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# Senior Software Engineer II

- **Company:** RELX Group plc
- **Location:** Oklahoma City, OK, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** .NET Framework, Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, Microsoft Azure, C Sharp (Programming Language), Code Review, Encodings, Elasticsearch, Identity and Access Management, Information Retrieval, JSON, Python (Programming Language), Key Management, PostgreSQL, Microsoft SQL Server, Node.Js, Regression Testing, OpenAI, Software Engineering, Strategies of Testing, TypeScript, Unstructured Data, Software Organization, Data Processing, Data Storage Technologies, Test-Driven Development (TDD), Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, AI Platforms, Kubernetes, Information Technology, Low Latency, Deployment Automation, Invoking Functions, Docker
- **Published:** October 9, 2026
- **Apply:** https://relx.wd3.myworkdayjobs.com/en-US/relx/details/Oklahoma-City-OK/Senior-Software-Engineer-II_R118850

## About the Role

* 5+ years of software engineering experience, including 2+ years building and shipping LLM-based or ML-based systems to production

 * BS in Engineering/Computer Science or equivalent experience required

 * Demonstrated track record of owning an AI feature or service end to end: design, evaluation, deployment, and monitoring
 * Expert proficiency in TypeScript/Node.js and/or Python; working knowledge of C#/.NET is a plus

 * Hands-on experience with LLM platforms and APIs (Azure OpenAI or equivalent), including prompt design, tool/function calling, structured outputs, and model selection tradeoffs
 * Experience building RAG pipelines: chunking, embedding, hybrid retrieval, reranking, and grounding/citation

 * Strong understanding of schema-driven structured extraction from unstructured data (Zod, Pydantic, JSON Schema) and validation strategies

 * Experience with evaluation frameworks for AI systems: golden datasets, LLM-as-judge, precision/recall on extraction tasks, regression testing of prompts and agents

 * Strong SQL proficiency and understanding of relational and vector data storage (SQL Server, PostgreSQL, Elasticsearch/vector stores)

 * Working experience with both AWS and Azure, including compute, storage, networking, IAM, and managed AI services; containerized deployment (Docker, Kubernetes or equivalent), secrets management, and observability (token usage, latency, cost attribution)
 * Strong knowledge of software development best practices, test-driven development, and code review

## Description

This position performs complex research, design, and software development assignments in the design and delivery of production AI systems, including agentic workflows, LLM-powered pipelines, retrieval-augmented generation (RAG), and structured extraction services. The position provides direct input to project plans, schedules, and methodology for cross-functional AI products; performs system design, typically across multiple systems and data sources; mentors more-junior members of the team; and works directly with business users and stakeholders to translate ambiguous, unstructured problems into measurable AI solutions., * Design, build, and deploy production AI systems including agentic workflows, RAG services, and extraction pipelines across multiple business units

 * Interface with business stakeholders and technical team members to scope AI use cases, define success metrics, and finalize requirements

 * Write and review detailed technical specifications and architecture documents for complex AI system components

 * Build and maintain evaluation harnesses; establish accuracy, latency, and cost baselines and monitor them in production

 * Implement responsible AI practices: data handling, PII controls, hallucination mitigation, auditability, and human review where required

 * Own cost and performance of LLM workloads, including model selection, caching, and usage attribution
 * Build and maintain CI/CD pipelines and deployment automation for AI services across AWS and Azure environments

 * Operate in Agile development environments while collaborating with key stakeholders across engineering, product, and business functions

 * Mentor less-senior engineers on AI system design, evaluation methodology, and production readiness