Backend Software Engineer II (AI)

TL;DR

Backend Software Engineer II (AI): Develop reliable, secure, and performant APIs for business and financial generative AI applications, agents, data retrieval, and extraction with an accent on scalable distributed systems. Focus on designing system architectures, API specifications, prototyping, and ensuring performance in loosely-coupled environments.

Location: Cambridge, Massachusetts or New York, New York, United States

Salary: $130k–$175k

Company

S&P Global’s hub for AI innovation and transformation with expertise in machine learning, natural language processing, and data discovery for financial applications.

What you will do

• Design, develop, test, document, deploy, maintain, and improve software for APIs.
• Collaborate with Machine Learning, Product, Infrastructure, and Applications teams on system architectures, API specs, requirements, and estimates.
• Test assumptions through instrumentation and prototyping.
• Promote technical development via code reviews and knowledge sharing.

Requirements

• At least two years developing SaaS applications in a team
• Experience with SaaS backends and APIs using various tools
• Work across full software development lifecycle
• Turn business requirements into technical plans
• Reasoning on loosely-coupled systems behavior and performance
• Proficiency in algorithms (time/space complexity), data structures, software architecture
• Thoughtful communication skills (verbal and written)

Nice to have

• Experience deploying production code in highly scalable distributed systems

Culture & Benefits

• Top-of-market benefits: medical, dental, vision insurance (100% company-paid premiums)
• Unlimited Paid Time Off, 26 weeks 100% paid Parental Leave
• 401(k) with 6% employer matching, tuition assistance up to $20k, professional education budget
• Snacks, catered lunches, dog-friendly office (Cambridge), bike sharing
• Compassion/elder care leave, mentoring, conference opportunities
• Open, honest communication; autonomy; diverse perspectives; engineering best practices