Advanced AI Engineer
Novo Nordisk5 hours ago
Bengaluru, IndiaMid Level
Responsibilities
- Take AI- and ML-centric use cases from discovery and rapid prototyping through production and continuous improvement.
- Engineer product-specific intelligence layers including data and feature transformations, decision logic, model and tool integrations, knowledge grounding, user-facing services, human oversight, and fallback behavior.
- Partner with product managers, domain experts, data scientists, engineers, and stakeholders to frame problems, define priorities, and establish product outcomes.
- Build reliable, scalable, secure, observable, tested, documented, and continuously improved AI solutions.
- Apply responsible AI, data integrity, validation, traceability, and auditability requirements in a regulated pharmaceutical environment.
- Use AI-assisted development tools and coding agents responsibly while maintaining code quality and review standards.
- Reuse shared AI Foundation capabilities and contribute reusable components, engineering patterns, and technical and product decisions.
Requirements
- Typically 2+ years of relevant experience building AI or software products.
- Experience taking AI-centric applications from idea to production and/or contributing to a product or platform team.
- Hands-on experience operating AI solutions in production, including evaluation, monitoring, reliability, and cost-performance trade-offs.
- Sound knowledge of statistical and machine-learning concepts and practical experience with modern AI application patterns.
- Strong programming and software engineering skills, including testing, documentation, APIs, and modern development practices, preferably with GitHub.
- Experience using AI-assisted development tools and coding agents as part of software delivery.
- Functional knowledge of modern AI interfaces and standards such as model and tool integrations, MCP, and observability approaches.
- Product sense, stakeholder collaboration skills, and the ability to explain technical choices to technical and non-technical audiences.
- Ability to independently take a defined AI solution component from problem framing through production and iteration.
- B.E., M.E., B.Tech., or M.Tech. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a closely related technical discipline.
- Desirable qualifications include familiarity with clinical NLP, drug discovery AI, regulatory automation, medical knowledge graphs, Databricks, Snowflake, Azure ML, Unity Catalog, MCP server design, and enterprise AI platform architecture patterns.
Benefits
- Continuous learning, career development, and benefits tailored to employees' life and career stages.
- Inclusive recruitment process and equal opportunity for all applicants.
- Opportunity to work with global product teams and build AI solutions supporting healthcare outcomes.