About the role

Thatch is rewiring how health benefits work. We build software that gives employees real control over how they use their benefits.

We’re looking for an Infrastructure Engineer to own the reliability, security, and performance of the platform that powers Thatch. Every product team depends on the infrastructure you design and operate.

Our platform runs in a HIPAA-compliant environment and handles sensitive healthcare data. Reliability and security are foundational. The systems you build must be secure, observable, and resilient under real-world load.

We organize engineering around product teams that serve members, employers, and partners. The Infrastructure team builds and operates the platform that enables them to ship reliably.

What you will do

• Own infrastructure health, performance, and reliability across the stack.
• Make architectural decisions and improve how we build and operate.
• Design and evolve infrastructure using Terraform.
• Improve CI/CD, deployments, and developer workflows so teams ship faster.
• Strengthen security across access controls, vulnerability management, and dependencies.
• Identify and eliminate reliability risks before they impact customers.

What we are looking for

• Experience operating production infrastructure, platform, DevOps, or SRE systems.
• A track record of owning critical systems end-to-end.
• Strong experience with PostgreSQL or comparable relational databases in production.
• Experience managing infrastructure as code using Terraform.
• Sound judgment across reliability, performance, and security tradeoffs.
• A bias toward automation and improving developer productivity.

We hire engineers across multiple levels and care most about the scope you’ve owned, the impact you’ve had, and how you make decisions.

Tools and tech stack

• Ruby on Rails
• PostgreSQL
• Terraform
• Modern cloud infrastructure and CI/CD tooling

You don’t need experience with every tool above. You do need to be able to operate systems responsibly in a regulated environment.

Experience that stands out

• Experience operating in HIPAA or SOC 2 environments.
• Deep PostgreSQL performance tuning or replication management.
• Building internal tooling that improves developer productivity.
• Improving observability, incident response, or overall security posture.

What to expect

We aim to move quickly, and most candidates complete the process within 2–3 weeks. The interview process typically includes:

• An initial conversation with a recruiter.
• A collaborative pair programming session.
• A systems or infrastructure design discussion.
• A conversation with members of the engineering team.
• A final conversation with engineering and company leadership. 

About this role

As a Staff Machine Learning Platform Engineer, you will help design, improve, and operate a scalable ML platform to accelerate model training, deployment, and governance. You are the technical bridge between data science and production engineering.  You’ll be joining a small but deeply critical team that scales Faire’s ability to support tens of thousands of local businesses in a constantly narrowing retail landscape.

What You Will Do

• Design and operate ML infrastructure, including workspaces, clusters, jobs, and workflows
• Productionize ML workloads using Spark, Delta Lake, MLflow, and Databricks Workflows
• Teach data scientists how to utilize our ML platform to advance development from notebook to production for our most critical models
• Implement Unity Catalog for data governance, lineage, access control, and secure multi-tenant usage
• Build CI/CD pipelines for ML using Terraform and Git-based workflows (e.g., GitHub Actions)
• Optimize performance, reliability, and cost across training and inference workloads
• Configure Identity and Access Management (IAM) and Role Based Authentication Controls (RBAC) for sensitive data sets
• Establish observability for data quality, model performance, and platform health
• Build and maintain ML Platform technical documentation

What it takes

• 8+ years of experience building production ML or data platforms
• A degree (preferably graduate level) in Computer Science, Engineering, Statistics, or a related technical field
• Strong hands-on expertise with Databricks, Spark, Delta Lake, and MLflow.
• Proficiency in Python, SQL, and distributed systems concepts
• Experience with cloud platforms and infrastructure-as-code
• Solid understanding of MLOps best practices: CI/CD, monitoring, reproducibility, and security
• Experience supporting multiple ML teams in a shared platform environment
• Are an active owner of orphaned problems and are willing to assimilate whatever knowledge you’re missing to get the job done

Tech Stack

Faire uses a modern cloud based tech stack.  For this role, you’ll want to be proficient with the following:

Salary Range

Canada: the pay range for this role is $216,000 to $297,000 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.

This job posting is for an existing vacancy.

Engineering at Brex

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you’ll do

As the Engineering Manager for Cloud Infrastructure, you will lead a highly competent team of senior engineers responsible for the foundational AWS ecosystem that powers Brex. Your primary near-term mission will be driving our high-priority Business Continuity and Disaster Recovery (BCDR) initiative to completion, a company-level priority that involves multi-region failover and infrastructure-wide resilience. You will balance people leadership with deep technical involvement, earning the respect of a senior team while improving operational hygiene and cross-functional coordination across the entire engineering organization.

Where you’ll work

This role will be based in our Seattle office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week: Monday, Wednesday, and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Lead and Grow: Manage and support a senior team of 6 ICs, fostering a culture of high ownership, autonomy, and technical excellence.
• Drive BCDR Strategy: Oversee the execution of the multi-year BCDR initiative, ensuring multi-region infrastructure readiness and automated failover capabilities.
• Technical Stewardship: Maintain and scale Brex’s core cloud infrastructure, including Kubernetes (EKS), RDS/Aurora/Postgres, networking (VPC), and AWS service integrations.
• Cross-Functional Collaboration: Partner with product and engineering teams across Brex to drive adoption of new infrastructure capabilities and ensure successful migrations.
• Operational Excellence: Improve team hygiene by establishing and improving best practices for work tracking (Linear), documentation, and incident response.
• Resource Management: Effectively allocate resources to balance critical project delivery with long-term infrastructure stability.

Requirements

• Leadership Experience: 3+ years of experience directly managing software or infrastructure engineering teams.
• Technical Depth: Deep hands-on experience with cloud infrastructure foundations, specifically AWS, Kubernetes, and Postgres.
• Architectural Insight: Proven ability to design and implement complex infrastructure projects such as multi-region deployments or disaster recovery frameworks.
• Collaborative Mindset: Strong communication skills with the ability to influence technical decisions across multiple autonomous teams.
• Analytical Problem Solving: Ability to dive deep into technical issues while maintaining a high-level strategic view of organizational goals.
• Engineering Background: 5+ years of experience in software or systems engineering.

Bonus points

• Experience with Infrastructure as Code tools, specifically Terraform.
• Background in managing cloud infrastructure cost optimization programs.
• Experience with our tech stack components: Go, Kotlin, Python, or Elixir.
• Passion for leveraging AI and LLM-assisted workflows to increase engineering velocity.

Compensation

The expected salary range for this role is $240,000 - $300,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Engineering at Brex

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you’ll do

As a Security Operations Engineer at Brex, you will focus on preventing, detecting and responding to security threats across Brex's corporate and cloud environments. You will use existing systems and develop tools to improve our security capabilities. Our team is responsible for functions across corporate security, detection & response and infrastructure security domains; and we perform systems engineering and automation to support those functions. 

Security Operations is part of our wider Trust & IT organization which means you will have the opportunity to work closely with Application Security, Corporate Engineering, GRC and IT and to improve security configurations, drive positive employee behaviors and generally work to prevent events from becoming incidents. You will also help build and maintain our team’s open source project Substation and have the opportunity to contribute to the Brex Tech Blog. You’ll be part of a team that actively contributes to the wider security community and has a commitment to mentorship and engineering excellence.

We’re looking for individuals with a strong background and interest in detecting, responding to, and resolving security incidents and security challenges. You should be comfortable dealing with lots of moving pieces, changing priorities, and new technologies, while having a keen eye for detail. Most importantly, you should be enthusiastic about working with a variety of backgrounds, roles, and people across Brex. Building a world-class financial service requires world-class security.

Where you’ll work

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Work on a highly cross-functional team to prevent, detect and respond to security threats across Brex's corporate and cloud environments
• Perform security incident response, investigation, remediation, and documentation, participate in periodic threat hunting and security exercises
• Leading, scoping and building features, participate in designing, and maintaining tools and systems which support the team’s domains – corporate security, detection & response and infrastructure security 
• Collaborating and partnering with engineering and operations teams to drive remediation of security issues, while balancing prioritization of those security issues within SLA and teams’ respective backlogs
• Caring about secure system design, valuing building things correctly, an understanding of a MVP approach and an empathetic mindset when working with others

Requirements

• Bachelor’s degree in Computer Science, Engineering or related field OR equivalent training / fellowship OR 5+ years work experienceExperience working in a corporate security, detection & response or infrastructure security role with responsibilities for security alert triage and security incident response 
• Familiarity with CI/CD systems and DevOps workflows (e.g. Buildkite, Flux, Git, Terraform) in cloud environments (e.g. AWS, Azure, GCP)
• Experience with deploying and maintaining some of the security services and tools owned by the team (e.g. - SIEM, data pipelines, SOAR, domain monitoring, endpoint tooling, email protection tooling, cloud security tools)
• While not primarily a development role, the team develops and maintains tools written in Go and Python, so experience with coding is required
• You thrive in a collaborative environment filled with a diverse group of people with different expertise and backgrounds. We currently have around 30 nationalities represented with more than ½ the company working in a country different from the one they grew up in.

Bonus points

• Proficiency with Go and other programming languages 
• Experience with securing distributed systems in AWS, cloud and Kubernetes environments
• Contributions to the wider technical community (open source, public research, mentorship, community organizing, blogging, presentations, etc)

Compensation

The expected salary range for this role is $192,000 - $240,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Engineering

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you’ll do

Brex’s Governance, Risk, and Compliance function is at an exciting and pivotal point in our maturity journey and we’re seeking a team member who can seamlessly bridge compliance expertise with technical execution. As a Senior GRC Engineer, you will drive critical GRC processes that mitigate risk, keep us compliant, and build trust with our customers and partners. You'll evolve the technical foundation of our Trust program by automating security controls, building integrations between security tools and GRC platforms, and creating scalable processes that enable Brex to maintain compliance efficiently as we expand into new markets. You'll work at the intersection of security, engineering, and compliance — translating regulatory requirements into technical solutions and building automation that eliminates manual toil.

You'll leverage your deep understanding of SOC 2, PCI DSS, ISO 27001, AI governance frameworks, and others to both design controls for emerging compliance requirements and mature existing programs through automation and continuous monitoring. You’ll support Trust Assurance, Third Party Risk Management, and other Security Risk Management initiatives. Working with our Engineering, Infrastructure, and Product teams, you'll translate compliance frameworks into technical controls and build automated systems that help us achieve world-class security as Brex expands.

