AI AGENT ENGINEER

CrewAI • MCP • Claude AI • PostgreSQL MCP • API Integration

Experience: 2+ Years

Role: AI Agent Engineer

Employment: Full-Time

Projects: IGEN NEWS + IGEN EXPO

AI Architecture: 60 Sectors → 60 AI Agents

Core Technology: CrewAI + MCP + Claude AI

Mandatory: PostgreSQL MCP + API Integration Hands-on Experience

? ROLE PURPOSE

IGEN World Ecosystem is building a 60-Sector AI Agent Architecture for IGEN NEWS and IGEN EXPO.

The architecture is

60 BUSINESS SECTORS

↓

60 SPECIALISED AI AGENTS

↓

ONE AI AGENT PER SECTOR

↓

CrewAI + MCP

↓

Claude AI Environment

↓

PostgreSQL MCP

↓

APIs + IGEN Platforms

We are looking for an AI Agent Engineer with 2+ years of practical experience in building, integrating, testing and deploying multiple AI-agent workflows.

This is a hands-on execution role.

The candidate must be capable of building the complete chain:

AI AGENT → CREWAI → MCP → POSTGRESQL MCP → API → IGEN PLATFORM

MANDATORY EXPERIENCE

Candidates must have hands-on practical experience in:

- CREWAI
- CrewAI agents
- CrewAI tasks
- Multi-agent workflows
- Agent orchestration
- Agent-to-agent communication
- Tool integration
- Agent workflow debugging
- MCP — MODEL CONTEXT PROTOCOL
- MCP servers
- MCP tools
- MCP clients
- Tool calling
- MCP-based data access
- MCP authentication/security
- MCP debugging
- CLAUDE AI
- Claude API
- Claude tool use
- Prompt/context engineering
- Structured outputs
- Agent workflows
- Claude-based AI application development
- POSTGRESQL MCP — MUST HAVE

Hands-on experience integrating PostgreSQL with AI agents through MCP is mandatory.

The engineer should understand

AI Agent

↓

MCP

↓

PostgreSQL MCP

↓

PostgreSQL Database

↓

Structured Data

↓

AI Agent Decision / Output

Experience should include

- PostgreSQL MCP integration
- Database querying through MCP
- Schema understanding
- Tables and relationships
- CRUD operations where appropriate
- SQL
- Data retrieval
- Data validation
- AI-to-database workflows
- Database security
- Error handling
- Performance considerations

Candidates without practical PostgreSQL + MCP integration experience should not be considered for this role.

? API INTEGRATION — MUST HAVE

Solid hands-on experience in API integration with AI agents is mandatory.

The engineer must be comfortable with:

- REST APIs
- JSON
- API authentication
- API keys
- OAuth where applicable
- Webhooks
- API requests/responses
- Error handling
- Retry mechanisms
- Rate limiting
- Data transformation
- API testing
- API debugging

Required understanding

AI Agent → MCP Tool → API → External System → Response → AI Agent The engineer should be able to independently troubleshoot failures across this entire chain.

? 60 AI AGENT ARCHITECTURE The core project is to create a scalable architecture for:

60 SECTORS = 60 AI AGENTS

Each sector gets one specialised AI Agent.

For example

Sector 01 AI Agent

Sector 02 AI Agent

Sector 03 AI Agent

...

Sector 60 AI Agent

However, the objective is not to build 60 completely different systems.

The engineer must create a:

REUSABLE AI AGENT ARCHITECTURE where the underlying architecture, tools, MCP patterns,



database integration, API framework, monitoring and deployment model can be reused across all 60 sector agents.

? IGEN NEWS — AI AGENT APPLICATION

AI agents will support workflows such as:

- Sector news discovery
- News classification
- Industry classification
- Company identification
- Leader identification
- Expert identification
- Country classification
- Taxonomy tagging
- Business intelligence
- Content intelligence
- Sector trend analysis
- Structured data generation

Example

News Source

↓

Sector AI Agent

↓

CrewAI

↓

MCP

↓

PostgreSQL MCP

↓

Taxonomy / Company / Leader Data

↓

Claude AI

↓

IGEN NEWS

? IGEN EXPO — AI AGENT APPLICATION

AI agents will support

- Indian exporter discovery
- Global importer discovery
- Global exporter discovery
- Indian importer discovery
- Company intelligence
- Buyer intelligence
- Seller intelligence
- Sector intelligence
- Market intelligence
- Business matching
- Country intelligence
- Opportunity discovery

Example

Business Data

↓

Sector AI Agent

↓

CrewAI

↓

MCP

↓

PostgreSQL MCP

↓

Business Database

↓

Claude AI

↓

IGEN EXPO

?️ CORE TECHNICAL RESPONSIBILITIES The AI Agent Engineer will:

AI AGENT DEVELOPMENT

- Design AI agents
- Develop CrewAI workflows
- Create agent roles and tasks
- Build multi-agent workflows
- Integrate tools
- Develop reusable agent templates

MCP DEVELOPMENT

- Build/integrate MCP servers
- Configure MCP tools
- Connect agents to MCP
- Develop tool-calling workflows
- Test MCP reliability

