Manager, AI Enablement

Job description

By clicking the “Apply” button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’s Privacy Notice and Terms of Use.  I further attest that all information I submit in my employment application is true to the best of my knowledge. Job Description Role: - Manager, AI Enablement Location: - Bengaluru The Future Begins Here At Takeda, we are leading digital evolution and global transformation. By building innovative solutions and future-ready capabilities, we are meeting the need of patients, our people, and the planet. Bengaluru, the city, which is India’s epicenter of Innovation, has been selected to be home to Takeda’s recently launched Innovation Capability Center. We invite you to join our digital transformation journey. In this role, you will have the opportunity to boost your skills and become the heart of an innovative engine that is contributing to global impact and improvement.   At Takeda’s ICC we Unite in Diversity Takeda is committed to creating an inclusive and collaborative workplace, where individuals are recognized for their backgrounds and abilities they bring to our company. We are continuously improving our collaborators journey in Takeda, and we welcome applications from all qualified candidates. Here, you will feel welcomed, respected, and valued as an important contributor to our diverse team OBJECTIVES / PURPOSE The AI Solutions Engineer will accelerate Takeda's AI-driven commercial transformation by identifying, designing, and delivering AI-native solutions that solve high-priority business problems and reimagine workflows. This role combines expertise in AI, software engineering, and product development to rapidly move from concept to production, enabling scalable adoption of AI across commercial functions. We're looking for an AI Solutions Engineer who thinks in AI-native patterns by default: someone who doesn't just bolt a model onto an existing process but reimagines the workflow around what modern AI systems make possible. You'll bring a blend of data science depth and software engineering discipline, applying modern SDLC practices to a domain that's evolving fast. ACCOUNTABILITIES AI Solution Design and Engineering • Design, develop, and deploy AI-powered applications, copilots, agents, and workflow automation solutions that address prioritized commercial business challenges. • Translate business requirements and user workflows into technical specifications, solution architectures, and production-ready implementations. • Develop and integrate Generative AI, Agentic AI, Retrieval-Augmented Generation (RAG), machine learning, and automation capabilities into scalable enterprise solutions. • Rapidly prototype, evaluate, and iterate on proof-of-concepts (POCs) to validate business value and technical feasibility before production deployment. • Build reusable components, APIs, services, and frameworks that accelerate AI solution development across commercial use cases.  AI-Driven Workflow Transformation • Apply AI-native thinking to identify opportunities where AI can simplify, augment, or fundamentally redesign commercial workflows and decision-making processes. • Partner with business stakeholders to understand processes, pain points, and success criteria, translating them into scalable AI-enabled solutions. • Evaluate emerging AI technologies, tools, and frameworks, recommending appropriate approaches based on business needs and technical constraints.  Software Engineering and Delivery Excellence • Develop production-grade applications following modern software engineering principles, including test-driven development, code reviews, CI/CD, observability, and secure coding practices. • Utilize GitHub-based development workflows, version control, and collaborative engineering practices to support scalable solution delivery. • Contribute to specification development and spec-driven implementation approaches, ensuring alignment between business requirements and delivered solutions. • Support deployment, monitoring, performance optimization, and ongoing enhancement of AI applications within enterprise environments.  KNOWLEDGE, SKILLS & EXPERIENCE Required • Bachelor's required in Computer Science Engineering, Data Science, or a related field. • 7+ years of professional experience in data science, software engineering, or AI/ML solutions role • 2+ years of hands-on experience building production-grade applications, prototypes, and POCs • Strong foundation in both data science and computer science — comfortable moving between model development and application engineering • Hands on development experience on cloud platforms (AWS, Azure, or GCP) • Demonstrated experience with modern software development lifecycle (SDLC – Agile) practices: version control (Git/GitHub), code review, testing, CI/CD, and iterative delivery • Experience with spec development and spec-driven development practices • Hands-on experience building with LLMs, generative AI, or agentic AI systems (APIs, frameworks, orchestration, prompt/context engineering) • Strong written and verbal communication skills, including the ability to translate ambiguous business problems into technical specs and vice versa • Proven ability to manage multiple projects simulta