Engineer | AI Engineer

Description

Job Summary: We are seeking an AI Engineer to design, develop, and deliver new intelligent technologies and systems, with a focus on building reasoning agents and decision-making pipelines. Key Highlights: 1. Building reasoning agents and decision-making pipelines 2. Designing and maintaining the AI Engineering data architecture 3. Working on real-world and innovative projects **Company Description** We are a Center for Engineering and Product Development that conceives, develops, and delivers new technologies, products, and services for a more sustainable society. We bridge cities, industry, and universities around major programs for product and service development and industrialization, originating from Portugal in high-tech sectors such as mobility, aeronautics, and space. The AI Engineering area is the new intelligence layer of the CEiiA ecosystem. It reports directly to the board and aims to grant autonomy to the systems built by CEiiA. This AI Engineer (m/f/d) position will join the AI Engineering area. **Job Description** You will work directly with the Head of AI Engineering and the Lead AI Engineer. The projects are real and already underway. You will not maintain legacy code. You will build things that do not yet exist — reasoning agents, decision-making pipelines, anticipatory systems. And you will ensure the data underpinning these systems is robust, sovereign, and trustworthy. **Responsibilities:** * Design and maintain the AI Engineering data architecture — how data arrives, how it is stored, how it is versioned, and who has access; * Ensure data sovereignty: critical data does not leave the perimeter; * Curate and structure messy data from multiple sources; * Build ingestion, transformation, and quality pipelines — clean data before it reaches the model; * Structure data for reasoning: knowledge graphs, embeddings, RAG, context injection; * Architect, design, and build intelligent systems atop LLMs for specific domains; * Design how machines think: cognitive architectures, knowledge representation, prompt architecture, tool ecosystems, context and memory; * Orchestrate models — frontier, open-source, fine-tuned — with reasoned trade-offs across cost, latency, quality, and privacy; * Prototype rapidly (days, not months) and take PoCs to production; * Failure design — brains hallucinate, lose context, become confused. Design guardrails, fallbacks, and graceful degradation; * Eval mindset — how do you know the brain improved? Design evaluations, red-teaming, test edge cases, measure reasoning quality — not just accuracy. **Qualifications** * Degree in Computer Engineering, Systems Engineering, Mathematics, Physics, or a related technical field; * 3+ years of experience, including at least 2 years with AI/ML systems in production (products serving real users); * Data architecture for AI — building a sovereign data layer: ingestion, storage, quality, versioning, access. Not a nice-to-have; it is the starting point; * Solid proficiency in at least one backend language (Python, Go, Rust, or equivalent), agents, integrations, and complex pipelines; * Real-world experience with LLMs in production: tool-calling, structured outputs, context management, cost and latency optimization; * Agent architecture: multi-step reasoning systems, memory, tool ecosystems, fallback mechanisms; * Model orchestration — when to use frontier vs. open-source vs. fine-tuned models, with clear trade-offs; * AI infrastructure: GPUs, model serving (vLLM, TGI or equivalent), inference pipelines, cloud vs. on-prem compute; * Integration of data from multiple sources; * Genuine curiosity; * Systems thinking and critical analysis; * Comfort with ambiguity; * Clear communication for non-technical audiences; * Portuguese (mandatory) + technical English. *Also valued:* * LLMOps — model versioning, monitoring, deployment, evaluation pipelines; * GCP, Docker; * Background in complex domains: defense, space, energy, critical infrastructure. **Additional Information** * Relaxed work environment, dynamic and multidisciplinary teams. * We facilitate and promote a balanced and healthy lifestyle, integrating work with personal life. * Health insurance. * Partnerships with gyms, Nutrium, and others. * Up to three additional vacation days. * Birthday off.