Descrição da Vaga
GENAI / AGENTIC AI ENGINEER – MID (HYBRID) LZ9LS4
GENAI / AGENTIC AI ENGINEER – MID (HYBRID LISBON OR PORTO)
Portuguese company hires for hybrid position
📍 Location: Lisbon or Porto, Portugal
⚠️ Only candidates already based in Portugal will be considered
💼 Work Model: Hybrid — 60% remote and 40% on-site
🗣️ Language Requirements: English B2 or higher
🕓 Seniority: Mid-level (3+years)
🏭 Sector: Energy
💲Rate Between €1200 - 1500 RV (gross value)
⚠️ Instructions: Please send your CV in English and make sure to include all skills and experience that match the requirements of the opportunity. This will significantly increase your chances of success
The Opportunity
We are looking for a Mid-Level GenAI / Agentic AI Engineer to design, develop, and deploy production-ready artificial intelligence solutions powered by Large Language Models and agentic architectures.
You will contribute to innovative projects in the energy sector, building intelligent workflows, RAG and Graph RAG solutions, evaluation frameworks, and integrations with enterprise data platforms.
Key Responsibilities
- Design, develop, and deploy applications powered by LLMs;
- Build AI agents and multi-step agentic workflows;
- Develop and orchestrate AI workflows using LangGraph;
- Design and implement RAG and Graph RAG architectures;
- Create evaluation frameworks for quality, accuracy, reliability, and performance monitoring;
- Integrate AI solutions with enterprise data sources, PostgreSQL, vector databases, and vector search platforms;
- Develop maintainable, testable, and production-grade applications in Python;
- Support the deployment, operation, monitoring, and continuous improvement of GenAI solutions;
- Collaborate with engineering, data, product, and business teams;
- Translate business needs into practical and scalable AI solutions.
Mandatory Requirements
- At least three years of relevant professional experience;
- Practical experience with Large Language Models;
- Strong Python development skills;
- Hands-on experience with LangGraph;
- Experience designing AI agents or Agentic AI solutions;
- Knowledge of RAG and Graph RAG architectures;
- Experience building AI evaluation frameworks;
- Knowledge of PostgreSQL;
- Experience with vector databases or vector search;
- Ability to develop solutions suitable for production environments;
- English proficiency at B2 level or higher;
- Availability to work under a hybrid model in Lisbon or Porto.
Nice to Have
- Experience with Azure, AWS, or Google Cloud Platform;
- Knowledge of Azure OpenAI or the OpenAI platform;
- Experience working with Claude or Gemini;
- Knowledge of Docker and Kubernetes;
- Experience with cloud-native AI architectures;
- Familiarity with LLM observability, prompt management, security, and responsible AI practices;
- Experience taking GenAI products from proof of concept to production.
Ideal Candidate Profile
The ideal candidate combines strong Python engineering skills with practical knowledge of modern GenAI architectures. You understand that delivering an LLM solution involves more than writing prompts: it requires orchestration, retrieval, evaluation, monitoring, integration, and operational reliability.
You are analytical, pragmatic, and comfortable solving ambiguous problems. You can discuss technical decisions clearly with engineers while also explaining the business value, limitations, and risks of AI solutions to non-technical stakeholders.
You enjoy working collaboratively, take ownership of deliverables, and are motivated by the opportunity to build AI products that move beyond experimentation into reliable production use.
Why Consider This Opportunity?
- Work on innovative GenAI and Agentic AI initiatives;
- Build solutions with LLMs, LangGraph, RAG, and Graph RAG;
- Participate in the complete AI product lifecycle, from design to production;
- Solve relevant challenges within the energy sector;
- Collaborate with multidisciplinary technical and business teams;
- Benefit from a flexible hybrid working model;
- Work from Lisbon or Porto.
Questions for Candidates
When applying, please address the following questions in your CV or application message:
- How many years of professional experience do you have in Python and artificial intelligence?
- Which GenAI solutions have you delivered to production?
- What types of AI agents or agentic workflows have you built?
- How have you used LangGraph in a professional or personal project?
- What experience do you have designing RAG and Graph RAG architectures?
- Which vector databases or vector search platforms have you used?
- How do you evaluate the quality, accuracy, safety, and performance of LLM applications?
- What experience do you have integrating AI solutions with PostgreSQL and enterprise data sources?
- Which LLM providers and models have you worked with?
- What experience do you have with cloud platforms, Docker, or Kubernetes?
- Is your English level B2 or higher?
- Are you available to work under a hybrid model, with 40% on-site presence in Lisbon or Porto?
Recommended CV Keywords
Generative AI, GenAI, Agentic AI, AI Agents, Large Language Models, LLMs, LangGraph, Agent Orchestration, Multi-Agent Systems, RAG, Retrieval-Augmented Generation, Graph RAG, Knowledge Graphs, Evaluation Frameworks, LLM Evaluation, AI Quality Monitoring, LLM Observability, Prompt Engineering, Python, PostgreSQL, SQL, Vector Databases, Vector Search, Embeddings, Semantic Search, Enterprise Data Integration, Production AI, MLOps, Azure, Microsoft Azure, AWS, Google Cloud Platform, GCP, Azure OpenAI, OpenAI, Claude, Anthropic, Gemini, Docker, Kubernetes, APIs, Microservices, Responsible AI, AI Security
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