Your contributions will directly accelerate Brex's maturity. You'll design workflows using Tines, build integrations between security and GRC systems, and create dashboards for security metrics. You'll implement controls across the technology stack, support multiple audits (SOC 2, PCI DSS, SOX/ITGC, FINRA, ISO), and contribute to AI governance framework implementation (ISO 42001, NIST AI RMF, EU AI Act).

You'll have autonomy to build innovative solutions, collaborating cross-functionally to implement controls that enable growth while communicating technical concepts effectively across the organization.

Where you’ll work

This role will be based in our Vancouver office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Manage and scale IT infrastructure, services and tooling
• Work with a diverse group of  IT partners to optimize our provided services
• Implement new services in support of Information Technologies vision
• Scale our services by implementing configuration as code via Terraform providers or APIs
• Operationalize and upskill IT and its partners by producing documentation and leading training sessions
• Evangelize best practices both internally and externally facing

Requirements

• 5+ years of experience in GRC, IT Governance, or Security Engineering with a strong track record of automating manual compliance workflows.
• Deep experience with security frameworks such as SOC 2, PCI DSS, ISO 27001, and NIST CSF, specifically within cloud-native environments.
• Technical proficiency in Python (or similar scripting languages) and experience building integrations using APIs to connect security tools with GRC systems. You can read code, design integrations, and understand technical implementations.
• Builder mindset with the ability to design and implement automated control testing, continuous monitoring, and data-driven security metrics. You see manual processes and immediately think about how to automate them.
• Exceptional cross-functional collaboration and communication skills. You can translate complex compliance requirements into technical specifications that engineering teams can actually implement and influence stakeholders across technical and non-technical domains.
• Strong systems thinking. You have the ability to design scalable GRC architectures that grow with the company, rather than just solving for the immediate audit.
• Bias for action. You’re a self-starter who ships solutions quickly and iterates based on feedback. 

Bonus points

• Previous experience in Fintech or banking environments navigating complex regulatory landscapes.
• Hands-on experience with Tines or other SOAR platforms to automate security operations.
• Familiarity with AI/ML governance frameworks (NIST AI RMF, ISO 42001) or securing agentic systems.
• Deep knowledge of Cloud Security (AWS/GCP), infrastructure-as-code (Terraform), or DevSecOps practices.
• Relevant industry certifications such as CISSP, CISA, or CCSP.
• Experience building metrics dashboards for security visualization and reporting.
• Active contributions to the GRC or Security community through open-source projects or public research.

Compensation

The expected salary range for this role is $153,600 - $192,000 CAD. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Engineering

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you’ll do

Brex’s Governance, Risk, and Compliance function is at an exciting and pivotal point in our maturity journey and we’re seeking a team member who can seamlessly bridge compliance expertise with technical execution. As a Senior GRC Engineer, you will drive critical GRC processes that mitigate risk, keep us compliant, and build trust with our customers and partners. You'll evolve the technical foundation of our Trust program by automating security controls, building integrations between security tools and GRC platforms, and creating scalable processes that enable Brex to maintain compliance efficiently as we expand into new markets. You'll work at the intersection of security, engineering, and compliance — translating regulatory requirements into technical solutions and building automation that eliminates manual toil.

You'll leverage your deep understanding of SOC 2, PCI DSS, ISO 27001, AI governance frameworks, and others to both design controls for emerging compliance requirements and mature existing programs through automation and continuous monitoring. You’ll support Trust Assurance, Third Party Risk Management, and other Security Risk Management initiatives. Working with our Engineering, Infrastructure, and Product teams, you'll translate compliance frameworks into technical controls and build automated systems that help us achieve world-class security as Brex expands.

Your contributions will directly accelerate Brex's maturity. You'll design workflows using Tines, build integrations between security and GRC systems, and create dashboards for security metrics. You'll implement controls across the technology stack, support multiple audits (SOC 2, PCI DSS, SOX/ITGC, FINRA, ISO), and contribute to AI governance framework implementation (ISO 42001, NIST AI RMF, EU AI Act).

You'll have autonomy to build innovative solutions, collaborating cross-functionally to implement controls that enable growth while communicating technical concepts effectively across the organization.

Where you’ll work

This role will be based in our Seattle office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Manage and scale IT infrastructure, services and tooling
• Work with a diverse group of  IT partners to optimize our provided services
• Implement new services in support of Information Technologies vision
• Scale our services by implementing configuration as code via Terraform providers or APIs
• Operationalize and upskill IT and its partners by producing documentation and leading training sessions
• Evangelize best practices both internally and externally facing

Requirements

• 5+ years of experience in GRC, IT Governance, or Security Engineering with a strong track record of automating manual compliance workflows.
• Deep experience with security frameworks such as SOC 2, PCI DSS, ISO 27001, and NIST CSF, specifically within cloud-native environments.
• Technical proficiency in Python (or similar scripting languages) and experience building integrations using APIs to connect security tools with GRC systems. You can read code, design integrations, and understand technical implementations.
• Builder mindset with the ability to design and implement automated control testing, continuous monitoring, and data-driven security metrics. You see manual processes and immediately think about how to automate them.
• Exceptional cross-functional collaboration and communication skills. You can translate complex compliance requirements into technical specifications that engineering teams can actually implement and influence stakeholders across technical and non-technical domains.
• Strong systems thinking. You have the ability to design scalable GRC architectures that grow with the company, rather than just solving for the immediate audit.
• Bias for action. You’re a self-starter who ships solutions quickly and iterates based on feedback. 

Bonus points

• Previous experience in Fintech or banking environments navigating complex regulatory landscapes.
• Hands-on experience with Tines or other SOAR platforms to automate security operations.
• Familiarity with AI/ML governance frameworks (NIST AI RMF, ISO 42001) or securing agentic systems.
• Deep knowledge of Cloud Security (AWS/GCP), infrastructure-as-code (Terraform), or DevSecOps practices.
• Relevant industry certifications such as CISSP, CISA, or CCSP.
• Experience building metrics dashboards for security visualization and reporting.
• Active contributions to the GRC or Security community through open-source projects or public research.

Compensation

The expected salary range for this role is $153,600 - $192,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Engineering

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you’ll do

Brex’s Governance, Risk, and Compliance function is at an exciting and pivotal point in our maturity journey and we’re seeking a team member who can seamlessly bridge compliance expertise with technical execution. As a Senior GRC Engineer, you will drive critical GRC processes that mitigate risk, keep us compliant, and build trust with our customers and partners. You'll evolve the technical foundation of our Trust program by automating security controls, building integrations between security tools and GRC platforms, and creating scalable processes that enable Brex to maintain compliance efficiently as we expand into new markets. You'll work at the intersection of security, engineering, and compliance — translating regulatory requirements into technical solutions and building automation that eliminates manual toil.

You'll leverage your deep understanding of SOC 2, PCI DSS, ISO 27001, AI governance frameworks, and others to both design controls for emerging compliance requirements and mature existing programs through automation and continuous monitoring. You’ll support Trust Assurance, Third Party Risk Management, and other Security Risk Management initiatives. Working with our Engineering, Infrastructure, and Product teams, you'll translate compliance frameworks into technical controls and build automated systems that help us achieve world-class security as Brex expands.

Your contributions will directly accelerate Brex's maturity. You'll design workflows using Tines, build integrations between security and GRC systems, and create dashboards for security metrics. You'll implement controls across the technology stack, support multiple audits (SOC 2, PCI DSS, SOX/ITGC, FINRA, ISO), and contribute to AI governance framework implementation (ISO 42001, NIST AI RMF, EU AI Act).

You'll have autonomy to build innovative solutions, collaborating cross-functionally to implement controls that enable growth while communicating technical concepts effectively across the organization.

Where you’ll work

This role will be based in our New York office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Manage and scale IT infrastructure, services and tooling
• Work with a diverse group of  IT partners to optimize our provided services
• Implement new services in support of Information Technologies vision
• Scale our services by implementing configuration as code via Terraform providers or APIs
• Operationalize and upskill IT and its partners by producing documentation and leading training sessions
• Evangelize best practices both internally and externally facing

Requirements

• 5+ years of experience in GRC, IT Governance, or Security Engineering with a strong track record of automating manual compliance workflows.
• Deep experience with security frameworks such as SOC 2, PCI DSS, ISO 27001, and NIST CSF, specifically within cloud-native environments.
• Technical proficiency in Python (or similar scripting languages) and experience building integrations using APIs to connect security tools with GRC systems. You can read code, design integrations, and understand technical implementations.
• Builder mindset with the ability to design and implement automated control testing, continuous monitoring, and data-driven security metrics. You see manual processes and immediately think about how to automate them.
• Exceptional cross-functional collaboration and communication skills. You can translate complex compliance requirements into technical specifications that engineering teams can actually implement and influence stakeholders across technical and non-technical domains.
• Strong systems thinking. You have the ability to design scalable GRC architectures that grow with the company, rather than just solving for the immediate audit.
• Bias for action. You’re a self-starter who ships solutions quickly and iterates based on feedback. 

Bonus points

• Previous experience in Fintech or banking environments navigating complex regulatory landscapes.
• Hands-on experience with Tines or other SOAR platforms to automate security operations.
• Familiarity with AI/ML governance frameworks (NIST AI RMF, ISO 42001) or securing agentic systems.
• Deep knowledge of Cloud Security (AWS/GCP), infrastructure-as-code (Terraform), or DevSecOps practices.
• Relevant industry certifications such as CISSP, CISA, or CCSP.
• Experience building metrics dashboards for security visualization and reporting.
• Active contributions to the GRC or Security community through open-source projects or public research.

Compensation

The expected salary range for this role is $153,600 - $192,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Engineering

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you’ll do

Brex’s Governance, Risk, and Compliance function is at an exciting and pivotal point in our maturity journey and we’re seeking a team member who can seamlessly bridge compliance expertise with technical execution. As a Senior GRC Engineer, you will drive critical GRC processes that mitigate risk, keep us compliant, and build trust with our customers and partners. You'll evolve the technical foundation of our Trust program by automating security controls, building integrations between security tools and GRC platforms, and creating scalable processes that enable Brex to maintain compliance efficiently as we expand into new markets. You'll work at the intersection of security, engineering, and compliance — translating regulatory requirements into technical solutions and building automation that eliminates manual toil.

