Artificial Intelligence Engineer

Title - Product SpecialistType - Contract Location - Remote Roles and Responsibilities:Lead Agentic AI product development by identifying, defining, and prioritizing AI, Generative AI, and Agentic AI use cases aligned with business value and technical feasibility.Define agent behaviors, prompts, workflows, knowledge sources, tool integrations, and human-in-the-loop processes.Collaborate hands-on with engineers, data scientists, and AI teams to design, prototype, and deliver agentic AI solutions.Rapidly prototype agent experiences using modern AI development tools and frameworks.Explore concepts including multi-agent systems, agent orchestration, Retrieval-Augmented Generation (RAG), and enterprise knowledge workflows.Develop proof-of-concepts and early product experiences with customers and SMEs to validate value propositions.Support transition of prototypes into scalable, production-ready enterprise solutions.Own and manage the product backlog, translating business and customer needs into detailed epics, user stories, and acceptance criteria.Develop and maintain product roadmaps aligned with strategic business priorities and technical capabilities.Lead product discovery, journey mapping, experimentation, prioritization, and iterative feedback cycles.Balance business value, user experience, technical feasibility, risk, and scalability in prioritization decisions.Define and monitor product KPIs, success metrics, adoption rates, and value realization.Engage directly with manufacturing stakeholders, SMEs, and business leaders to uncover challenges, workflows, and opportunities.Lead discovery workshops, co-creation sessions, pilots, and stakeholder feedback forums.Act as the voice of the customer within AI and digital product development teams.Translate complex business requirements into clear, technology-enabled solutions.Effectively communicate AI capabilities, limitations, risks, and tradeoffs to both technical and non-technical audiences.Collaborate across global, cross-functional teams in complex enterprise settings.Define and implement evaluation frameworks for AI and agentic solutions focusing on quality, accuracy, performance, and user experience.Support development of AI guardrails, human-in-the-loop oversight, and responsible AI governance practices.Monitor deployed agent performance and leverage user feedback and operational data for continuous improvement.Collaborate with engineering, data, quality, cybersecurity, and governance teams to ensure secure and scalable AI delivery.Manage AI/LLM lifecycle aspects including evaluation, monitoring, change management, and risk mitigation.Ensure solutions comply with regulatory and validation requirements in complex enterprise environments. Qualifications:Bachelor’s degree in Business, Engineering, Computer Science, Data Science, or a related field; advanced degrees preferred.5 – 7 years of experience in Product Management, Product Ownership, or Product Strategy roles with a focus on AI-enabled or digital products.Proven track record owning and delivering AI, Generative AI, or AI-enabled solutions in enterprise settings.Strong understanding of Agentic AI, AI agents, multi-agent systems, and AI orchestration concepts.Hands-on familiarity with AI/LLM technologies including prompt engineering, RAG, agent frameworks, evaluation, and guardrails.Extensive experience with Agile methodologies including backlog management, roadmap planning, user story creation, and iterative delivery.Exceptional stakeholder management, business requirement gathering, and discovery workshop facilitation skills.Strong data literacy with experience in enterprise data platforms, APIs, cloud technologies, and integrations.Experience working in large, complex enterprise environments, preferably in regulated industries such as pharmaceutical, biotech, life sciences, or manufacturing.Excellent communication and presentation skills with the ability to influence both technical and business stakeholders.Entrepreneurial, hands-on mindset with a builder mentality—comfortable prototyping, experimenting, and driving adoption from concept through production. Tools and Technologies:Agentic AI platforms and agent prototyping tools (e.g., Cursor, Lovable, Replit, Retool)Generative AI and Large Language Models (LLMs) such as OpenAI, Azure AI, AWS BedrockPrompt engineering and Retrieval-Augmented Generation (RAG) frameworksAI evaluation and monitoring platforms (e.g., Langfuse)AI guardrails and human-in-the-loop frameworksMLOps / LLMOps tools and best practicesCloud data platforms such as Snowflake, AWS, AzureProgramming and query languages: SQL, PythonEnterprise system integrations: MES, LIMS, SAP, Veeva, SCADA, OT/automation systemsProduct wireframing and design tools such as FigmaAPIs and modern data architectures for scalable enterprise solutions Preferred Industry Experience:Manufacturing, Smart Factory, pharmaceutical, biotech, life sciences, or other regulated industries.Experience delivering AI or digital solutions in manufacturing or regulated environments.Familiarity with manufacturing execution systems (MES), laboratory information management systems (LIMS), SAP, Veeva, and operational technology (OT) systems.Knowledge of quality systems, validation, change control, and computerized system validation (CSV) processes.Experience supporting global, multi-site enterprise deployments.