About the job LLM Engineer - AI Agent Development
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Were not just hiring were building a team of AI pioneers ready to shape the future of intelligent agents. If youre passionate about LLMs, agent architecture, and solving complex problems with cutting-edge tools, this is your moment.
Position: LLM Engineer - AI Agent Development
Location: Maia, Porto (On-site)
Experience Level: Junior to Mid (1-4 years)
Employment Type: Full-time
About the Role
Youll join our AI development team to refine existing agents and help build the next generation using MCP (Model Context Protocol). From hallucination control to multi-agent orchestration, youll be working at the forefront of conversational AI and customer support automation.
Key Projects
Current: Backoffice Agent Refinement
* Enhance agent capabilities and performance
* Optimize workflows using LangGraph for multi-step reasoning
* Implement hallucination detection and mitigation strategies
* Improve reliability, error handling, and output validation
Upcoming: Frontend Agent & MCP Server
* Design real-time customer-facing agents
* Implement MCP server architecture for seamless model integration
* Build scalable infrastructure for concurrent interactions
* Develop robust conversation management and context preservation
Key Responsibilities
AI Agent Development & Architecture
* Design complex workflows with LangGraph
* Build LangChain pipelines for document retrieval
* Implement hallucination control and validation mechanisms
* Create scalable agent architectures for high concurrency
* Develop RAG systems with vector databases
Advanced Agent Capabilities
* Orchestrate multi-agent systems
* Implement tool calling and function execution frameworks
* Design memory systems for long-term context
* Build agent evaluation and testing frameworks
* Optimize prompts and dynamic generation strategies
Production & Scalability
* Apply horizontal scaling strategies
* Develop caching for embeddings and responses
* Implement load balancing and token cost optimization
* Build rate limiting and abuse prevention mechanisms
Quality & Safety
* Create output validation pipelines
* Implement safety filters and content moderation
* Develop confidence scoring and uncertainty quantification
* Design human-in-the-loop workflows
* Build audit trails and logging systems
Required Technical Skills
AI/ML Frameworks & Tools
* LangChain & LangGraph for agent workflows
* Vector databases (PostgreSQL + pgvector)
* LLM APIs (OpenAI GPT-4, Claude, etc.)
* Embeddings for semantic search and retrieval
Hallucination Control & Validation
* Fact-checking and ground truth verification
* Confidence scoring and output validation
* Guardrails and content filtering
Scalability & Performance
* Async programming with Python asyncio
* Queue systems (Redis, Celery, RQ)
* Caching strategies and database optimization
* Load testing for high-concurrency scenarios
Backend Development
* Python (2+ years), FastAPI or Flask
* PostgreSQL, vector DBs, ORM usage
* Authentication (JWT, OAuth)
* Docker and container orchestration
Soft Skills & Attributes
* Creative problem-solving mindset
* Precision in prompt engineering and validation
* Empathy for user experience in conversational interfaces
* Analytical thinking and data-driven decision-making
* Strong communication in English and Portuguese
* Adaptability to fast-evolving AI technologies
* Commitment to quality and production-readiness
What We Offer
* Competitive salary based on experience
* Budget for AI/ML courses and certifications
* Access to premium LLM APIs and dev tools
* Modern office in Maia with high-performance hardware
* Flexible working hours within core business times
* Opportunity to work on cutting-edge AI agent tech
* Coffee and snacks always available
Work Environment
This is an on-site position in our Maia office. We foster a collaborative space where AI engineers experiment, share discoveries, and iterate quickly. Our team thrives on continuous learning and pushing the boundaries of agent development.
Technical Stack
* AI/ML: LangChain, LangGraph, GPT-4, Claude, Hugging Face
* Languages: Python (primary), TypeScript/JavaScript (frontend)
* Databases: PostgreSQL + pgvector, Redis
* Infrastructure: Docker, Kubernetes, AWS/GCP/Azure
* Monitoring: OpenTelemetry, Prometheus
* Development: FastAPI, Pydantic, pytest, black, mypy
Technical Interview Topics
Agent Architecture & Development
* LangGraph workflow design
* LangChain pipeline optimization
* RAG architecture and vector DB selection
* Multi-agent coordination patterns
Quality & Safety
* Hallucination detection and mitigation
* Output validation and fact-checking
* Confidence scoring and safety filters
Scalability & Performance
* Horizontal scaling and caching
* Async programming for concurrency
* Token optimization and cost control
Integration & Production
* MCP protocol implementation
* Real-time conversation systems
* Error handling and observability
Sample Technical Challenges
You may be asked to:
* Design a LangGraph workflow for a multi-step support scenario
* Implement hallucination detection for agent responses
* Architect a system for 1000+ concurrent conversations
* Debug inconsistent agent outputs
* Optimize a RAG system for speed and accuracy
Ready to stop being just another number?
Apply now and become a Nimber where your ideas shape the future of AI.