Elsevier · 5 hours ago
Retrieval-Augmented Generation (RAG) System - Senior Software Developer
Philadelphia, PA
Full-time
Hybrid
Senior Level
5+ years expElsevier is seeking a Senior Software Developer to work on a healthcare centered production-scale RAG system. The role involves designing, implementing, and operating end-to-end RAG pipelines while collaborating with various teams to ensure the delivery of reliable and scalable systems.
ContentContent DiscoveryDeliveryHealth CareInformation ServicesInformation TechnologyPublishing
Hiring Manager
ALAN KRULL
Responsibilities
Architect, implement, test, and operate end-to-end RAG workflows:
Ingest and normalize documents from diverse sources
Generate and manage embeddings; index and query vector databases
Retrieve relevant passages, apply reranking or fusion strategies, and feed prompts to LLMs
Build scalable, low-latency services and APIs (Python preferred; other languages acceptable) and ensure production-grade reliability (monitoring, tracing, alerting)
Integrate with vector databases and embedding pipelines and optimize for latency, throughput, and cost
Design and implement ML Ops workflows: model/version management, experiments, feature stores, CI/CD for ML-enabled services, rollback plans
Develop robust data pipelines and governance around ingestion, provenance, quality checks, and access controls
Collaborate with data engineers to improve retrieval quality (embedding strategies, reranking, cross-encoder models, prompt engineering) and implement evaluation metrics (precision/recall, MRR, QA accuracy, user-centric metrics)
Implement monitoring and observability for RAG components (latency, success rate, cache hit rate, retrieval quality, data drift)
Ensure security, privacy, and compliance (authentication, authorization, data masking, PII handling, audit logging)
Optimize for scalability and reliability in cloud environments (AWS/GCP/Azure) and containerized deployments (Docker, Kubernetes)
Contribute to architecture decisions, drive technical debt reduction, and mentor junior engineers
Collaborate with product, design, and data teams to translate requirements into robust software solutions
Document APIs, runbooks, and architectural decisions; participate in code reviews and design reviews
Qualification
Required
5+ years of professional software engineering experience designing and delivering production systems
Strong programming skills (Python required; NodeJs a plus)
Deep understanding of retrieval-augmented or application-scale NLP systems and practical experience building RAG-like pipelines
Hands-on experience with ML workflow tooling and MLOps concepts (model serving, versioning, experiments, feature stores, reproducibility)
Proficiency with cloud infrastructure and modern software practices (AWS/GCP/Azure; Docker; Kubernetes; CI/CD)
Strong problem-solving skills, excellent communication, and ability to work with cross-functional teams
Familiarity with data governance, privacy, and security best practices
Preferred
Experience with agentic workflow tools (LangGraph) and familiarity with prompt engineering for LLMs
Exposure to working with and evaluating different LLMs
Knowledge of evaluation methodologies for retrieval and QA systems and the ability to set up A/B tests and dashboards
Experience with data processing frameworks (SQL, Pandas, Spark) and working with large-scale data pipelines
Background in performance optimization for low-latency AI services (MLflow)
Experience with monitoring and logging via New Relic, K9s, Portkey, etc
Experience with minimizing token usage and cost optimization
Comfortable with design and implementation of security controls for data-intensive AI systems
Company
Elsevier
Elsevier is a world-leading provider of information solutions that enhance the performance of science, health, and technology. It is a sub-organization of RELX.
5001-10000 employees
H1B Sponsorship
Elsevier has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (32)
2024 (17)
2023 (28)
2022 (46)
2021 (28)
2020 (19)
Funding
Current Stage
Late StageTotal Funding
unknown2003-09-01Private Equity
Leadership Team
Dan Olley
EVP & CTO - Elsevier
C
Catherine Thrift
CFO
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