You'll leverage your deep understanding of SOC 2, PCI DSS, ISO 27001, AI governance frameworks, and others to both design controls for emerging compliance requirements and mature existing programs through automation and continuous monitoring. You’ll support Trust Assurance, Third Party Risk Management, and other Security Risk Management initiatives. Working with our Engineering, Infrastructure, and Product teams, you'll translate compliance frameworks into technical controls and build automated systems that help us achieve world-class security as Brex expands.

Your contributions will directly accelerate Brex's maturity. You'll design workflows using Tines, build integrations between security and GRC systems, and create dashboards for security metrics. You'll implement controls across the technology stack, support multiple audits (SOC 2, PCI DSS, SOX/ITGC, FINRA, ISO), and contribute to AI governance framework implementation (ISO 42001, NIST AI RMF, EU AI Act).

You'll have autonomy to build innovative solutions, collaborating cross-functionally to implement controls that enable growth while communicating technical concepts effectively across the organization.

Where you’ll work

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Manage and scale IT infrastructure, services and tooling
• Work with a diverse group of  IT partners to optimize our provided services
• Implement new services in support of Information Technologies vision
• Scale our services by implementing configuration as code via Terraform providers or APIs
• Operationalize and upskill IT and its partners by producing documentation and leading training sessions
• Evangelize best practices both internally and externally facing

Requirements

• 5+ years of experience in GRC, IT Governance, or Security Engineering with a strong track record of automating manual compliance workflows.
• Deep experience with security frameworks such as SOC 2, PCI DSS, ISO 27001, and NIST CSF, specifically within cloud-native environments.
• Technical proficiency in Python (or similar scripting languages) and experience building integrations using APIs to connect security tools with GRC systems. You can read code, design integrations, and understand technical implementations.
• Builder mindset with the ability to design and implement automated control testing, continuous monitoring, and data-driven security metrics. You see manual processes and immediately think about how to automate them.
• Exceptional cross-functional collaboration and communication skills. You can translate complex compliance requirements into technical specifications that engineering teams can actually implement and influence stakeholders across technical and non-technical domains.
• Strong systems thinking. You have the ability to design scalable GRC architectures that grow with the company, rather than just solving for the immediate audit.
• Bias for action. You’re a self-starter who ships solutions quickly and iterates based on feedback. 

Bonus points

• Previous experience in Fintech or banking environments navigating complex regulatory landscapes.
• Hands-on experience with Tines or other SOAR platforms to automate security operations.
• Familiarity with AI/ML governance frameworks (NIST AI RMF, ISO 42001) or securing agentic systems.
• Deep knowledge of Cloud Security (AWS/GCP), infrastructure-as-code (Terraform), or DevSecOps practices.
• Relevant industry certifications such as CISSP, CISA, or CCSP.
• Experience building metrics dashboards for security visualization and reporting.
• Active contributions to the GRC or Security community through open-source projects or public research.

Compensation

The expected salary range for this role is $153,600 - $192,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

About the Role

We are seeking a GRC Automation Lead to join our GRC organization and build the technical foundation for how we scale our risk and compliance programs. In this role, you will lead the team that designs and implements automated workflows, data pipelines, and integrations that transform manual compliance processes into scalable engineering systems. 

This is a greenfield opportunity to establish the team, architecture, and integrations that will define how we approach governance, risk, and compliance at Anthropic. The core challenge is a data problem: compliance information lives across dozens of systems—cloud infrastructure, identity providers, HR platforms, ticketing tools, code repositories—and your job is to design systems that bring it together, normalize it, and make it actionable. Success in this role comes from understanding how systems connect and how data flows between them, not from writing code yourself.

At Anthropic, you'll also have a unique advantage: the ability to design AI-powered workflows where Claude acts as an extension of your team, handling tasks that would traditionally require additional headcount or manual effort. You'll need ingenuity to identify where agentic AI can accelerate evidence collection, interpret unstructured data, triage compliance gaps, and augment human judgment in risk assessments. Working closely with Security, IT, and Engineering teams, you'll translate compliance and regulatory requirements into solutions that support audit programs including SOC 2, ISO, HIPAA, and FedRAMP, building systems that combine traditional automation with AI capabilities to achieve scale that wouldn't otherwise be possible.

Responsibilities: 

• Lead the team that establishes foundational GRC processes and architecture. Design and build automated workflows for risk management and compliance, creating scalable systems that enable continuous monitoring as Anthropic grows.
• Build data pipelines that aggregate risk, control, and asset information from across our technology stack. This means solving hard data integration problems: mapping disparate schemas, handling inconsistent data quality, and creating unified views of compliance posture through dashboards and reporting tools.
• Inform GRC platform strategy and implementation: in partnership with other programs, evaluate, select, and deploy tooling that meets our compliance requirements.
• Translate written policies and compliance requirements into policy-as-code—working with Engineering and Security teams to express requirements as enforceable rules, automated checks, and continuous validation rather than static documents.
• Establish feedback loops between policy and implementation: surface where technical controls diverge from written requirements, identify where policies need to evolve based on infrastructure realities, and ensure that compliance requirements are expressed in terms engineers can act on.
• Design and deploy agentic AI workflows that extend team capacity, using Claude to serve as a virtual GRC analyst to automate evidence analysis, monitor control effectiveness, draft audit responses, interpret policy documents, and handle other tasks that require reasoning over unstructured information.
• Design and maintain integrations connecting GRC tooling with cloud infrastructure, identity management systems, HRIS platforms, ticketing systems, version control, and CI/CD pipelines—working with engineers to implement integrations that enable automated evidence collection and continuous compliance validation.
• Build and lead an AI-forward GRC engineering function as we scale: hiring team members, establishing practices, and defining the technical roadmap for governance and compliance automation at Anthropic.

You may be a good fit if you:

• Have 12+ years of total experience and 3-4+ years of experience managing technical individual contributors or systems-focused teams, with a proven track record of building or scaling small teams (2-5 people) in security, compliance, automation, or operations functions.
• Are a systems thinker first. You understand how complex environments work: how data flows between systems, where integration points exist, what breaks when systems don't talk to each other. Your strength is designing the right architecture and environment for security monitoring, not necessarily implementing it yourself.
• Have 5+ years of experience designing automated workflows, data pipelines, or system integrations, whether through traditional development, low-code platforms, GRC tools, or process automation. We care about your ability to solve integration problems more than your programming language proficiency.
• Have a relentless focus on data integration: you understand how to pull data from multiple sources, normalize it, join it meaningfully, and surface insights. You're comfortable reasoning about messy, inconsistent data and designing systems that handle edge cases gracefully.
• Understand APIs and integration patterns: REST APIs, webhooks, authentication flows, polling vs. push architectures, and can evaluate systems based on how well they expose data and support automation.
• Can work independently with minimal guidance, taking ownership of complex problems from design through implementation while managing ambiguity inherent in early-stage programs.
• Have strong analytical and problem-solving skills with attention to detail necessary for compliance work, balanced with pragmatism about risk-based prioritization in fast-paced environments.

Strong candidates may have:

• Experience designing or implementing AI-powered automation, agentic workflows, or LLM-based tooling in operational contexts.
• Experience with GRC platforms such as ServiceNow GRC, Vanta, Drata, OneTrust, RSA Archer, or similar tools including configuration, customization, and integration capabilities
• Familiarity with scripting languages (Python or similar) for automation tasks, API interactions, and data transformation.
• Prior experience in high-growth startup environments demonstrating ability to build scalable processes and adapt quickly to changing requirements and priorities
• Familiarity with Infrastructure as Code tools (Terraform, CloudFormation, Ansible) and DevSecOps practices including CI/CD pipeline integration and policy-as-code implementations.
• Familiarity with cloud platforms (AWS, GCP, Azure) and an understanding of how compliance-relevant data can be extracted from their APIs and logging systems.

Deadline to apply: None, applications will be received on a rolling basis.

About the Role:

We're looking for a Senior Staff Security Engineer to lead Gusto's edge and network security strategy, owning the design and operation of our Cloudflare WAF, DDoS protection, Zero Trust, and broader perimeter controls. The ideal candidate brings deep, hands-on Cloudflare expertise and a proven track record of hardening edge and network architectures at scale, including tuning WAF rulesets, defending through live DDoS events, and shipping Zero Trust rollouts engineers actually adopt. You think in terms of layered defense, measurable risk reduction, and automation over manual toil. In this role, you'll serve as a force multiplier across the security org, partnering with infrastructure and product teams to make high-impact architectural decisions that compound over time.

About the Team:

The Gusto's Enterprise Security Engineering team, a small but high-leverage group responsible for cloud security posture, edge and network defense, container security, secrets management, and endpoint protection across the company. The team runs a modern stack including Cloudflare, Wiz, CrowdStrike, Panther, and Tines, scaling impact through automation, IaC, and AI-augmented tooling. The work carries real stakes, protecting the payroll, benefits, and HR systems that hundreds of thousands of small businesses and their employees rely on every day. The team is engineering-first, with most of the roadmap living in code and a strong emphasis on partnering with infrastructure and product teams rather than gatekeeping them.

Here’s what you’ll do day-to-day:

• Design and operate Gusto's edge security stack including Cloudflare WAF, DDoS protection, Bot Management, WARP, Gateway, and Access, tuning rules against real traffic and shaping how engineers and operations teams reach internal systems securely.
• Own the network security perimeter across AWS and the edge: VPC design, Network Firewall, Shield, CloudFront, NACLs, and egress filtering, all codified in Terraform and Crossplane, observable, and consistently enforced.
• Develop policy-as-code patterns for WAF rules, network policies, and edge configuration so changes ship through pull requests with review, testing, and clean rollback paths.
• Build detections and alerting on edge and network telemetry including Cloudflare logs, VPC Flow Logs, and CloudTrail flowing into Panther, and lead incident response for perimeter and network events.
• Contribute broadly across the security engineering surface including cloud posture, container security, IAM, vulnerability management, and on-call, bringing a strong generalist instinct to wherever the work is most critical.
• Operate as an AI-native engineer, using Claude Code, MCP-driven tooling, and agentic workflows as a daily force multiplier across investigation, automation, and detection engineering.
• Prototype and ship agents, custom MCP servers, and LLM-assisted automations that compress security work from days to minutes and raise the bar for what one engineer can own.

