Staff Software Engineer, Cloud Developer Experience

The world’s most sophisticated companies rely on AlphaSense to remove uncertainty from decision-making. With market intelligence and search built on proven AI, AlphaSense delivers insights that matter from content you can trust. Our universe of public and private content includes equity research, company filings, event transcripts, expert calls, news, trade journals, and clients’ own research content.

The acquisition of Tegus by AlphaSense in 2024 advances our shared mission to empower professionals to make smarter decisions through AI-driven market intelligence. Together, AlphaSense and Tegus will accelerate growth, innovation, and content expansion, with complementary product and content capabilities that enable users to unearth even more comprehensive insights from thousands of content sets. Our platform is trusted by over 6,000 enterprise customers, including a majority of the S&P 500. Founded in 2011, AlphaSense is headquartered in New York City with more than 2,000 employees across the globe and offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland. Come join us!

The Cloud DX team owns the outer loop of software development at AlphaSense, everything from the moment code is pushed to source control to the moment it reaches production, for ~400 engineers distributed across the globe. We've built a solid delivery foundation and we're now raising the bar toward industry-leading CI/CD. Progressive delivery, canary deployments, automated rollbacks, trunk-based development, GitOps workflows: these aren't aspirations but the direction we're actively building, and we're looking for passionate engineers to help shape what best-in-class looks like.

This is a Staff Engineer role with real breadth. It requires both operational and software development skills, the ability to lead projects and collaborate across timezones with Engineering leaders and very senior Engineers across dozens of teams. You'll design and operate production-grade delivery infrastructure, contribute hands-on in Go and Python, and help shape the engineering practices a global organisation depends on. 
We're looking for someone who genuinely embraces AI tooling in their day-to-day work, appreciates the productivity value it brings, and is motivated to push that further, both in their own practice and by helping embed AI-assisted workflows into the SDLC for the wider engineering organization.

• Strong experience in Platform Engineering or Developer Experience roles focused on CI/CD and delivery, ideally at companies with 200+ engineers
• Experience owning and operating a CI/CD platform at admin and architecture level, including security, configuration, and enablement
• Proven ability to design and operate delivery systems at scale
• Hands-on software development experience including production-quality Go
• Passion for progressive delivery practices: canary deployments & automated rollbacks
• Familiarity with cloud-native architectures and Kubernetes-based platforms
• Passion for using AI to improve engineering velocity, quality, and developer experience
• Strong collaboration skills and ability to influence across teams
• [Nice to Have] Built and/or maintained an IDP in production 
• [Nice to Have] Previous experience working in both Software and Platform Engineering teams 
• [Nice to Have] Interest in Security and an understanding of RBAC and OAuth

• →Own and evolve our CI/CD architecture and the developer-facing experience
• →Drive continuous improvements to pipeline reliability, speed, and predictability
• →Define paved paths that let product teams ship fast and safely without deep platform knowledge
• →Own the delivery process end-to-end, from code merge to production
• →Champion progressive delivery practices: canary deployments & automated rollbacks
• →Build tooling that makes deployments observable, repeatable, and self-service
• →Own and evolve our Internal Developer Portal and the self-service experience around it
• →Partner with Cloud Platform teams on infrastructure while owning the developer-facing delivery
• →Embed AI tooling into delivery workflows in ways that create lasting productivity gains