Syensqo is all about chemistry. We’re not just referring to chemical reactions here, but also to the magic that occurs when the brightest minds get to work together. This is where our true strength lies. In you. In your future colleagues and in all your differences. And of course, in your ideas to improve lives while preserving our planet’s beauty for the generations to come.
Syensqo.ai - Senior AI Engineer
Syensqo is a leading multinational materials company headquartered in Brussels, advancing humanity through scientific exploration and innovation. Nearly two years after the spin-off from Solvay, Syensqo.ai has evolved from inception to a nimble, high-impact scale-up that accelerates AI adoption across the Group—partnering closely with corporate functions (e.g., Finance, HR, Legal, Procurement), operations, and our chemists and researchers.
We operate lean and fast, with a startup mindset and strong governance: deliver impact quickly, build responsibly, and meet enterprise standards for security, compliance, ethics, and guardrails. As a Senior AI Engineer, you will design, build, and productionize agentic and generative AI solutions on Azure, with a focus on real business outcomes, reproducibility, and maintainability (MLOps).
The Senior AI Engineer will co-lead the planning, execution, and delivery of AI proofs-of-value and products, ensuring they solve concrete business problems and can scale across Syensqo. You will collaborate directly with stakeholders, guide technical decisions, and help shape patterns and standards for agentic AI within the enterprise.
In this role, you will focus on Finance and Corporate use cases (controlling, FP&A, accounting, procurement, treasury). You will translate stakeholder needs into secure, compliant AI solutions—automated workflows, agents/GPTs, Python services—that integrate with enterprise systems and deliver measurable value.
You are a hands-on builder and clear communicator who bridges business and engineering. You combine LLM/RAG, Document Intelligence, and robust MLOps on Azure to ship useful products, coach peers, and accelerate adoption. The position reports to the AI Lead.
Key Responsibilities:
- Partner with Finance/Corporate stakeholders to clarify needs and convert them into AI-enabled solutions and automated workflows;
- Design, implement, and deploy finance-focused agents and GPTs on Azure using function calling and secure tool integrations;
- Build RAG solutions over finance documents with Azure AI Search; govern chunking, routing, safety, and evaluation;
- Orchestrate pipelines with Data Factory/Microsoft Fabric; integrate ERP/SAP and corporate APIs with enterprise identity controls;
- Establish evaluation frameworks for quality, hallucination, bias, latency, and cost; run offline/online testing;
- Drive Azure MLOps: CI/CD for prompts/models, versioning, telemetry, canary/rollback strategies, and cost governance;
- Ensure privacy/security by design; manage secrets, PII handling, approvals, audit trails, and documentation;
- Co-define KPIs with Finance; instrument telemetry and dashboards to evidence business value and adoption;
- Collaborate with IT/Security to productionize on AKS/Container Apps, meeting policy, reliability, and SLA requirements;
- Mentor engineers/scientists; create reusable templates, SDKs, and reference architectures; share best practices;
- Evangelize through demos/workshops and concise guides; support change management for non-technical audiences.
Education and experience:
Education: Master’s or PhD in Computer Science, Data Science, Engineering, Mathematics, or related field — or equivalent practical experience. Finance literacy is a plus.
Experience:
- Proven delivery of production AI/GenAI in enterprise settings; strong preference for Finance domains (controlling, FP&A, accounting, procurement, treasury);
- Hands-on track record with agentic LLM systems (tool use/function calling, orchestration, safety) and robust RAG pipelines;
- MLOps on Azure: CI/CD, model/data/prompt versioning, monitoring, rollback, and cost management;
- Collaboration with corporate stakeholders; translate business needs into technical specifications and measurable outcomes;
- Open-source contributions, side projects, or published case studies evidencing passion and craftsmanship.
Technical Knowledge:
- Python; ML/LLM stacks (PyTorch; scikit-learn; Transformers); agent frameworks (LangChain, Semantic Kernel, LlamaIndex);
- Azure services: Azure Machine Learning; Azure OpenAI / Azure AI Foundry; Azure AI Search; Azure AI Document Intelligence; Azure Data Factory; Azure DevOps; Microsoft Fabric;
- Containers and runtime: Docker; AKS/Container Apps; serverless where appropriate;
- Data engineering fundamentals: SQL/NoSQL, ETL/ELT, APIs/eventing, and secure cloud data integration.
Skills and behavioral competencies:
Startup mindset & ownership: proactive, resourceful, bias to action; comfortable with ambiguity; drives ideas to value;
Technical leadership: sets architecture; makes pragmatic trade-offs across quality, latency, security, and cost.
Business impact orientation: frames problems with stakeholders, defines KPIs, measures value, iterates quickly.
Communication & evangelism: explains complex topics clearly to Finance audiences; runs workshops/demos and crisp write-ups.
Collaboration & knowledge sharing: reusable components, patterns, and docs; uplifts team capabilities.
Curiosity & craftsmanship: keeps pace with GenAI/agentic advances; integrates what truly works.
Responsible AI: security, privacy, compliance, fairness, and robustness by design.
Language skills:
- English (mandatory);
- French (nice to have);
- Italian (nice to have).
What’s in it for the candidate:
Be part of — and contribute to — a once-in-a-lifetime transformation at Syensqo: small, empowered team; direct line of sight to impact; modern Azure stack; autonomy to ship meaningful AI products used across the Group. Shape the Finance AI portfolio and enterprise patterns from the ground up.
Additional information:
- Location: Brussels, Belgium (hybrid model).