Here’s what we're looking for:

• 10+ years of hands-on security engineering experience, with significant time owning edge, network, or perimeter security at scale.
• Deep, production-grade expertise with Cloudflare's security stack including WAF, DDoS, Bot Management, WARP, Gateway, and Access, covering rule tuning, incident response, and Zero Trust rollouts.
• Strong network architecture skills across edge and cloud: TLS/mTLS, segmentation, egress controls, DDoS resilience, and AWS networking including VPC, Network Firewall, Shield, CloudFront, and NACLs.
• Fluency with policy-as-code, Terraform, and CI/CD-first delivery of security controls; Crossplane or similar a plus.
• Solid generalist foundation across cloud security, IAM, container security, and detection engineering, with hands-on incident response experience on edge and network telemetry in a modern SIEM.
• AI-native working style with daily use of Claude Code or equivalent agentic tooling, and a track record of building AI-assisted workflows including custom MCP servers, agents, and LLM automations that compound team output.
• Excellent written and verbal communication; you can take a complex perimeter decision and explain the tradeoffs to a staff engineer, a PM, and a VP without changing the substance.
• Relevant certifications a plus including AWS Certified Advanced Networking Specialty, AWS Certified Security Specialty, Cloudflare Certified Security Associate/Professional, CKS, or equivalent.

The opportunity
Unity is looking for a Senior Machine Learning Infrastructure Engineer to join our Vector Ads team, where we build the real-time systems that power Unity's global advertising platform. This is a high-scale, low-latency environment — processing billions of requests daily to deliver fast, relevant ads to players around the world.

You'll build and operate the infrastructure that brings ML models from training into production, ensuring our ranking, bidding, and targeting systems run reliably at scale. This is a great opportunity for an engineer who's excited to work at the intersection of ML systems and distributed infrastructure, collaborate across teams, and have direct impact on how machine learning shapes the player and advertiser experience.

What you'll be doing

• Design, build, and maintain the infrastructure that serves ML models in real-time across Unity's ads ecosystem
• Build and operate scalable model serving pipelines — owning latency, throughput, and reliability in a high-QPS production environment
• Partner with ML engineers to productionize models, manage model deployments, and improve iteration speed
• Improve observability, performance, and cost-efficiency of ML serving infrastructure
• Contribute to architectural decisions around feature serving, model versioning, and inference optimization

What we're looking for

• Experience building and operating ML infrastructure or model serving systems in production
• Proficiency in Golang or Python, with strong systems engineering fundamentals
• Hands-on experience with Kubernetes and container orchestration at scale
• Familiarity with ML serving frameworks such as Ray Serve, Triton, TorchServe, or similar
• Understanding of distributed systems, API design, and system reliability
• Strong collaboration and communication skills in a remote-first environment

You might also have

• Experience with feature stores, feature pipelines, or online/offline feature serving
• Background in ad tech, real-time bidding, or programmatic advertising systems
• Familiarity with infrastructure-as-code such as Terraform
• Experience with observability tooling — Prometheus, Grafana, OpenTelemetry
• Background with real-time data pipelines, caching layers, or low-latency serving systems

Additional information

• Relocation support is not available for this position

Benefits
At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.

Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status.

While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program

Life at Unity
Unity [NYSE: U] is the world’s leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D — closing the gap between ideas and reality. For more information, please visit www.unity.com.

Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.

Headhunters and recruitment agencies may not submit resumes/CVs through this Web site or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity.

Your privacy is important to us. Please take a moment to review our Prospect Privacy Policy and Applicant Privacy Policy. Should you have any concerns about your privacy, please contact us at DPO@unity.com.

#SEN #LI-ED1

We are looking for a Staff Forward Deployed Engineer who is passionate about solving complex cloud infrastructure challenges in the fast-growing AI/ML space. This is a high-impact position designed to be the "technical tip of the spear" for our most strategic AI-Native (ANE) customers.

As an FDE, you will sit at the intersection of Product Engineering and Customer Implementation. You will be embedded directly with our most strategic customers to drive transformational AI adoption. You will collaborate closely with customer teams to ship advanced AI applications that solve real world business problems.

You will build the tools, migration scripts, and AI starter kits that don't just solve one customer's problem, but scale the entire DigitalOcean AI Cloud ecosystem. Your mission is to accelerate "time-to-inference" in production at scale and serve as a critical feedback loop, ensuring our product roadmap is informed by the world's most demanding AI workloads.

What you’ll do:

• Embedded Customer Engineering: Partner deeply with strategic ANEs to manage complex migrations, build production-ready PoCs, and execute hands-on application builds on our GPU infrastructure.
• Build Scalable Assets & Tooling: Operationalize field learning by building migration planners, reusable systems, benchmarking frameworks, model optimization agents, and deployment automation scripts (e.g., Terraform/Pulumi) that standardize how AI workloads are deployed and tuned across DigitalOcean.
• Develop AI "Starter Kits": Create pre-built GenAI agents, solution templates, and notebooks (e.g., LangGraph, CrewAI) tailored to popular and advanced business needs.
• Drive the Product Roadmap: Act as the frontline technical voice for CPTO, surfacing architectural gaps and edge cases to inform core product development. Transition field-built tools into native product features.
• New Tech Validation: Lead the early testing and integration of emerging AI frameworks to ensure a first-class developer experience on DigitalOcean.
• Partner & GTM Enablement: Co-develop delivery frameworks with Strategic and Technical partners to enable repeatable, high-quality deployments at scale.
• Market Leadership: Produce field-tested demo kits and deployment guides that support new product releases with practical, validated assets.

Key Metrics

• Customer Adoption: Number of high-impact production workloads landed; reduction in average "time-to-production"; and Pilot-to-Production conversion rates.
• Asset & Tooling Delivery: Number of reusable tools (agents, scripts, playbooks) delivered per quarter and their subsequent adoption rate by the crossfunctional teams and customers.
• Field Enablement & Scale: Measured by the successful handoff and execution of FDE-defined deployment patterns to technical partners and the internal adoption rate of FDE playbooks across all customer-facing technical teams.
• Product Influence: Number of roadmap features or architectural changes directly attributed to FDE feedback and validated customer hypotheses.

What You’ll Add to DigitalOcean:

• AI/ML Architecture & Domain Expertise: Significant experience in the AI/ML lifecycle, specifically hosting large language or multimodal models using inference engines like vLLM, SGLang, or Modular. You have a deep understanding of common LLM architectures and optimization techniques (e.g., continuous batching, quantization).
• Distributed Systems & Infrastructure Mastery: Act as the subject matter expert on modern GPU families (NVIDIA/AMD) and their software stacks (CUDA, ROCm, TensorRT, OpenAI Triton). Expert proficiency in Kubernetes (K8s) and the design of distributed systems, including microservices, messaging systems, databases, and Infrastructure as Code. You can seamlessly integrate AI workloads with core cloud services (Networking, VPC, Storage, Compute).
• High-Performance Inference & Hardware Optimization: Hands-on experience with distributed inference serving frameworks (e.g., llm-d, NVIDIA Dynamo, or Ray Serve). You understand GPU-level optimization and have experience with interconnect technologies like NVlink, XGMI, or RoCE to maximize hardware efficiency.
• Software Engineering Foundation: Strong production coding skills in Python or Go with the ability to build high-quality tools, automation, and internal assets.
• Data-Driven Performance Insight: Proven ability to benchmark AI infrastructure and perform GPU utilization tuning to optimize customer ROI and workload performance.
• Consultative Execution: Proven ability to establish instant technical credibility with CTOs and Lead Architects while managing high-stakes technical migrations.

Preferred

• Experience with emerging AI orchestration frameworks like LangGraph, CrewAI, or LlamaIndex.
• A background in technical consulting or "Forward Deployed" roles at high-growth AI or infrastructure companies.
• Experience building and scaling "Center of Excellence" models or partner delivery frameworks.
• Active contributor to open-source AI projects or technical communities.

Compensation Range: 

• $195,000 - $239,000

*This is a remote role

JR: 2026-7748

#LI-Remote

About this role

As a Staff Machine Learning Platform Engineer, you will help design, improve, and operate a scalable ML platform to accelerate model training, deployment, and governance. You are the technical bridge between data science and production engineering.  You’ll be joining a small but deeply critical team that scales Faire’s ability to support tens of thousands of local businesses in a constantly narrowing retail landscape.

What You Will Do

• Design and operate ML infrastructure, including workspaces, clusters, jobs, and workflows
• Productionize ML workloads using Spark, Delta Lake, MLflow, and Databricks Workflows
• Teach data scientists how to utilize our ML platform to advance development from notebook to production for our most critical models
• Implement Unity Catalog for data governance, lineage, access control, and secure multi-tenant usage
• Build CI/CD pipelines for ML using Terraform and Git-based workflows (e.g., GitHub Actions)
• Optimize performance, reliability, and cost across training and inference workloads
• Configure Identity and Access Management (IAM) and Role Based Authentication Controls (RBAC) for sensitive data sets
• Establish observability for data quality, model performance, and platform health
• Build and maintain ML Platform technical documentation

What it takes

• 8+ years of experience building production ML or data platforms
• A degree (preferably graduate level) in Computer Science, Engineering, Statistics, or a related technical field
• Strong hands-on expertise with Databricks, Spark, Delta Lake, and MLflow.
• Proficiency in Python, SQL, and distributed systems concepts
• Experience with cloud platforms and infrastructure-as-code
• Solid understanding of MLOps best practices: CI/CD, monitoring, reproducibility, and security
• Experience supporting multiple ML teams in a shared platform environment
• Are an active owner of orphaned problems and are willing to assimilate whatever knowledge you’re missing to get the job done

Tech Stack

Faire uses a modern cloud based tech stack.  For this role, you’ll want to be proficient with the following:

Salary Range

San Francisco: the pay range for this role is $246,500 to $339,000 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Scale's Physical AI business unit is dedicated to solving the data bottleneck across Robotics, Autonomous Vehicles, and Computer Vision. This position will be a key contributor in conducting applied research in Physical AI and developing ML pipelines for processing, training, and fine-tuning on data collected by Scale, with a specific focus on optimizing algorithms and pipelines to run efficiently on GPUs in the cloud. In this role, you will have the opportunity to advance research, shape Scale’s offerings, and expand the frontier of data and model evaluation for Physical AI.

