Role Description At Mindera, we believe in building software that improves lives. As a Senior AI Engineer, you own the machinery that makes our accelerators reliable and reusable: - The reusable accelerator core and the multi-agent workflows built on it. - Agent design across coding, planning, review, and testing agents, with tool-calling and human-in-the-loop where it earns its place. - The evaluation pipelines and telemetry that make quality measurable and regressions visible. - Reliability, cost control, and observability for agentic systems in real use. Qualifications - At least 6 years of professional experience as an AI Engineer or in a similar role. - Strong production software engineering: Python, testing, packaging, CI/CD, async, REST, Docker. You build products, not scripts. - Real depth in LLM application engineering: prompt design, function calling, structured outputs, RAG, vector stores, with the Anthropic and OpenAI APIs. - Evaluation-driven development as a core habit, not an afterthought. You treat evals as the source of truth. - Experience building agentic systems end to end: systems that plan, write code, validate their own output, and improve over time. - Familiar with the orchestration landscape (LangGraph, LlamaIndex, AutoGen, CrewAI) and opinionated about when a thin custom harness beats a framework. - Working fluency with at least one cloud data platform and SQL: enough to build eval and verification infrastructure that your applied-data counterpart fills with domain rules. You do not need to be the deepest data expert in the room. Benefits - Health Insurance, because health comes first. - Flexible working hours. - Open holidays, take the time you need for yourself. - Profit distribution for everyone. - Mindera Annual Trip, Sports, and sharing groups to connect and have fun! - Training & conferences, create your own training plan. - Child Care vouchers. - Choose Laptop & Peripherals that best suit your needs. - Hotspot with unlimited usage (PT), for work or Netflix. - Amazing offices in Porto, Aveiro, and Coimbra if you want to physically connect with minders. Remote from Portugal is also an option. Remote from other Countries will depend on your current location and Projects. - A wide range of snacks to keep you fed and healthy at the offices. - Partnerships with local businesses. Company Description At Mindera we use technology to build products we are proud of, with people we love. - Software Engineering Applications, including Web and Mobile, are at the core of what we do at Mindera. - We partner with our clients to understand their products and deliver high-performance, resilient, and scalable software systems that create an impact in their users and businesses across the world. - You get to work with a bunch of great people, where the whole team owns the project together. - Our culture reflects our lean and self-management attitude. We encourage our colleagues to take risks, make decisions, work in a collaborative way, and talk to everyone to enhance communication. - We are proud of our work and we love to learn all and everything while navigating through an Agile, Lean, and collaborative environment. - Check out our Blog and our Handbook! - Our offices are located: Porto, Portugal | Aveiro, Portugal | Coimbra, Portugal | Leicester, UK | San Diego, USA | San Francisco, USA | Chennai, India | Bengaluru, India | Cluj-Napoca, Romania | Blumenau, Brazil.

• Lead AI modelling projects end-to-end, from problem definition through to a validated solution that a partner team can understand, adopt, and maintain. • Advise product, data, and engineering teams on AI solution design, including model selection, data requirements, architecture decisions, and the tradeoffs involved in each. • Serve as a technical reference across the C4E and its partner teams: review approaches, answer hard questions, and provide a grounded second opinion on high-stakes decisions. • Adapt model designs and methods based on partner feedback and validation results, balancing technical rigour with practical constraints. • Identify where the team's modelling practices could be stronger and act on it: better evaluation approaches, shared templates, clearer processes. • Create reusable technical resources such as design patterns, evaluation frameworks, and model cards, and actively facilitate knowledge sharing across disciplines. • Collaborate with the Responsible AI, Data, Platform, and Security teams, ensuring the right people are involved at the right stage and feeding recurring patterns or gaps back to them. • Support partner adoption by producing documentation and handover materials that are genuinely usable, and staying involved until teams are confident with what has been built.

• Design and deploy AI-powered workflows and automation across internal systems • Integrate LLM APIs (OpenAI, Anthropic, etc.) into operational platforms and internal tooling, with examples including: - Airtable Scripting & AI Automation - Microsoft 365 / Power Platform AI Enhancements - Custom Agent & RAG Pipeline Development • Build and maintain custom AI agents, automation pipelines, and retrieval-augmented generation (RAG) systems • Own the bridge between AI capabilities and the existing technology stack • Evaluate and prototype emerging AI tools for business relevance and operational fit • Collaborate with operations, sales, and leadership teams to identify and prioritize AI opportunities • Contribute to platform development features and maintain clean, well-documented code • Translate AI capabilities for non-technical stakeholders and gather real requirements from business teams • Maintain a running roadmap of AI enhancements tied to business goals and project timelines • Consistently exemplify established best practices, serving as the internal subject matter expert on applied AI • Provide team or company-wide AI training and education where applicable. • Create & manage technical documentation for all AI systems, integrations, and workflows.

• Lead the technical architecture of Data, Analytics and AI solutions for our clients, covering the full lifecycle from design to deployment: • Design end-to-end data architectures: data lakes, lakehouses, warehouses, and streaming pipelines. • Define standards for data modeling, storage, ingestion, and transformation across client engagements. • Architect MLOps and AI deployment infrastructure (model registries, CI/CD for ML, monitoring). • Lead technical decisions on cloud platforms (Azure, AWS, GCP) and open-source tooling. • Define best practices and reusable frameworks for data engineers, analysts, and data scientists. • Act as a technical mentor and reviewer for cross-functional project teams. • Bridge the gap between data analysts, data engineers, and AI/ML engineers on complex projects. • Contribute to internal knowledge base, toolkits, and delivery accelerators. • Lead architecture workshops and discovery sessions with client stakeholders. • Translate business requirements into scalable, robust technical blueprints. • Present architecture decisions to both technical teams and executive audiences. • Support pre-sales and proposal efforts with technical scoping and solution design. • Provide internal training and knowledge-sharing sessions with the team. • Support the Head of Practice on business development and internal capability initiatives.