Senior Developer focused on backend systems development using Java and Spring Boot. Responsible for microservices architecture, API development, and ensuring application security.
About the role
- Principal Software Engineer designing and delivering agentic AI systems for Elsevier Health Education. Leading development of scalable software while collaborating across teams in a mission-driven organization.
Responsibilities
- Lead the design and development of agentic AI systems
- Architect and deliver autonomous workflows, multi-step reasoning agents, and AI copilots that solve complex business problems across the organization.
- Define and implement LLM-powered architectures
- Design scalable solutions leveraging large language models, orchestration frameworks (e.g., LangChain, OpenAI APIs), and modular service patterns to enable reusable AI capabilities.
- Build and optimize tool-augmented agents
- Develop agents that effectively utilize function calling, retrieval-augmented generation (RAG), memory systems, and planning/execution loops to perform reliable, context-aware tasks.
- Establish best practices for prompt engineering and evaluation
- Create standardized approaches for prompt design, testing, benchmarking, and continuous improvement to ensure high-quality outputs in production environments.
- Implement production-grade guardrails and safety mechanisms
- Design and enforce controls for hallucination mitigation, output validation, policy compliance, and safe execution of AI-driven workflows.
- Drive AI system performance and reliability
- Optimize latency, throughput, and cost efficiency of AI systems while ensuring high availability, observability, and fault tolerance across agent workflows.
- Design and manage retrieval systems
- Architect solutions using embeddings, vector databases, and hybrid search techniques to enable accurate, scalable knowledge retrieval.
- Integrate AI capabilities into enterprise platforms
- Embed AI services into existing products, APIs, and developer workflows, ensuring seamless interoperability with enterprise systems and data sources.
- Lead technical strategy and cross-functional alignment
- Partner with product, data, and engineering leaders to define AI roadmaps, prioritize initiatives, and align solutions with business objectives.
- Champion responsible AI practices
- Ensure systems adhere to standards for fairness, bias mitigation, transparency, and governance, while meeting regulatory and organizational compliance requirements.
- Mentor and elevate engineering teams
- Provide technical leadership, guide architectural decisions, and mentor engineers in building scalable, maintainable AI systems.
- Continuously evaluate emerging technologies
- Stay at the forefront of advancements in AI/ML, agent frameworks, and tooling, and drive adoption of innovations that create competitive advantage.
Requirements
- Experience designing, building, or integrating agentic AI systems (e.g., autonomous workflows, multi-step reasoning agents, AI copilots).
- Hands-on experience with LLMs and orchestration frameworks (e.g., LangChain, OpenAI APIs, or similar).
- Ability to design tool-augmented agents (function calling, retrieval-augmented generation, memory systems, planning/execution loops).
- Experience with prompt engineering, evaluation, and guardrails for production-grade AI systems.
- Understanding of AI system architecture, including latency, cost optimization, observability, and reliability of agent workflows.
- Familiarity with vector databases, embeddings, and retrieval systems.
- Experience integrating AI capabilities into enterprise systems and developer workflows.
- Knowledge of responsible AI practices, including safety, bias mitigation, and governance.
Benefits
- health insurance
- retirement plans
- paid time off
- flexible work arrangements
- professional development
- annual incentive bonus
Job title
Job type
Experience level
Salary
Degree requirement
No Education Requirement
Location requirements
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