AI Engineer

About the role

As an AI Engineer you will build and ship AI‑powered features as part of a cross‑functional Innovation Squad, working inside a business function. You will deliver the set technical direction to production standard, interfacing with host‑function stakeholders to ensure your solutions fit real workflows, not assumed ones.

• Build prototypes, proofs of concept, and ship agentic AI solutions to production standard within a defined technical approach.
• Implement and test tool use, retrieval pipelines, and agent workflows.
• Contribute to evaluation, observability, and guardrails for agentic systems.
• Integrate AI capabilities into existing enterprise workflows and systems.
• Maintain high code quality and documentation so patterns can be reused.
• Flag technical risks and blockers early.
• Interface with technical peers to finalize requirements and complete moderately complex bug fixes.
• Build solutions for reuse, contributing to patterns, reference implementations, and starter kits.
• Instrument solutions to capture outcome data against baselines.
• Support handover and capability‑building so the solution is owned and operable after the squad moves on.
• Keep abreast of new technology developments and take on related responsibilities as the squad’s needs evolve.

• Engineering experience: 3+ years in software engineering, with hands‑on experience building LLM‑powered applications in production (RAG, tool‑augmented agents or agentic workflows).
• Education:
  
  BS in Engineering, Computer Science, or equivalent.
• Ways of working:
  Comfortable working autonomously within a defined problem, delivering in short, time‑boxed cycles where validated outcomes matter more than perfect solutions.
• Agentic AI / LLMs:
  Building RAG pipelines, tool‑augmented agents and agentic workflows; familiar with prompt engineering, context management, evaluation and observability.
• Agent fundamentals:
  Understands how agents use memory, tools, and retrieval to complete multi‑step tasks.
• Enterprise integration:
  Integrating AI into existing systems via APIs and data pipelines.
• Cloud: AWS, Azure, or GCP.
• Delivery: CI/CD, modern SDLC, TDD, and code review.
• Data:
  Working with relational, columnar, and vector stores, grounded in sound data‑modelling principles.
• Languages:
  
  Python, Java, Type Script/JavaScript, SQL, and relevant AI SDKs.
• Communication:
  Clear written and verbal communication with technical peers and stakeholders.
• Measurement:
  Instrumenting solutions to capture usage, productivity, and quality metrics against established baselines.

Join our team and contribute to a culture of innovation, collaboration, and excellence. We promote a healthy work/life balance, offer flexible hours, generous vacation entitlement, pension plan, parental leave, study assistance, sabbaticals, employee discounts, and an employee assistance program. We are committed to providing a fair and accessible hiring process and to supporting continuous discovery while upholding the highest standards of professional ethics.

Elsevier is an equal‑opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. We support continuous discovery and uphold the highest standards of content integrity, reliability, and reproducibility.