AI AGENT Engineer INTERNSHIP - for candidates with two years FULL STACK experience for learning tech execution to develop MULTIPLE AI AGENT TECH execution and POSTGRESQL MCP AI

JOB DESCRIPTION
AI AGENT ENGINEER INTERNSHIP for FULL STACK ENGINEER
CrewAI • MCP • Claude AI • PostgreSQL MCP • API Integration
Experience: 2+ Years
Role: AI Agent Engineer Intern
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:
1. CREWAI
- CrewAI agents
- CrewAI tasks
- Multi-agent workflows
- Agent orchestration
- Agent-to-agent communication
- Tool integration
- Agent workflow debugging
2. MCP — MODEL CONTEXT PROTOCOL
- MCP servers
- MCP tools
- MCP clients
- Tool calling
- MCP-based data access
- MCP authentication/security
- MCP debugging
3. CLAUDE AI
- Claude API
- Claude tool use
- Prompt/context engineering
- Structured outputs
- Agent workflows
- Claude-based AI application development
4. 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
Strong 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:
1. Production-ready AI agents delivered
2. CrewAI workflow reliability
3. MCP integration success

Work arrangement
No