The Role 

As an ML Systems Engineer on the Physical AI team, you will design and build platforms for scalable, reliable, and efficient serving of foundation models specifically tailored for physical agents. Our platform powers cutting-edge research and production systems, supporting both internal research discovery and external customer use cases for autonomous vehicles and robotics.

The ideal candidate combines strong ML fundamentals with deep expertise in backend system design. You’ll work in a highly collaborative environment, bridging the gap between Physical AI research and production engineering to accelerate innovation across the company.

You Will: 

• Build & Scale: Maintain fault-tolerant, high-performance systems for serving robotics-related models and foundation models at scale, ensuring low latency for real-time applications.
• Platform Development: Build an internal platform to empower model capability discovery, enabling faster iteration cycles for research teams working on robotics.
• Collaborate: Work closely with Robotics researchers and Computer Vision engineers to integrate and optimize models for production and research environments.
• Design Excellence: Conduct architecture and design reviews to uphold best practices in system scalability, reliability, and security.
• Observability: Develop monitoring and observability solutions to ensure system health and real-time performance tracking of model inference.
• Lead: Own projects end-to-end, from requirements gathering to implementation, in a fast-paced, cross-functional environment.

Ideally, You’d Have: 

• Experience: 4+ years of experience building large-scale, high-performance backend systems, with deep experience in machine learning infrastructure.
• Algorithm Optimization: Deep experience optimizing computer vision and other machine learning algorithms for cloud environments, including GPU-level algorithm optimizations (e.g., CUDA, kernel tuning).
• Programming: Strong skills in one or more systems-level languages (e.g., Python, Go, Rust, C++).
• Systems Fundamentals: Deep understanding of serving and routing fundamentals (e.g., rate limiting, load balancing, compute budgets, concurrency) for data-intensive applications.
• Infrastructure: Experience with containers (Docker), orchestration (Kubernetes), and cloud providers (AWS/GCP).
• IaC: Familiarity with infrastructure as code (e.g., Terraform).
• Mindset: Proven ability to solve complex problems and work independently in fast-moving environments.

Nice to Haves: 

• Exposure to Vision-Language-Action (VLA) models.
• Knowledge of high-performance video processing (e.g., FFmpeg, NVDEC/NVENC) or 3D data handling (point clouds).
• Familiarity with robotics middleware (e.g., ROS/ROS2) or AV data formats.

Scale AI is seeking a highly skilled and motivated Software Engineer, ARC (Architecture, Reliability, & Compute) to join our dynamic Public Sector Engineering team. As a part of this team, you will define how the company ships software, establishing the patterns for deploying into complex government and high-security environments, rather than just running Terraform scripts. You will build and maintain internal CLIs/tools that standardize testing, deployment, environment management and are tools that engineering relies on to prevent downstream breakages. You will execute on automated deployment efforts to pay down tech debt, creating fully functional staging/testing environments, and defining the company's standard for safe deployments.

You will:

• Design and implement secure scalable backend systems for Public Sector customers, leveraging Scale's modern and cloud-native AI infrastructure.
• Own services or systems and define their long-term health goals, while also improving the health of surrounding components.
• Re-architect the stack to run in compliant or restrictive environments. This requires designing swappable components (auth, storage, logging) to meet government/security mandates without breaking the product.
• Collaborate with cross-functional teams to define and execute the vision for backend solutions, ensuring they meet the unique needs of government agencies operating in secure environments.
• Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.
• Contribute to the platform roadmap and product strategy for Scale AI's Public Sector business, playing a key role in shaping the future direction of our offerings.

Must have:

• At least an active secret clearance and the ability & willingness to up level to TS/SCI with CI Poly. This is a requirement and candidates will not be considered who do not hold at least a secret clearance

Ideally you'd have:

• Full Stack Development: Proficiency in both front-end and back-end development, including experience with modern web development frameworks, programming languages, and databases. Experience with developing & delivering software to air-gapped & isolated environments is a plus.
• Cloud-Native Technologies: Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is desired. Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. 
• Security Focused: Experience with Federal Compliance frameworks, and requirements(e.g, Cloud SRG, FedRAMP, STIG Benchmarks, etc). Experience developing software & technical solutions that meet strict security & regulatory compliance requirements.
• Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles.
• Collaboration and Communication: Excellent interpersonal and communication skills to effectively collaborate with cross-functional teams, stakeholders, and customers. Ability to clearly articulate technical concepts to non-technical audiences and foster a collaborative work environment.
• Adaptability and Learning Agility: Willingness to embrace new technologies, learn new skills, and adapt to evolving project requirements. Ability to quickly grasp and apply new concepts and stay up-to-date with emerging trends in software engineering.
• Must be able to support work 3-4 days a week from the DC, SF, NYC, or STL office.

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition.

At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI.

At the foundation of these products is the Platform Engineering team. As a Staff Software Engineer, you will define and drive both the architectural roadmap and implementation of core platforms and software systems. You will be responsible for providing high-level vision and driving adoption across the engineering org for orchestration, data abstraction, data pipelines, identity & access management, and underlying cloud infrastructure.  You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies.

Impact and Responsibilities:

• Architectural Vision: You will drive the design and implementation of foundational systems, acting as a bridge between high-level business goals and technical goals.
• Cross-Functional Leadership: You will collaborate with cross-functional teams to define and drive adoption of the next generation of features for our AI data infrastructure.
• Technical Ownership: You are responsible for proactively identifying and driving opportunities for organizational growth, driving improvements in programming practices, and upgrading the tools that define our development lifecycle.
• Technical Mentorship: You will serve as a subject matter expert, presenting technical information to stakeholders and providing the guidance to elevate the engineering culture across the company.

Ideally you’d have:

• 8+ years of full-time engineering experience, post-graduation with specialities in back-end systems.
• Extensive experience in software development and a deep understanding of distributed systems and public cloud platforms (AWS preferred).
• Demonstrated a track record of independent ownership and leadership across successful multi-team engineering projects
• Possess excellent communication and collaboration skills, and the ability to translate complex technical concepts to non-technical stakeholders.
• Experience working fluently with standard containerization & deployment technologies like Kubernetes, Terraform, Docker, etc.
• Experience with orchestration platforms, such as Temporal and AWS Step Functions.
• Experience with NoSQL document databases (MongoDB) and structured databases (Postgres).
• Strong knowledge of software engineering best practices and CI/CD tooling (CircleCI, ArgoCD).

Nice to haves:

• Experience with data warehouses (Snowflake, Firebolt) and data pipeline/ETL tools (Dagster, dbt).
• Experience scaling products at hyper-growth startups.
• Excitement to work with AI technologies.

As a Software Engineer on the Machine Learning Infrastructure team, you will build the "Operating System" for our large-scale GPU clusters. You will architect a high-performance training platform that handles the immense complexity of multi-thousand GPU workloads, ensuring every cycle is used efficiently. Your work directly determines the velocity at which our researchers can train and iterate on the world’s most advanced models.

The ideal candidate is a systems expert who thrives on solving the orchestration, networking, and reliability challenges that emerge at massive scale. You will partner closely with researchers to build a seamless, resilient environment that transforms raw compute into breakthrough AI.

You will:

• Architect and scale a multi-tenant orchestration layer that abstracts away the complexity of GPU clusters, ensuring high utilization and seamless job recovery.
• Design and implement scheduling primitives to optimize the lifecycle of training jobs.
• Develop deep observability and automated health-checking into the training stack to proactively identify and isolate hardware failures
• Evaluate and integrate emerging technologies in the CNCF and AI ecosystem (e.g. Ray, Kueue), making data-driven build vs. buy decisions that balance velocity with long-term maintainability.
• Work closely with Finance and Procurement teams to drive our capacity planning process.
• Participate in our team’s on call process to ensure the availability of our services.
• Own projects end-to-end, from requirements, scoping, design, to implementation, in a highly collaborative and cross-functional environment.

Ideally you'd have:

• 5+ years of experience in backend or infrastructure engineering, with at least 2 years focused on orchestrating ML workloads at scale (100+ GPU nodes).
• Strong programming skills in one or more languages (e.g. Python, Go, Rust, C++)
• Experience with complex compute management systems that cover queueing, quotas, preemption, and gang scheduling.
• Experience with distributed training infrastructure, such as EFA, Infiniband, and topology-aware scheduling.
• Experience with distributed storage systems (e.g. Lustre, S3) as they relate to training throughput
• Expert-level knowledge of Kubernetes internals (Custom Resources, Operators, Admission Controllers) and how they interact with device plugins for specialized hardware.
• Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform).
• Proven ability to solve complex problems and work independently in fast-moving environments.

Nice to haves:

• Experience with distributed training techniques such as DeepSpeed, FSDP, etc.
• Experience with the NVIDIA software and hardware stack (CUDA, NCCL)
• Experience with PyTorch
• Familiarity with post-training algorithms such as GRPO, and with Reinforcement Learning

About Scale AI

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities.

Role Overview

As a Forward Deployed AI Engineering Manager on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments.

This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. You'll work directly with customer engineering teams to integrate AI into their critical workflows.

