Senior Software Engineer - Data and Platform Tools

Bloomberg Connects is a rapidly growing, free platform that helps museums, galleries, and cultural spaces make their institutions, stories and dynamic content more engaging to audiences around the world. Launched in 2019, Connects features multimedia guides with unique content exclusive to each of our over 1,500 cultural institution partners across 33 countries.

As part of Bloomberg's culture of giving back, Connects is a joint effort between Bloomberg and Bloomberg Philanthropies in support of their work to ensure better, longer lives for the greatest number of people by focusing on five key areas: the arts, education, the environment, government innovation, and public health.

We believe that technology opens doors, and we created Connects as a part of our mission to make art and culture accessible to all—in-person, at-home, and anywhere.

We are a team of designers, researchers, marketers, editors, engineers, and leaders working together to enhance our partner's capacity to reach audiences around the world and improve their visitor experience. Built through empathy and research, qualitative and quantitative data, and experimentation and iteration, our products seek to delight and empower.

The Data and Platform Tools team builds and runs the services behind the platform's analytics, search, speech, computer vision, generative AI, and agentic systems. We are looking for a senior engineer to own the infrastructure those services are built on.

What's in it for you?

Own systems end to end: Design, build and operate the services behind Connects' analytics, search, speech, computer vision, and AI features, from architecture through to what runs in production.

Work on AI systems in production: Build and run the infrastructure behind our LLM-based and agentic features, from deployment through evaluation.

Work the way we're building toward: Use AI-assisted and agentic engineering practices in your own daily work, and help build the internal platform and tooling other disciplines rely on to do the same.

Shape how we build: Establish the infrastructure, deployment and delivery patterns our services are built on.

Shape global cultural engagement: Directly impact how millions access and experience art and culture through a rapidly expanding platform.

Contribute to a philanthropic mission: Align your work with a meaningful initiative supporting arts and cultural accessibility.

We'll trust you to:

·Design, build and operate the distributed services that power Connects' analytics, search, speech, computer vision, generative AI, and agentic systems

·Build and maintain the infrastructure that runs our AI features in production

·Contribute directly to our agentic core platform and tooling — used across engineering and, increasingly, every discipline on the product team

·Own the deployment, release and delivery pipelines our services depend on, and raise the standard of how we ship

·Take architectural decisions that carry real weight, and distribute that knowledge across the team

·Partner with engineering teams across Connects — backend/api, mobile and web teams — on the interfaces and infrastructure our systems share

·Participate in a cross-functional agile team spanning design and engineering

You'll need to have:

·5+ years of professional experience designing, developing and releasing high-quality software in Python, C++, C# and/or TypeScript/JavaScript

·A Degree in Computer Science, Engineering, Mathematics or equivalent work experience

We’d love to see:

·Google Cloud Platform — BigQuery, Cloud Run, Cloud Composer, Artifact Registry

·Infrastructure as code, particularly Terraform

·Designing and owning CI/CD pipelines, including Jenkins

·Designing, building and operating distributed systems and services in production

·Owning services across their full lifecycle — architecture, deployment, operation and evolution — rather than handing them off

·Proficiency in Python

·Working with cloud platforms and cloud-native services

·Containerized workloads and orchestration

·Real, current use of AI-assisted and agentic engineering tools in your own work — this is how the team operates, not an occasional aid

·Setting technical direction and working independently

·Building or operating LLM and agent systems in production, including evaluation frameworks

·Experience working in a compiled language such as Go, Rust, C++, etc.

·Search infrastructure and indexing pipelines

·Vector embeddings/databases and Retrieval Augmented Generation

·Speech (TTS/STT) or computer vision systems in production