Senior Software Engineer / Senior AI Engineer

RELX•Philadelphia, MA

4d•$86,600 - $144,400

About The Position

As a Senior AI Engineer, you will build and ship AI-powered features as part of a cross-functional Innovation Squad embedded within a business function. You will set technical direction to production standards and work autonomously within a defined problem, building and testing tool use, retrieval pipelines, and agent workflows. The role integrates AI capabilities into enterprise systems and contributes to evaluation, observability, and guardrails for agentic systems. You will maintain high code quality, flag risks and blockers early, and work with host-function stakeholders to ensure solutions fit real workflows. You will also support handover and capability-building so solutions remain owned and operable after the squad moves on. The team works problem-first, turning internal AI experimentation into validated, reusable solutions and building capabilities that support customer value and growth.

Requirements

3+ years of software engineering experience.
Hands-on experience building LLM-powered applications in production, such as RAG, tool-augmented agents, or agentic workflows.
Comfort working autonomously within a defined problem, pushing back when something does not make sense, and delivering in short, time-boxed cycles focused on validated outcomes.
Experience building RAG pipelines, tool-augmented agents, and agentic workflows; familiarity with prompt engineering, context management, evaluation, and observability.
Understanding of how agents use memory, tools, and retrieval to complete multi-step tasks.
Experience integrating AI into existing systems through APIs and data pipelines.
Experience with AWS, Azure, or GCP.
Knowledge of CI/CD, modern SDLC, TDD, and code review.
Experience with relational, columnar, and vector stores, grounded in sound data-modeling principles.
Experience with Python, Java, TypeScript/JavaScript, SQL, and relevant AI SDKs.
Clear written and verbal communication with technical peers and stakeholders.
Ability to instrument solutions to capture usage, productivity, and quality metrics against established baselines.

Responsibilities

Build prototypes and proofs of concept, and ship agentic AI solutions to production standards 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 reusable solutions and contribute patterns, reference implementations, and starter kits for use across functions.
Implement solutions to capture outcome data against baselines.
Work with host-function stakeholders to ensure solutions fit real workflows.
Support handover and capability-building in the host function so solutions remain owned and operable.