POSTGRESQL MCP

- Connect AI agents with PostgreSQL through MCP
- Develop database-driven agent workflows
- Query structured data
- Validate database responses
- Implement secure data access
- Optimise database interactions

CLAUDE AI

- Integrate Claude
- Develop prompts
- Manage context
- Implement structured outputs
- Optimise agent performance

API INTEGRATION

- Integrate internal and external APIs
- Connect APIs with MCP tools
- Handle authentication
- Handle failures and retries
- Validate API responses

? AI AGENT TESTING The engineer will establish testing for:
- Agent accuracy
- Tool-call accuracy
- MCP reliability
- PostgreSQL query accuracy
- API reliability
- Data integrity
- Hallucination control
- Response consistency
- Error recovery
- Latency
- Cost efficiency

Every sector agent should have defined:

INPUT → PROCESS → TOOL CALL → DATABASE/API → AI PROCESSING → OUTPUT

? SECURITY & GOVERNANCE

Experience with secure AI-agent architecture is expected.

Responsibilities include

- API credential security
- MCP access control
- Database permissions
- Authentication
- Authorisation
- Input validation
- Output validation
- Secrets management
- Audit logging
- Data access controls

? TECHNICAL SKILLS

MUST HAVE





- 2+ years relevant hands-on AI/AI-agent engineering experience
- CrewAI
- MCP
- Claude AI / Anthropic API
- PostgreSQL
- PostgreSQL MCP integration
- REST API integration
- Python
- SQL
- JSON
- Git/GitHub
- Prompt engineering
- AI Agent workflows
- Debugging

GOOD TO HAVE

- RAG
- Vector databases
- Embeddings
- MongoDB
- Node.js
- TypeScript
- Docker
- Microservices
- AWS/cloud deployment
- AI evaluation
- Observability/monitoring

? IDEAL CANDIDATE

We are looking for an engineer who is:

HANDS-ON

Has actually built AI agents rather than only studied AI-agent concepts.

INTEGRATION-ORIENTED

Can connect AI agents with databases, MCP tools and APIs.

DATABASE-STRONG

Understands PostgreSQL and can implement AI-to-database workflows through MCP.

EXECUTION-ORIENTED

Can take architecture and convert it into working technology.

DEBUGGING-ORIENTED

Can identify whether an issue originates from:

Claude → CrewAI → MCP → PostgreSQL → API → Application

SCALABILITY-ORIENTED

Can build a reusable architecture capable of supporting 60 sector-specific AI agents.

? KEY PERFORMANCE INDICATORS

Success will be measured by:

- Production-ready AI agents delivered
- CrewAI workflow reliability
- MCP integration success
- PostgreSQL MCP integration success
- API integration success
- Agent task completion rate
- Data accuracy
- Tool-call accuracy
- Error recovery
- Response latency
- AI infrastructure cost optimisation
- Reusability of the 60-agent architecture
- Quality of technical documentation

? WORKING WITH THE TECHNOLOGY TEAM The AI Agent Engineer will work closely with:
- CTO
- Technology Lead
- Layer 1 API Integration Team
- Layer 2 AI Agent Execution Team
- Layer 3 Platform/API Integration Team
- Product Team
- IGEN NEWS Team
- IGEN EXPO Team

THREE-LAYER SUCCESS MODEL

LAYER 1

API / Platform Integration

↓

LAYER 2

AI AGENT EXECUTION

↓

LAYER 3

API / Application Integration The AI Agent Engineer will have primary responsibility for Layer 2 AI Agent execution, while ensuring successful integration with Layers 1 and 3.

? FIRST 90 DAYS

DAYS 1–30

- Understand IGEN NEWS architecture
- Understand IGEN EXPO architecture
- Understand 60-sector taxonomy
- Establish CrewAI framework
- Establish MCP framework
- Validate Claude integration
- Validate PostgreSQL MCP integration
- Build first reference sector agent

DAYS 31–60
- Integrate multiple APIs
- Build reusable MCP tools
- Develop additional sector agents
- Establish agent testing framework
- Establish monitoring and logging

DAYS 61–90
- Scale the reusable agent architecture
- Deploy multiple sector agents
- Standardise agent templates
- Improve PostgreSQL/MCP workflows
- Improve API integrations
- Document the architecture
- Establish framework for scaling toward 60 AI Agents THE MISSION

BUILD THE AI AGENT ENGINE OF IGEN WORLD.

60 SECTORS

↓

60 AI AGENTS

↓

CREWAI

↓

MCP

↓

CLAUDE AI

↓

POSTGRESQL MCP

↓

API INTEGRATION

↓

IGEN NEWS + IGEN EXPO

ONE SECTOR. ONE AI AGENT. ONE REUSABLE ARCHITECTURE.

This is a hands-on engineering role for someone who can build, integrate, test, debug and scale AI agents in a real production environment.

📌 AI AGENT Engineer with two year experience in MULTIPLE AI AGENT TECH execution and POSTGRESQL MCP + API Integration experience (Bengaluru)
🏢 IGEN - India Global Expo News - www.igenworld.com
📍 Bengaluru