Key Responsibilities

Customer Integration & Deployment

• Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements
• Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)
• Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows
• Deploy and configure AI models and agents within customer security and compliance boundaries

AI Agent Development

• Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation
• Architect multi-agent systems that orchestrate between different models, tools, and data sources
• Implement evaluation frameworks to measure agent performance and iterate toward business objectives
• Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement

Prompt Engineering & Optimization

• Create sophisticated prompt engineering strategies optimized for customer-specific domains and data
• Build and maintain prompt libraries, templates, and best practices for customer use cases
• Conduct systematic prompt experimentation and A/B testing to improve model outputs
• Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate

Leadership & Collaboration

• Serve as the Engineering Manager and technical point of contact for strategic enterprise accounts
• Lead a team that is collaborating with customer data scientists, ML engineers, and software developers to ensure smooth integration
• Work closely with Scale's product and engineering teams to translate customer needs into product improvements
• Document technical architectures, integration patterns, and best practices

Problem Solving & Innovation

• Debug complex technical issues across the entire stack, from data pipelines to model outputs
• Rapidly prototype solutions to unblock customers and prove out new use cases
• Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems
• Identify opportunities for productization based on common customer patterns

Required Qualifications

• 5+ years of software engineering experience with 2+ yrs of  Management experience with strong fundamentals in data structures, algorithms, and system design
• Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API)
• Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure
• Strong problem-solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutions
• Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences

Preferred Qualifications

Agent Development Wiz

• Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures
• Experience building and deploying AI agents or autonomous systems in production
• Knowledge of vector databases and semantic search systems
• Contributions to open-source AI/ML projects

Infrastructure Guru

• Experience with containerization (Docker, Kubernetes) and CI/CD pipelines
• Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools
• Previous work in a devops, platform, or infra role
• Familiarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA)

Customer Product Whisperer

• Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role
• Domain expertise in verticals like finance, healthcare, government, or manufacturing
• Experience with technical enablement or teaching programs

Sample Projects

The following are some examples of the types of projects we’ve worked on with customers. All of these projects leverage customer data, integrate directly into customers’ existing systems, and are deployed on their infrastructure.

Deep Research for Due Diligence

For a global professional services firm, we developed a sophisticated deep research agent to assist in due diligence. This agent employs a multi-agent architecture for robust fact-checking, integrates several internal MCP tools, and processes complex, unstructured data sources. This solution reliably saves employees hundreds of hours weekly.

Churn Prediction

Working with a TelCo organization, we built a model utilizing customer data to predict churn likelihood. The system then curates personalized offers based on this prediction. This model was integrated into a "next best action" copilot, enabling call center agents to proactively surface relevant offers to customers, leading to a significant reduction in churn.

Data Extraction Voice Agent

We partnered with a healthcare organization to create a lifelike voice agent and avatar designed to gather unstructured health information from patients. Engineered for low latency, the agent adeptly manages conversational flow, adheres to safety guardrails, and efficiently handles data extraction. This automation saves the organization's nurses hundreds of hours each week.

• Conduct in-depth code reviews to identify and remediate security vulnerabilities.
• Evaluate and enhance the security of our product offerings, through RFC and service review.
• Implement and maintain CI/CD pipelines with a strong focus on security.
• Perform Static Application Security Testing (SAST) and Dynamic Application Security Testing (DAST) to identify vulnerabilities in production code.
• Utilize terraform orchestration to ensure secure and efficient infrastructure management.
• Guide engineering teams to build robust long-term solutions that consider security and privacy.
• Clearly explain the mechanics and significance of security vulnerabilities, including their exploitability and potential impact.
• Influence the security strategy and direction of the team, advocating for best practices and continuous improvement.

• Proven experience as a Security Engineer with a focus on product security.
• Proficiency in NodeJS, TypeScript, Python, and/or Kubernetes.
• Strong understanding of modern Javascript application design.
• Production experience with Kubernetes backed services
• Hands-on experience with SAST and DAST tools and methodologies.
• Familiarity with terraform orchestration for infrastructure management.
• You can structure complex problems and diagnose root causes independently, providing actionable insights without requiring manager input.
• Excellent communication skills, with the ability to clearly present technical concepts and their implications to both technical and non-technical stakeholders.
• Demonstrated ability to influence security strategies and drive improvements within a team.
• Relevant security certifications (e.g., CISSP, CEH, OSCP) are a plus.

About Scale AI

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities.

Role Overview

As a Forward Deployed AI Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments.

This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows.

Key Responsibilities

Customer Integration & Deployment

• Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements
• Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)
• Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows
• Deploy and configure AI models and agents within customer security and compliance boundaries

AI Agent Development

• Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation
• Architect multi-agent systems that orchestrate between different models, tools, and data sources
• Implement evaluation frameworks to measure agent performance and iterate toward business objectives
• Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement

Prompt Engineering & Optimization

• Create sophisticated prompt engineering strategies optimized for customer-specific domains and data
• Build and maintain prompt libraries, templates, and best practices for customer use cases
• Conduct systematic prompt experimentation and A/B testing to improve model outputs
• Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate

Technical Leadership & Collaboration

• Serve as the primary technical point of contact for strategic enterprise accounts
• Collaborate with customer data scientists, ML engineers, and software developers to ensure smooth integration
• Provide technical training and knowledge transfer to customer teams
• Work closely with Scale's product and engineering teams to translate customer needs into product improvements
• Document technical architectures, integration patterns, and best practices

Problem Solving & Innovation

• Debug complex technical issues across the entire stack, from data pipelines to model outputs
• Rapidly prototype solutions to unblock customers and prove out new use cases
• Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems
• Identify opportunities for productization based on common customer patterns

Required Qualifications

• 4+ years of software engineering experience with strong fundamentals in data structures, algorithms, and system design
• Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API)
• Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure
• Strong problem-solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutions
• Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences

Preferred Qualifications

Agent Development Wiz

• Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures
• Experience building and deploying AI agents or autonomous systems in production
• Knowledge of vector databases and semantic search systems
• Contributions to open-source AI/ML projects

Infrastructure Guru

• Experience with containerization (Docker, Kubernetes) and CI/CD pipelines
• Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools
• Previous work in a devops, platform, or infra role
• Familiarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA)

Customer Product Whisperer

• Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role
• Domain expertise in verticals like finance, healthcare, government, or manufacturing
• Experience with technical enablement or teaching programs

Sample Projects

The following are some examples of the types of projects we’ve worked on with customers. All of these projects leverage customer data, integrate directly into customers’ existing systems, and are deployed on their infrastructure.

Deep Research for Due Diligence

For a global professional services firm, we developed a sophisticated deep research agent to assist in due diligence. This agent employs a multi-agent architecture for robust fact-checking, integrates several internal MCP tools, and processes complex, unstructured data sources. This solution reliably saves employees hundreds of hours weekly.

Churn Prediction

Working with a TelCo organization, we built a model utilizing customer data to predict churn likelihood. The system then curates personalized offers based on this prediction. This model was integrated into a "next best action" copilot, enabling call center agents to proactively surface relevant offers to customers, leading to a significant reduction in churn.

Data Extraction Voice Agent

We partnered with a healthcare organization to create a lifelike voice agent and avatar designed to gather unstructured health information from patients. Engineered for low latency, the agent adeptly manages conversational flow, adheres to safety guardrails, and efficiently handles data extraction. This automation saves the organization's nurses hundreds of hours each week.

As a Software Engineer on the ML Infrastructure team, you will design and build platforms for scalable, reliable, and efficient serving of LLMs. Our platform powers cutting-edge research and production systems, supporting both internal and external use cases across various environments.

The ideal candidate combines strong ML fundamentals with deep expertise in backend system design. You’ll work in a highly collaborative environment, bridging research and engineering to deliver seamless experiences to our customers and accelerate innovation across the company.

You will:

• Build and maintain fault-tolerant, high-performance systems for serving LLMs workloads at scale.
• Build an internal platform to empower LLM capability discovery.
• Collaborate with researchers and engineers to integrate and optimize models for production and research use cases.
• Conduct architecture and design reviews to uphold best practices in system design and scalability.
• Develop monitoring and observability solutions to ensure system health and performance.
• Lead projects end-to-end, from requirements gathering to implementation, in a cross-functional environment. 

Ideally you'd have:

• 5+ years of experience building large-scale, high-performance backend systems.
• Strong programming skills in one or more languages (e.g., Python, Go, Rust, C++).
• Experience with LLM serving and routing fundamentals (e.g. rate limiting, token streaming, load balancing, budgets, etc.)
• Experience with LLM capabilities and concepts such as reasoning, tool calling, prompt templates, etc.
• Experience with containers and orchestration tools (e.g., Docker, Kubernetes).
• Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform).
• Proven ability to solve complex problems and work independently in fast-moving environments.

Nice to haves:

• Experience with modern LLM serving frameworks such as vLLM, SGLang, TensorRT-LLM, or text-generation-inference.

We are seeking a highly technical Security Engineer to join our Product Security team. This role is integral to ensuring the security and integrity of our products and services. You will conduct in-depth code reviews, implement security best practices, and influence the overall security strategy. Your expertise in TypeScript, Python, AWS, CI/CD, SAST, DAST, and terraform orchestration will be crucial in identifying and mitigating potential security vulnerabilities. You will also structure complex problems, diagnose root causes independently, and clearly explain the mechanics and significance of security vulnerabilities, including their exploitability and potential impact.

You will:

• Leverage broad product security expertise to build and maintain software tooling that secures every layer of the modern AI/ML software ecosystem.
• Conduct in-depth code reviews to identify and remediate security vulnerabilities.
• Evaluate and enhance the security of our product offerings, through RFC and service review.
• Implement and maintain CI/CD pipelines with a strong focus on security.
• Perform Static Application Security Testing (SAST) and Dynamic Application Security Testing (DAST) to identify vulnerabilities in production code.
• Utilize terraform orchestration to ensure secure and efficient infrastructure management.
• Guide engineering teams to build robust long-term solutions that consider security and privacy. 
• Clearly explain the mechanics and significance of security vulnerabilities, including their exploitability and potential impact.
• Influence the security strategy and direction of the team, advocating for best practices and continuous improvement.

Ideally, you’d have:

• Demonstrated ability to drive multi-month security initiatives independently, from problem definition through execution, without requiring significant direction.
• Proven experience as a Security Engineer with a focus on product security.
• Proficiency in NodeJS, TypeScript, Python, and/or Kubernetes.
• Strong understanding of modern Javascript application design.
• Production experience operating and securing AWS infrastructure at scale.
• Hands-on experience with SAST and DAST tools and methodologies.
• Familiarity with terraform orchestration for infrastructure management.
• You can structure complex problems and diagnose root causes independently, providing actionable insights without requiring manager input.
• Excellent communication skills, with the ability to clearly present technical concepts and their implications to both technical and non-technical stakeholders.
• Demonstrated ability to influence security strategies and drive improvements within a team.
• Relevant security certifications (e.g., CISSP, CEH, OSCP) are a plus.

