Senior GenAI & RAG Data Scientist (Production)

RELX; Raleigh (NC); On-site; USD 105,000 - 175,000; Full time

Job summary

LexisNexis Legal & Professional is seeking a Senior Data Scientist II to advance generative AI, RAG, and agentic AI systems, with a strong software-engineering foundation. You will own production applications, improve drafting and retrieval workflows, and ensure robust observability and secure operations.

The role emphasizes independent design, refactoring, testing, deployment, and cross-functional delivery in a monorepo environment, using Python, OpenSearch/Solr, and state-of-the-art ML tooling.

Qualifications

• Advanced Python proficiency demonstrated through independently designing, implementing, debugging, testing, reviewing, and refactoring production applications.
• Strong command of Python fundamentals, standard data structures, common algorithms, object-oriented and functional design principles, type annotations, and time and space complexity analysis.
• Demonstrated ability to transform prototype or experimental code into modular, maintainable, observable, and production-ready systems.
• Strong understanding of software design principles, including separation of concerns, dependency injection, interface design, configuration management, and effective abstraction.
• Experience implementing automated unit, integration, regression, and end-to-end testing using tools such as pytest, including appropriate mocking of external services.
• Experience designing resilient distributed applications that account for timeouts, retries, rate limits, partial failures, malformed responses, idempotency, and graceful degradation.
• Experience with production observability, including structured logging, metrics, tracing, alerting, and incident troubleshooting.
• Demonstrated ability to conduct rigorous code reviews and identify correctness, maintainability, performance, security, testing, and operational risks.
• Experience taking technical ownership of applications across their lifecycle, from design and experimentation through deployment, monitoring, incident response, and ongoing improvement.
• Strong understanding of production LLM concerns, including structured output validation, context management, model and tool failures, prompt versioning, token and cost controls, security, and evaluation.

Responsibilities

• Architect modular agentic applications with clear separation among retrieval, prompt construction, model invocation, tool execution, state and history management, orchestration, validation, and response formatting.
• Independently refactor complex or legacy Python code to improve correctness, readability, modularity, extensibility, testability, and runtime performance.
• Own production readiness for AI components, including input validation, exception handling, timeout management, retries with backoff, fallback behavior, configuration management, and secure handling of credentials.
• Establish observability for LLM and retrieval workflows through structured logging, metrics, distributed tracing, alerting, and actionable error reporting.
• Design clear interfaces and data contracts between retrieval, orchestration, model, and downstream application components.
• Write comprehensive unit, integration, regression, and end-to-end tests, including tests for failure modes, malformed model responses, empty retrieval results, and unavailable dependencies.
• Review Python and agentic application code, identify architectural and operational risks, and provide actionable feedback aligned with production engineering standards.
• Diagnose and optimize latency, memory usage, retrieval performance, token consumption, model cost, and application scalability.
• Apply appropriate data structures, algorithms, and computational-complexity analysis when designing and optimizing solutions.
• Participate in production deployments, incident investigation, root-cause analysis, remediation, and continuous reliability improvements.

Skills

Advanced Python proficiency

Python fundamentals

Distributed systems

Automated testing (pytest)

Observability & monitoring

Code review

Production ownership

LLM & retrieval experience

Tools

OpenSearch

Solr

Job description

LexisNexis Legal & Professional is seeking a Senior Data Scientist II to advance generative AI, RAG, and agentic AI systems, with a strong software-engineering foundation. You will own production applications, improve drafting and retrieval workflows, and ensure robust observability and secure operations.

The role emphasizes independent design, refactoring, testing, deployment, and cross-functional delivery in a monorepo environment, using Python, OpenSearch/Solr, and state-of-the-art ML tooling.