Software Engineer, Developer Platforms and Generative AI

About the Role

The mission of The New York Times is to seek the truth and help people understand the world. Independent journalism is at the core of our work, and our digital products, from News to Games to Cooking and Audio, help millions of people engage with that journalism every day.

Behind those products is a large engineering organization that relies on a reliable, modern, and AI-augmented developer platform.

The Developer Platforms organization provides cloud infrastructure and tooling to 100+ teams and 750+ engineers in NYT Product Engineering through an internal developer platform.

The Developer AI team focuses on developer experience with GenAI tools and agentic workflows. We provide paved paths that make it easier for product engineers to deliver and operate reliable software using AI-augmented workflows. We work with teams using tools like Claude Code, Cursor, and Copilot to support debugging, migrations, test generation, and everyday development in a safe, measurable way.

You'll be part of Developer Platforms and report to the Engineering Manager of the Developer AI team.

As a Software Engineer on the Developer AI team, you'll help build GenAI-augmented developer experiences and platform capabilities used across The New York Times. You'll work with more senior engineers on the team to deliver well-scoped projects that improve how engineers build, test, and deploy software.

You'll also help define how engineers across Product Engineering design and operate their own agents and agentic workflows. That means helping turn one-off experiments into opinionated, reusable patterns - deliverying and running custom agents safely on our internal platform.

Your work will help teams:

• Ship faster and more safely by using GenAI-augmented workflows instead of one-off scripts and manual toil.


• Pay down technical debt through structured migrations and platform modernization.


• Turn internal practices into reusable tools and agents.

You'll collaborate with partner teams, contribute to the reliability and security of our services, and grow your skills in cloud-native engineering, internal platforms, and practical GenAI.

We operate on shorter planning horizons than many product teams, typically in six-week increments. This lets us respond quickly to an evolving GenAI and agentic ecosystem, incorporating new capabilities and usage patterns into the platform while maintaining clear priorities and structure.

This role includes limited on-call responsibilities; the schedule will be set when you join.

Responsibilities:

• You'll deliver GenAI-powered developer tooling—such as prompts, IDE integrations, skills, and telemetry. You'll help us understand and improve how we deploy and use these tools.


• You'll contribute to the GenAI developer platform: services and integrations built on top of https://www.litellm.ai/ to power both local and background/long-running agents.


• You'll implement and maintain guardrails and observability for agentic workflows, to integrate them with DataDog, DX, and FinOut.


• You'll partner with platform and product teams to define how engineers build their own agentic workflows and custom agents.


• You'll deliver self-service APIs, templates, and documentation that make it easy and safe for engineers to build and operate team-specific agents as part of their everyday development workflows.


• You'll experiment with new GenAI and agentic capabilities, evaluate what works in practice. You'll turn successful experiments into paved paths that can be adopted at scale.


• You'll work with engineers and managers across Product Engineering to understand how they build software today to design solutions that actually fit the way they work.


• Demonstrate support and understanding of our Values and a strong commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

• 1–2 years improving developer experience through workflows, documentation, or internal platforms (for example, building CI/CD improvements, internal tooling, or onboarding guides for other engineers)


• 1–2 years working with Amazon Web Services or Google Cloud Platform


• 1+ years using GenAI tools like GitHub Copilot, Cursor, or Claude Code as part of your daily development


• Experience learning new tools and patterns and asking clear questions when requirements or tradeoffs are ambiguous


• High level of empathy towards coworkers and existing solutions; you're curious about how other engineers work and motivated to make their experience better


• Comfort working in a fast-evolving GenAI and agentic landscape, where new capabilities, usage data, and experiments, inform our priorities

Preferred Qualifications:

• 3+ years working with AWS in depth, including designing and operating production services


• Production experience with Go (Golang), including debugging and helping users or partner teams troubleshoot issues


• Experience deploying and troubleshooting workloads on Kubernetes (EKS) and related observability tooling


• Experience in prompt engineering or building AI-powered internal tools that integrate directly into developer workflows


• Experience contributing to internal platforms or shared libraries that are used by multiple teams


• Experience helping define opinionated patterns, guardrails, or internal standards for how other teams adopt new tools or workflows, especially in fast-changing domains like GenAI