About the Team

This role will lead either our Gateway or Agent team, depending on your experience and interests.

Both teams sit on the critical path of every ngrok connection and are central to our reliability, performance, and customer trust.

• Gateway Team: Owns the core infrastructure that handles and shapes all traffic flowing through ngrok—routing, security enforcement, rate limiting, and observability. Every request passes through this layer, and its correctness and performance are foundational to everything we do.
• Agent Team: Builds the software that runs on the customer side of every connection. The Agent is what developers install and trust to securely expose their systems to the internet, and it must perform reliably across unpredictable, real-world environments.

What You’ll Actually Do

Lead a team that ships and learns quickly

You’ll manage and coach a team of 5–7 engineers. The goal isn’t just shipping—it’s building a team that can consistently make good decisions, move fast, and improve over time.

Treat management like a systems problem (with humans in the loop)

You’ll design how your team works: planning, execution, retros, feedback loops, and decision-making. You’ll tune the system, not just react to it.

Stay close enough to the code to matter

You won’t be coding every day, but you’ll get into the details when needed—reviewing designs, debugging tricky issues, and helping the team make better technical tradeoffs.

Drive product and technical direction together

This isn’t “just execution.” You’ll help shape what the team builds—balancing product work, technical investments, and experiments that actually teach you something.

Build a team people want to be on

You’ll coach junior and senior engineers, create psychological safety, and raise the bar on both performance and collaboration.

Connect the team to the bigger picture

You’ll make sure your team understands how their work ties to ngrok’s product, customers, and business. Context isn’t optional here. You’ll work closely with senior leadership and functional orgs to shape and meaningfully impact company culture and roadmap.

You Might Be a Great Fit If…

• You’ve spent 5+ years as a software engineer and comfortable in Go, Rust, Java, or C/C++
• You have 4+ years of engineering leadership experience
• You think in systems—whether that’s distributed systems or team dynamics
• You’re comfortable zooming in (code, debugging) and zooming out (strategy, org design)
• You’ve built things from scratch—teams, processes, or products
• You communicate clearly, directly, and without unnecessary fluff

Bonus points if you’ve:

• Contributed to open source, blogs, or conferences
• Worked in developer tools or product-led growth environments
• Built teams in ambiguous, early-stage contexts

Tech Stack

ngrok runs entirely on AWS. Engineers develop by using remote development tools and/or ssh to connect to remote EC2 environments that run a full Kubernetes cluster of the ngrok stack, closely mirroring production. The codebase is primarily Go and TypeScript. We use Postgres for persistence, Kafka for streaming, Protobuf for service boundaries, and Kubernetes, Terraform, Helm, and Buildkite to operate and ship reliably. React is used for user interfaces, and GitHub supports our development workflows and remembers everything.

Location

This is a remote position for candidates outside of the Bay Area and a hybrid role for candidates within commuting distance to San Francisco. Our Bay Area employees commute to the office on Tuesdays and Wednesdays.

Sponsorship

All candidates must be US-based, and legally authorized to work in the United States.

At this time, ngrok is unable to provide visa sponsorship for this position. Applicants must be authorized to work in the United States on a permanent, ongoing basis without the need for current or future sponsorship.

Compensation

Engineering Manager: $225,000 – $275,000

Job level and actual compensation will be evaluated based on factors including, but not limited to, qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of role), internal equity with other team members, market data, and specific work location. We provide an attractive mix of salary and equity.

#LI-Remote

About the Role

Anthropic manages one of the largest and fastest-growing accelerator fleets in the industry — spanning multiple accelerator families and clouds. The Accelerator Capacity Engineering (ACE) team is responsible for making sure every chip in that fleet is accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute.

As an engineer on ACE, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend.

You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment.

What This Team Owns

The team’s work spans three functional areas. Depending on your background and interests, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap:

• Data infrastructure — collecting, normalizing, and serving the fleet-wide data that powers everything else. This means building pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalizing billing and usage data across cloud providers, and maintaining the BigQuery layer that the rest of the org queries against. Correctness, completeness, and latency matter here.

• Fleet observability — making the state of the accelerator fleet legible and actionable in real time. This means building cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and driving systemic improvements to scheduling and fragmentation. The work sits at the intersection of Kubernetes operations and cross-team coordination.

• Compute efficiency — measuring and improving how effectively every major workload uses the hardware it’s running on. This means instrumenting utilization metrics across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and collaborating directly with system-owning teams to close efficiency gaps.

• Internal compute tooling — building the platforms and interfaces that make capacity data usable across the org. This includes capacity planning tools, workload attribution systems, cost dashboards, and self-service APIs. The consumers are research engineers, infrastructure teams, finance, and leadership — each with different needs and different levels of technical depth. The work involves product thinking as much as engineering: figuring out what people actually need, defining schema contracts, and making the data discoverable.

You will be placed on a pod based on your background and interests. We are especially focused on hiring for Data Platform, but strong candidates for any of the three active pods will move forward.

What You’ll Do

• Build and operate data pipelines that ingest accelerator occupancy, utilization, and cost data from multiple cloud providers into BigQuery. Own data completeness, latency SLOs, gap detection, and backfill automation.

• Develop and maintain observability infrastructure — Prometheus recording rules, Grafana dashboards, and alerting systems — that surface actionable signals about fleet health, occupancy, and efficiency.

• Instrument and analyze compute efficiency metrics across training, inference, and eval workloads. Build benchmarking infrastructure, establish per-config baselines, and work with system-owning teams to improve utilization.

• Build internal tooling and platforms that enable capacity planning, workload attribution, and cluster debugging. The consumers are other engineering teams, finance, and leadership — not external users.

• Operate Kubernetes-native systems at scale — deploying data collection agents, managing workload labeling infrastructure, and understanding how taints, reservations, and scheduling affect capacity.

• Normalize and reconcile data across heterogeneous sources — including AWS, GCP, and Azure billing exports, vendor-specific telemetry formats, and internal systems with different schemas and billing arrangements.

• Collaborate across organizational boundaries with research engineering, infrastructure, inference, and finance teams. Gather requirements from technical stakeholders, translate them into useful systems, and communicate trade-offs to non-technical audiences.

You May Be a Good Fit If You Have

• 5+ years of software engineering experience with a strong track record building and operating production systems. You write code every day — this is a hands-on engineering role, not a planning or coordination role.

• Kubernetes fluency at operational depth — you’ve operated production K8s at meaningful scale, not just written manifests. Comfort with scheduling, taints, labels, node management, and debugging cluster-level issues.

• Data pipeline engineering experience — designing, building, and owning the full lifecycle of production data pipelines. Experience with data warehouses (BigQuery preferred), schema management, streaming ingestion, SLOs for latency and completeness, and a strong instinct for correctness.

• Observability tooling experience — Prometheus, PromQL, and Grafana are in the critical path for this team. Experience writing recording rules, understanding metric semantics, and building monitoring systems that engineering teams actually rely on.

• Python and SQL at production quality. Most pipeline code is Python; the presentation layer is BigQuery SQL including table-valued functions and views. Both need to be idiomatic, well-tested, and maintainable.

• Familiarity with at least one major cloud provider (AWS, GCP, or Azure) at the infrastructure level — compute, billing, usage APIs, cost management tooling. Multi-cloud experience is a strong plus.

• High autonomy and strong cross-team communication. You can gather your own requirements, navigate ambiguity, and work across organizational boundaries. Scrappiness and ownership matter more than polish.

Strong Candidates May Also Have

• Multi-cloud data ingestion experience — especially working with AWS and GCP APIs, billing exports, or vendor-specific telemetry formats. Experience normalizing data from external providers with different billing arrangements is directly applicable.

• Accelerator infrastructure familiarity — GPU metrics (DCGM), TPU utilization, Trainium power and utilization metrics, or experience working with ML training/inference systems at the hardware level.

• Performance engineering and benchmarking experience — building benchmark harnesses, establishing baselines, reasoning about compute efficiency (FLOPs utilization, memory bandwidth, interconnect throughput), and working with system teams to diagnose and improve performance.

• Data-as-product thinking — experience building internal data products with self-service access, schema contracts, API serving, documentation, and discoverability. Not just building pipelines, but thinking about how platform data gets consumed.

• Experience with capacity planning, resource management, or cost attribution systems at a hyperscaler or large-scale ML environment. FinOps, chargeback systems, or infrastructure cost modeling.

Familiarity with ClickHouse, Terraform, or Rust. ClickHouse is the team’s current streaming store; Terraform for infrastructure-as-code; Rust for high-performance data collection agents.

Who We Are

EDO is the TV outcomes company. Our measurement platform connects convergent TV airings to the ad-driven consumer behaviors most predictive of future sales, helping advertisers, agencies, networks, streamers, and studios understand what works across linear and streaming TV.

We combine immediate engagement signals with decision science, vertical AI, and investment-grade data to help the advertising industry maximize media impact, optimize creative performance, and value every impression. EDO is headquartered in New York City and Los Angeles with office space in San Francisco. For employees residing full-time in NYC, SF, or LA, we have a hybrid work policy of three days in the office and two remote work days.

The Role

EDO is looking for a Senior Platform Engineer to help accelerate our shift toward a platform model. This is a senior IC role on the Infrastructure team focused on paved paths, reusable infrastructure patterns, and self-service workflows that help software, data, and machine learning engineers ship safely and efficiently.

Our environment is AWS-heavy and data-intensive, with heavy use of EC2, RDS, S3, SageMaker, MWAA/Airflow, Snowflake, dbt, Chef, Terraform, Spacelift, and emerging ECS/container patterns. The right person has strong AWS and infrastructure-as-code fundamentals, prior exposure to platform engineering practices, and the pragmatism to modernize existing systems without assuming everything should be rebuilt from scratch.

We approach infrastructure as an internal product: understanding engineers’ needs, prioritizing high-leverage platform capabilities, and iterating on tools and workflows that make teams faster, safer, and more self-sufficient.

