Senior Software Engineer - External Products at Silverchair in United States

Job description

• We're looking for a Senior Software Engineer to help build the next generation of tools for researchers and publishers. You'll work on external-facing products that serve scholarly content at scale — the search, discovery, and peer review systems that thousands of researchers depend on every day.
• This is a hands-on engineering role. You'll design and build the backend services, data pipelines, and search infrastructure that need to be fast, reliable, and correct. Some of what we're building leans on AI and machine learning, and you'll have room to work on that if it interests you — but we're hiring for engineering fundamentals first.
• Scientific research drives human progress — but only if it can be found, trusted, and used. The systems that connect researchers to knowledge matter enormously.
• Research discovery: Tools that help researchers find relevant work faster, surface unexpected connections, and stay current in rapidly evolving fields
• Research integrity: Systems that support rigorous peer review and help maintain trust in the scientific record
• Access and equity: Making scholarly content more accessible and usable for researchers everywhere
• We're remote-first, engineering-driven, and committed to building software that lasts. If you want your work to matter beyond the next sprint, we'd like to hear from you.

Responsibilities

• Design, build, and operate scalable backend services and APIs that process and serve scholarly content
• Build and maintain data pipelines handling high-volume ingestion, transformation, and indexing
• Build the services and APIs behind user-facing product experiences, working closely with design, product, and frontend engineers
• Design search and discovery systems that return the right result, fast, across large corpora
• Build upstream tooling for peer review and editorial workflows
• Integrate LLMs and other AI capabilities into existing high-volume systems, with the same rigor around latency, cost, and failure handling you'd apply to any dependency
• Evaluate where AI meaningfully improves a product experience — and where a conventional approach is the better engineering call
• Own systems in production: instrument, monitor, debug, and optimize for performance, reliability, and cost
• Make architectural decisions and document the tradeoffs behind them
• Review code, mentor other engineers, and raise the bar for engineering quality across the team
• Collaborate with product and engineering peers to translate user needs into production systems

Requirements

• 7+ years of professional software engineering experience
• Strong proficiency in a modern backend language — Python, Go, Java, C#, or similar — and the ability to pick up others
• Demonstrated experience building and operating production systems at scale
• Solid grounding in distributed systems: concurrency, caching, queuing, failure modes, and how systems behave under load
• Strong SQL and relational data modeling skills
• Experience building search over large corpora — indexing, relevance, and ranking
• BS in Computer Science or equivalent practical experience
• You're a strong engineer first — you've built systems that handle real-world scale and complexity
• You care about the details: clean code, thoughtful architecture, reliable infrastructure
• You've owned software in production and know what it takes to keep it healthy
• You're curious about where AI fits into the products you build, without needing it to be the whole job
• You're energized by mission-driven work and want your engineering to matter
• You thrive in a technology-forward environment that values learning and experimentation
• Experience with event-driven architectures and streaming data
• Cloud platform experience (Azure preferred)
• Applied experience with LLMs and retrieval-augmented systems in production
• Experience with semantic search and hybrid retrieval alongside traditional keyword search
• Familiarity with ML pipelines and model deployment
• Experience integrating AI models with external tools and data sources
• Infrastructure-as-code and platform/DevOps experience

Skills

Required

• Python
• Go
• Java
• C#
• SQL
• Distributed systems
• Search indexing and relevance
• LLMs
• Retrieval-augmented systems
• Semantic search
• Hybrid retrieval
• ML pipelines