Senior Software Engineer

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Revenue Analytics, Inc.

WebsiteLinkedInAll Job Openings

51 - 200 employees

☁️ SaaS

🏢 Enterprise

🤝 B2B

SaaS • Enterprise • B2B

Revenue Analytics, Inc. is a company that specializes in providing advanced pricing and revenue management solutions for various industries, including hospitality, manufacturing, distribution, private equity, media, and passenger rail. They are pioneers in the field of Revenue Management, helping businesses make profitable pricing decisions at scale with their next-generation software. Their products, such as N2Pricing™, Pricing-as-a-Service™, RateOptics™, and FareVantage™, are designed to tackle complex pricing challenges and improve revenue outcomes for their clients. Revenue Analytics is trusted by top businesses to deliver confidence and data for making strategic pricing decisions.

📋 Description

• Own full-stack features from start to finish — partnering with Product on discovery, building across our Python back-end and Angular front-end, and supporting your work in production. • Partner with product managers to turn ambiguous business problems into well-scoped, high-impact software — deciding what to build, and what not to. • Design and scale the data systems behind our products, working with large, sometimes messy datasets across AWS and our data lake. • Build AI/ML and LLM-powered features into the product, and own the full lifecycle — from prototyping through evaluation, monitoring, cost, and reliable production performance. • Mentor engineers and raise the team's bar through pairing, code review, and everyday craft.

🎯 Requirements

• 7+ years shipping production software full-stack, ideally in a SaaS / multi-tenant environment. • Strong CS fundamentals and fluency in a core language (Python preferred). • Deep experience with large datasets — strong SQL, relational databases (PostgreSQL/Redshift), and data lakes on AWS (S3, Athena, Lambda). • Front-end development (Angular or similar), able to own features end to end. • AI/ML and LLM fluency, including building AI/ML features into products. • Demonstrated use of AI coding assistants (Claude Code, Cursor, Copilot) to accelerate delivery while improving quality. • Demonstrated technical leadership and mentoring.