Principal Software Engineer (Agentic AI)

TL;DR

Principal Software Engineer (Agentic AI): Lead the design and development of agentic AI systems for scalable content ingestion pipelines powering health education platforms with an accent on autonomous workflows, multi-step reasoning agents, and AI copilots. Focus on designing LLM-powered architectures, tool-augmented agents with RAG and planning loops, production-grade guardrails, and integrating AI into enterprise systems.

Location: St. Louis, MO; Houston, TX; Raleigh, NC

Salary: $115,400 - $192,300

Company

Global organization with 10,000 employees providing knowledge and analytics for research, health, and education through platforms like ScienceDirect, Scopus, ClinicalKey, and Sherpath.

What you will do

• Lead design and development of agentic AI systems including autonomous workflows, multi-step reasoning agents, and AI copilots.
• Define and implement scalable LLM-powered architectures using orchestration frameworks like LangChain and OpenAI APIs.
• Build and optimize tool-augmented agents with function calling, RAG, memory systems, and planning/execution loops.
• Establish best practices for prompt engineering, evaluation, benchmarking, and continuous improvement.
• Implement guardrails for hallucination mitigation, output validation, policy compliance, and safe AI execution.
• Drive performance optimization for latency, throughput, cost, availability, observability, and fault tolerance.
• Design retrieval systems using embeddings, vector databases, and hybrid search techniques.
• Integrate AI into enterprise platforms, products, APIs, and developer workflows.
• Lead technical strategy, cross-functional alignment, responsible AI practices, and mentor engineering teams.

Requirements

• Experience designing, building, or integrating agentic AI systems like autonomous workflows and multi-step reasoning agents.
• Hands-on with LLMs, orchestration frameworks (LangChain, OpenAI APIs), tool-augmented agents, prompt engineering, evaluation, and guardrails.
• Understanding of AI architecture including latency, cost optimization, observability, reliability, vector databases, embeddings, and retrieval.
• Experience integrating AI into enterprise systems and developer workflows.
• Knowledge of responsible AI practices: safety, bias mitigation, governance.

Culture & Benefits

• Country-specific benefits including health, well-being support, and annual incentive bonus.
• Commitment to inclusion, diversity, equity, and fair hiring process with accommodations available.
• Part of RELX, focusing on societal progress in research and healthcare.