MongoDB

MongoDB

Posted via Greenhouse

Software Engineer 3

Posted Aug 6, 2026

Role at a glance

Salary
Not Disclosed
Location
Sydney Australia - New South Wales - Sydney
Work arrangement
Hybrid
Employment
Full-time
Experience
4+ years building backend, infrastructure systems, CI and build tooling

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Role Summary

AI-generated

The Software Engineer 3 will build systems, tooling, and deployment workflows that deliver Voyage embedding and reranking models beyond first-party MongoDB Atlas, including through cloud marketplaces, third-party inference providers, and self-managed deployments. Working within the Search and AI Platform organization and alongside Voyage’s model-serving teams, the role focuses on consistent, reliable, observable model delivery across customer environments.

What You'll Do

  • Port and tune the model server for Voyage embedding and reranking models across environments.
  • Productionize Voyage models by owning packaging, configuration, and deployment workflows for AWS, Azure, GCP, and other environments.
  • Design correctness, correlation, and performance validation for third-party deployments.
  • Build structured logging, metrics, diagnostics, and health checks using tools such as Prometheus and OpenTelemetry.
  • Debug issues spanning model servers, containers, deployment configuration, and partner cloud environments.
  • Partner with model-serving teams, GTM, SAs, TSEs, and strategic customers on external deployments.

Generated from the employer's posting. Verify important details before applying.

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Qualifications

4+ years building backend, infrastructure systems, CI and build tooling; strong software engineering skills in Python or Go; experience with AWS, Azure, or GCP, containers, and Kubernetes; debugging across code, runtime, model servers, configuration, and external dependencies; familiarity with ML model serving and inference runtimes.

Required

  • 4+ years building backend, infrastructure systems, CI and build tooling
  • Python or Go
  • AWS, Azure, or GCP
  • Containers and Kubernetes
  • Debugging across code, runtime, model servers, configuration, and external dependencies
  • ML model serving and inference runtimes

Preferred

  • Productionizing or deploying ML model servers or inference runtimes, such as vLLM, Triton, or TGI
  • Observability stacks such as Prometheus, Grafana, or OpenTelemetry
  • Shipping software through cloud marketplaces or partner / self-managed channels
  • Contributions to open-source infrastructure for ML serving or deployment

Original job description

Content provided by the employer

We’re looking for a Software Engineer 3 to help bring Voyage’s embedding models - used for semantic search, retrieval, and AI-native experiences; to the platforms and environments where customers already run their workloads, beyond first-party MongoDB Atlas.

You’ll join the broader Search and AI Platform organization and collaborate closely with the engineers building Voyage’s first-party inference. Together, we’re extending that platform across cloud marketplaces, third-party inference providers, and self-managed deployments so customers get the same Voyage models, behaving consistently, wherever they choose to run them.

As a Software Engineer 3, you'll focus on building the systems, tooling, and deployment workflows that power third-party model delivery. You'll own key components of how Voyage models are packaged, validated, and deployed, work across teams to ensure tight integration with the core inference platform, and contribute to delivery surfaces designed for reliability, observability, and ease of use.

We are looking to speak to candidates who are based in Sydney for our hybrid working model.

What you'll do

  • Port and tune the model server that runs Voyage embedding and reranking models: improving inference performance, consistency, and runtime behavior across environments
  • Productionize new Voyage models for delivery beyond first-party Atlas, owning the packaging, configuration, and deployment workflows that get them running on AWS, Azure, GCP and more
  • Design correctness, correlation, and performance validation that proves third-party deployments match first-party behavior
  • Build operability into every surface: structured logging, metrics, diagnostics, and health checks with tools like Prometheus and OpenTelemetry
  • Debug problems that span model servers, containers, deployment configuration, and partner cloud environments
  • Work alongside Voyage's model-serving teams, and partner with GTM, SAs, TSEs, and strategic customers on the hardest external deployments

Who you are

  • 4+ years building backend, infrastructure systems, CI and build tooling
  • Strong software engineering skills in languages such as Python or Go, with an emphasis on performance and reliability
  • Experience with cloud environments (AWS, Azure, or GCP), containers, and Kubernetes
  • Comfortable debugging across the stack - code, runtime, model servers, configuration, and external dependencies
  • Familiar with concepts in ML model serving and inference runtimes, even if not directly deploying models
  • You communicate clearly and do well in ambitious, cross-team work
  • Motivated to get Voyage's AI models running reliably wherever customers want them

Nice to have

  • Experience productionizing or deploying ML model servers or inference runtimes (e.g., vLLM, Triton, TGI)
  • Experience with observability stacks like Prometheus, Grafana, or OpenTelemetry
  • Experience shipping software through cloud marketplaces or partner / self-managed channels
  • Contributions to open-source infrastructure for ML serving or deployment

Why join us

  • Own how Voyage's AI models reach customers everywhere outside first-party Atlas — a fast-growing, high-visibility part of the platform
  • Work on genuinely varied engineering: model servers inference, CI deployments, observability, and large-scale cloud integration
  • Collaborate with the ML and platform teams behind Voyage to bring new models to market
  • Join a team that values ownership, pragmatism, technical judgment, and clarity in ambiguous spaces

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the data platform for the AI era, enabling builders to create, transform, and disrupt industries with software. MongoDB’s unified data platform, the most widely available, globally distributed data platform on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud data platform and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and over 67,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB is an equal opportunities employer.

Req ID - 2273505626

MongoDB

About the company

MongoDB

Large Enterprise

MongoDB is a leading provider of modern, general-purpose databases designed for scalability, performance, and flexibility. Founded in 2007, the company offers an innovative, open-source database platform that allows developers to store and manage data in JSON-like formats, enabling easier and faster application development. With a strong focus on data accessibility and cloud integration, MongoDB serves a diverse range of industries, empowering businesses to harness the power of data and build intelligent applications. As a significant player in the tech landscape, MongoDB supports developers and organizations with robust resources and a vibrant community.