• Own and refine the overarching platform story, with special emphasis on context-first document management, AI and agentic automations, scalability, security, and extensibility. • Define differentiated messaging and value propositions for platform capabilities across personas and industries. • Ensure consistency and clarity of platform-level messaging across all marketing and sales touchpoints. • Lead platform feature releases, orchestrating cross-functional launch strategies for AI, cloud, and core platform enhancements. • Partner with Product Management to influence roadmap decisions based on market opportunity, customer needs, and competitive insights. • Drive content strategy for platform launches, including pitch decks, solution briefs, whitepapers, demos, customer stories, webpages, and sales tools. • Own competitive and market intelligence for platform-level capabilities, especially in AI-driven information management and cloud content services. • Identify market trends, customer pain points, and emerging competitors to guide product and GTM strategy. • Deliver actionable insights to Sales, Product, and Executive teams. • Partner with Sales Enablement to ensure clear understanding of platform capabilities, differentiation, and value drivers. • Support customer-facing teams with platform-level messaging guides, battlecards, objection handling, and training content. • Collaborate with the cross-functional teams to position M-Files as an industry leader in AI-powered information management. • Represent M-Files in webinars, events, analyst briefings, and customer engagements as a platform subject-matter expert.

• 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.

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.