{"id":2292205,"url":"https://alion.io/job/syensqo-senior-ai-engineer","title":"Senior AI Engineer","company":{"id":50272,"name":"Syensqo","domain":"syensqo.com","url":"https://alion.io/company/syensqo","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Shanghai, China"],"countries":["CN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":42000,"max_usd":107000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":18},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Azure","optional":false},{"name":"Azure AKS","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Copilot","optional":false},{"name":"Copilot Studio","optional":false},{"name":"Function Calling","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"LocalAI","optional":false},{"name":"Machine Learning","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"OpenAI","optional":false},{"name":"RAG","optional":false},{"name":"Azure Data Factory","optional":true},{"name":"Docker","optional":true},{"name":"ETL/ELT","optional":true},{"name":"Fine-tuning","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangChain","optional":true},{"name":"LlamaIndex","optional":true},{"name":"LLM","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"Scikit-learn","optional":true},{"name":"Semantic Kernel","optional":true},{"name":"SQL","optional":true},{"name":"Transformers","optional":true}],"status":"live","first_seen_at":"2026-10-03T02:00:00Z","employer_posted_date":"2026-10-03","last_verified_at":"2026-10-28T05:42:10Z","board_verified":true,"closed_at":null,"days_open":25,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":25},"description":"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.\nWe are looking for:\nWe are looking for a senior AI Engineer to design, build, and productionize agentic and generative AI solutions on Azure, with a focus on real business outcomes, reproducibility, and maintainability (MLOps). The job holder 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. The job holder is expected to collaborate directly with stakeholders, guide technical decisions, and help shape patterns and standards for agentic AI within the enterprise.\n\nWe count on you for:\nAssess and understand local specificities on the AI market - spot opportunities and potential partnerships with local AI leaders.\n\nWorking close to local leadership to provide AI solutions.\n\nLead the end-to-end design, implementation, and deployment of agentic and generative AI solutions (tool-using LLMs, function calling, multi-step workflows) that integrate with enterprise systems and data.\n\nArchitect RAG pipelines (retrieval, indexing, chunking, routing, safety filters, evaluation) using Azure services (e.g., Azure AI Search, Azure OpenAI / Azure AI Foundry, Azure Machine Learning) and modern frameworks.\n\nDesign, develop, and extend solutions across the Microsoft Copilot ecosystem, including Microsoft 365 Copilot, Copilot Studio, Copilot Agents, Azure AI Foundry Agents, and custom Copilot experiences. Build enterprise-grade copilots and agentic applications leveraging Microsoft Graph, Graph Connectors, Semantic Index, Copilot APIs, Power Platform, and Microsoft Fabric. Demonstrate expertise in integrating Copilot capabilities with business processes, enterprise knowledge sources, and line-of-business systems while ensuring governance, security, compliance, and responsible AI practices.\n\nDrive MLOps on Azure: CI/CD for prompts and models, model/data/versioning, telemetry, guardrails, rollback strategies, canary releases, monitoring, and cost governance.\n\nServe as a technical authority on Azure (Azure ML, Azure DevOps, Azure Functions, Microsoft Fabric, Azure AI/OpenAI, Azure AI Search; familiarity with AKS/Container Apps is a plus).\n\nWork side-by-side with business stakeholders in corporate functions and R&I to frame use cases, define success metrics, and deliver measurable value.\n\nChampion Responsible AI: privacy, security, compliance, ethical use, and documentation across the lifecycle.\n\nMentor engineers/scientists, share best practices, and contribute reusable components, templates, and reference architectures.\n\nPromote adoption through demos, workshops, and concise internal write-ups; stay current on GenAI/agentic research and bring relevant advances into production.