Applied AI Solutions Engineer – PHB Commercial Transformation

Interested in a career that matters? At Novonesis, we believe biology holds the key to solving some of the world's biggest challenges. To unlock that potential, we are scaling AI capabilities that help our sales, marketing, and technical service teams work smarter, serve customers better, and create measurable business impact. As an Applied AI Solutions Engineer , you will join the Strategy Deployment team within the Planetary Health Biosolutions (PHB) business division. Working at the intersection of applied AI, commercial problem-solving, and business transformation, you will help turn high-value opportunities into practical AI solutions that transform how commercial teams operate. This is a forward-deployed engineering opportunity for someone who wants to combine strong technical expertise with visible business impact. You will move between commercial workflows, solution design, and hands-on development, owning the journey from identifying a business challenge to delivering solutions that users genuinely adopt and value. The Role & Your Impact In this role, you will design, build, deploy, and continuously improve AI solutions that enable PHB commercial teams to work more effectively and create measurable business outcomes. Key Responsibilities AI Solution Development Work directly with PHB commercial teams to understand workflows, user needs, and business challenges, translating them into practical AI solutions. Design and build AI agents, applications, and workflows utilizing prompting, grounding, retrieval, tool usage, actions, and orchestration. Develop thin-slice solutions to rapidly validate user value and technical feasibility. Build iteratively with users, leveraging feedback and evidence to improve, redesign, or discontinue solutions where appropriate. Integration & Engineering Securely connect AI solutions to enterprise platforms and data sources, including Salesforce, Microsoft 365, and approved AI services. Build integrations using APIs, connectors, and workflow technologies with appropriate identity, security, and approval controls. Work with structured and unstructured data, enterprise knowledge sources, and retrieval-augmented generation (RAG) patterns. Design and develop solutions with security, privacy, responsible AI, maintainability, and reuse in mind. Evaluation, Deployment & Scale Design and execute functional, integration, regression, and AI-specific evaluations covering groundedness, retrieval quality, agent behavior, reliability, and user experience. Test solutions with end users and make data-driven decisions on whether to scale, iterate, or stop initiatives. Deploy, monitor, support, and continuously improve production solutions in partnership with Central IT, ComEx, and other enterprise stakeholders. Document solutions, technical patterns, and key learnings to support ongoing maintenance, reuse, and scale across the organization. What You'll Need to Be Successful Required Qualifications Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related discipline, or equivalent practical experience. 2–6 years of relevant professional experience building and deploying AI, GenAI, or agent-based solutions in production environments. Hands-on experience with LLMs, AI agents, prompting, grounding, retrieval-augmented generation (RAG), tool use, and orchestration frameworks. Strong programming skills in Python and/or JavaScript/TypeScript. Experience working with APIs, data integration, Git/version control, testing practices, and CI/CD pipelines. Experience building workflows and integrations using technologies such as Microsoft Power Platform, Power Automate, Azure Logic Apps, Salesforce Flow, REST APIs, or similar tools. Experience taking AI solutions from prototype through deployment, monitoring, troubleshooting, and continuous improvement. Good understanding of cloud platforms, identity and access management, secure enterprise data hand