delivery Lead
iPeople Infosystems LLC
Contact No: +91 7972726448
Email ID: [email protected]
Visit us at www.ipeopleinfosystems.com
Pay: ₹3,000,000.00 - ₹3,500,000.00 per year
Work Location: Hybrid remote in Bengaluru, Karnataka