\n\n(Optional, valued) Contribute to initiatives involving chemistry/materials datasets and domain-specific tooling.\n\nYou can count on us for:\nJoin a dynamic team that tackles big challenges of transformation.\n\nBe 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.\n\nYou will bring:\nMaster’s or PhD in Computer Science, Data Science, Engineering, Mathematics, or related field - or equivalent practical experience. Background in Chemistry/Cheminformatics is a plus.\n\nSolid hands-on experience delivering production AI/GenAI solutions (tenure flexible; we value demonstrated capability over years).\n\nProven track record building agentic LLM systems (tool use/function calling, orchestration, safety), RAG pipelines, and fine-tuning/adaptation.\n\nExperience working with corporate business functions (e.g., Finance, HR, Legal, Procurement) and/or R&I stakeholders.\n\nDemonstrated MLOps implementation on Microsoft Azure.\n\nOpen-source contributions, internal frameworks, or published case studies are a strong plus.\n\nPython expertise; proficiency with ML/LLM stacks (PyTorch; scikit-learn; Transformers).\n\nLLM/agent frameworks such as LangChain, LlamaIndex, Semantic Kernel (or equivalents).\n\nAzure services: Azure Machine Learning, Azure OpenAI / Azure AI Foundry, Azure AI Search, Azure Data Factory, Azure DevOps, Microsoft Fabric; containers (Docker; AKS/Container Apps).\n\nData engineering fundamentals: SQL/NoSQL, ETL/ELT, APIs/eventing, and secure cloud data integration.\n\nFamiliarity with chemistry/cheminformatics data and tools is a plus.\n\nPython expertise; proficiency with ML/LLM stacks (PyTorch; scikit-learn; Transformers).\n\nLLM/agent frameworks such as LangChain, LlamaIndex, Semantic Kernel (or equivalents).\n\nAzure services: Azure Machine Learning, Azure OpenAI / Azure AI Foundry, Azure AI Search, Azure Data Factory, Azure DevOps, Microsoft Fabric; containers (Docker; AKS/Container Apps).\n\nData engineering fundamentals: SQL/NoSQL, ETL/ELT, APIs/eventing, and secure cloud data integration.\n\nFamiliarity with chemistry/cheminformatics data and tools is a plus.\n\nStartup mindset & ownership: proactive, resourceful, bias to action, comfortable with ambiguity, drives ideas to value.\n\nTechnical leadership: sets architecture, makes pragmatic trade-offs (quality, cost, latency), mentors peers.\n\nBusiness impact orientation: frames problems with stakeholders, defines KPIs, measures value, iterates quickly.\n\nCuriosity & craftsmanship: keeps pace with GenAI/agentic advances; evaluates and integrates what truly works.\n\nCommunication & evangelism: explains complex topics clearly to non-technical audiences; runs workshops/demos.\n\nCollaboration & knowledge sharing: reusable components, patterns, docs; uplifts team capabilities.\n\nResponsible AI: builds with security, privacy, and compliance by design.\n\nYou will get:\nCompetitive Compensation\n\n16 weeks of maternity/paternity and co-parenting leave\n\nTraining platform for all employees\n\nAdditional information:\nLocation: Shanghai, China\n\nHybrid working model\n\nAbout us\nSyensqo is a science company developing groundbreaking solutions that enhance the way we live, work, travel and play. Inspired by the scientific councils which Ernest Solvay initiated in 1911, we bring great minds together to push the limits of science and innovation for the benefit of our customers, with a diverse, global team of more than 13,000 associates. Our solutions contribute to safer, cleaner, and more sustainable products found in homes, food and consumer goods, planes, cars, batteries, smart devices and health care applications. Our innovation power enables us to deliver on the ambition of a circular economy and explore breakthrough technologies that advance humanity.\nAt Syensqo, we seek to promote unity and not uniformity. We value the diversity that individuals bring and we invite you to consider a future with us, regardless of background, age, gender, national origin, ethnicity, religion, sexual orientation, ability or identity. We encourage individuals who may require any assistance or accommodations to let us know to ensure a seamless application experience. We are here to support you throughout the application journey and want to ensure all candidates are treated equally. 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Docs: https://alion.io/developers"}}