What You Will Do

• Build and evolve EDO's internal platform capabilities: paved paths, reusable infrastructure modules, deployment standards, documentation, and self-service workflows.
• Own and improve Terraform and Spacelift-based infrastructure workflows, including module design, reviews, approvals, drift detection, and guardrails.
• Modernize existing AWS infrastructure, including EC2- and Chef-based systems, while helping teams adopt more standardized and repeatable patterns over time.
• Support production data and ML platform infrastructure, including MWAA/Airflow, Snowflake, dbt, SageMaker, S3, RDS, and related AWS services.
• Partner with software, data, and ML engineers as internal customers, turning recurring infrastructure needs into scalable platform capabilities rather than one-off support work.
• Improve deployment, CI/CD, observability, alerting, and incident response practices so teams can operate production systems with greater confidence.
• Expand pragmatic ECS/container deployment patterns where they create value, without treating Kubernetes as the default answer.
• Participate in a lightweight on-call rotation and use operational learnings to reduce toil, improve reliability, and strengthen the platform.

What We Are Looking For

• 6+ years of experience in platform engineering, infrastructure engineering, SRE, DevOps, cloud infrastructure, or similar roles.
• Experience building, operating, or contributing to an internal developer platform, infrastructure platform, developer productivity team, or similar platform-oriented function.
• Strong production experience with AWS, especially EC2, RDS, S3, IAM, networking, load balancing, and related operational patterns.
• Strong hands-on experience with Terraform or similar infrastructure-as-code tooling, including reusable modules and multi-environment patterns.
• Comfort working in a data-heavy environment and supporting technologies such as Airflow/MWAA, Snowflake, dbt, SageMaker, S3, and RDS.
• Product-minded approach to infrastructure: able to understand engineer pain points, prioritize high-impact platform work, document paved paths, and iterate based on adoption and feedback.
• Strong operational judgment, including debugging production systems, improving observability, and building platform patterns that support reliability, security, and cost efficiency.

Bonus Points

• Hands-on experience with Spacelift or similar IaC orchestration platforms such as Terraform Cloud or Atlantis.
• Experience helping an organization adopt platform engineering practices, including paved paths, golden paths, service templates, and developer-facing documentation.
• Experience with Chef, AWS cost management, security/compliance-driven infrastructure, or production ML/data science infrastructure.

Compensation and Benefits

EDO offers a competitive compensation package. Components of compensation include:

• Mid-stage equity and competitive salary
• Flexible Time Off
• Medical, dental and vision coverage: EDO provides full coverage for individual medical plans and partial coverage for dependent or family plans.
• 401(k) plan, FSA, HSA
• Commuter Benefits
• When in an office, employee meals, snacks, and more

In compliance with New York and California Pay Transparency Law, the salary range for this position is $170,000 to $190,000 plus equity. We note the salary information as a general guideline only, as actual compensation may vary from posting. We will consider various factors to determine the offer for this role, including the scope and responsibilities of the position, relevant work experience, key skills, training, and business considerations.

EDO is an Equal Opportunity Employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status, or any legally protected status. All your information will be kept confidential according to EEO guidelines.

The Team

Platform Engineering is the department within SRE that is responsible for a range of critical infrastructure and operational functions that support the broader engineering organization. Among these are our multi-cloud-provider Kubernetes infrastructure, networking, load balancing (including our public-facing edge and internal service mesh), and observability and alerting systems.

The Fleet Management team provides the core runtime environment that empowers our developers to build and ship products to delight our customers. We manage the end-to-end lifecycle of our Kubernetes fleet, alongside the critical components that ensure cluster reliability and security (e.g., CoreDNS, cert-manager, and Gatekeeper). As our infrastructure scales to support new use cases and products, we are spearheading a migration from Terraform-based Infrastructure as Code (IaC) to an Operator-driven lifecycle management model.

This role can be based out of our Austin, Boston, Los Angeles, New York City, Raleigh, or San Francisco offices, remotely in the United States region, or our European office in Dublin.

Responsibilities

• Contribute to developing and maintaining a scalable and secure runtime environment on top of Kubernetes that supports product needs across MongoDB
• Provide internal support for our Kubernetes ecosystem, partnering with engineering teams to help them solve domain-specific problems
• Participate in a 24/7 on-call rotation to resolve critical issues
• Prioritize blameless post-mortems and dedicate engineering time to systemic fixes, ensuring you aren’t paged for the same issue twice

You may be a good fit if you

• Have 6+ years of experience in software development and operating distributed systems
• Are proficient in Go, Python, or a similar language, with a strong commitment to code quality and testing practices (writing unit, integration, and E2E tests)
• Have deep experience using and extending containerization technologies, preferably Kubernetes
• Have a solid understanding of Linux operating system internals and networking concepts (e.g., filesystems, TCP/IP, DNS, TLS)
• Possess a customer focused mindset, treating internal developers as your primary users
• Have strong operational ownership, including a track record of debugging complex production issues and driving them to resolution
• Prefer automation over manual processes ("allergic to ops work")
• We are a small team of software engineers with a strong bias toward building software solutions to eliminate toil

Strong candidates may also have experience with

• Designing and implementing secure, multi-tenant runtime environments from first principles
• Proficiency with Kubernetes ecosystem tools such as Helm, Kustomize, Gatekeeper, Kyverno, and CRDs/Operators, CRI, CSI
• Expertise in cloud infrastructure platforms, including AWS, GCP, or Azure
• Proficiency in provisioning infrastructure using tools like Terraform, Crossplane, and AWS Controllers for Kubernetes (ACK)
• Advanced Linux systems internals and networking concepts specifically relevant to containers, such as namespaces and cgroups

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 database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform, the most widely available, globally distributed database 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 database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and over 60,000 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, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Req ID: 426182

We are looking for an experienced Senior or Staff Engineer for our SRE, InfraSec team, to guide the security of our cloud-based infrastructure. As a Staff SRE, you will be very hands-on technically while also mentoring a small team of SREs.

The InfraSec team collaborates closely with other engineering teams to ensure that our infrastructure adheres to the highest security standards. They build essential security infrastructure and implement controls that reinforce the platform’s security posture.

This is an SRE team, which means you can expect a highly hands-on approach, tackling the technical challenges of implementing large scale solutions.This team is deeply involved in the technical aspects of security and the nuances of its actual implementation.

This role can sit in our New York City, Austin, Seattle or San Francisco offices on a hybrid basis, or it can be fully remote while working from a location based in either Eastern or Central time zones.

Responsibilities:

Cloud Security Design and Implementation:  

• Help lead the design and deployment of security solutions for cloud platforms (AWS, Azure, GCP), including network and compute security, identity management, and cloud security posture management (CSPM)

Automation and Monitoring:  

• Build automated solutions for real-time security monitoring, logging, and alerting in cloud environments. Leverage native cloud services and third-party tools for runtime security monitoring and anomaly detection

Security Tooling:

• Evaluate, implement, and manage cloud-native security tools and platforms for endpoint security, identity management (IAM), and CSPM 

Qualifications:

Experience:  

• 6+ years of experience in SRE, infrastructure engineering or similar role, with a strong focus on security work, with ideally 2+ years in a senior or staff engineering role

Security Mindset:

• A comprehensive understanding of all facets of cloud environment security, spanning from foundational OS networking layers to cloud provider configurations. Proven experience in leading projects within security-focused areas, such as runtime scanning, security observability, CSPM, and more

Cloud Expertise:  

• Strong experience with at least one cloud platform (AWS, Azure, GCP), including expertise in IAM, VPC networking, security groups, and cloud security tools (e.g., GuardDuty, Security Hub, CloudTrail)

Coding/Automation:  

• Proficiency in at least one programming language (we use Golang but are language agnostic when it comes to hiring ) and experience with infrastructure-as-code tools (Terraform, CloudFormation, Ansible) to automate security configurations and processes

Linux and Networking

• Understanding of the underlying Linux and networking concepts, including low-level fundamentals, and how they work together in complex systems

Communication and Leadership Skills:  

• Strong ability to explain complex security concepts to both technical and non-technical teams. Ability to lead a small technical team and ensure success both meeting the team goals as well as personal growth for all team members

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 database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database 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 database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and nearly 60,000 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, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Req ID: 1263064630

The Team

Platform Engineering is the department within SRE that is responsible for a range of critical infrastructure and operational functions that support the broader engineering organization. Among these are our multi-cloud-provider Kubernetes infrastructure, networking, load balancing (including our public-facing edge and internal service mesh), and observability and alerting systems.

The Fleet Management team provides the core runtime environment that empowers our developers to build and ship products to delight our customers. We manage the end-to-end lifecycle of our Kubernetes fleet, alongside the critical components that ensure cluster reliability and security (e.g., CoreDNS, cert-manager, and Gatekeeper). As our infrastructure scales to support new use cases and products, we are spearheading a migration from Terraform-based Infrastructure as Code (IaC) to an Operator-driven lifecycle management model.

This role can be based out of our Austin, Boston, Los Angeles, New York City, Raleigh, or San Francisco offices, or remotely in the United States region.

Responsibilities

• Manage a team of 6-8 engineers, fostering a positive culture, handling career growth and performance conversations, and proactively removing blockers
• Help develop a clear technical vision and comprehensive roadmap for our runtime environment, balancing long-term strategic infrastructure goals with immediate engineering needs
• Contribute through light hands-on technical work, such as leading architectural design reviews, reviewing PRs, and stepping in to guide the team through complex operational challenges
• Act as the primary liaison for the Fleet Management team, collaborating closely with other engineering leaders to ensure platform alignment and manage stakeholder expectations

You may be a good fit if you:

• Have 10+ years of experience working on software and operating distributed systems, with 2+ years managing engineering teams
• Possess a customer-focused mindset, treating internal developers as your primary users
• Value efficiency in processes and operations, and have a track record of optimizing team workflows
• Prefer automation over manual processes ("allergic to ops work"), fostering a culture of building software solutions to eliminate toil
• Have deep technical familiarity with Kubernetes ecosystems, containerization technologies, and modern IaC tooling (e.g., Terraform, Crossplane, or Operators) so you can effectively guide the team's technical decisions
• Excel at translating complex business and engineering requirements into actionable, phased technical roadmaps
• Have a high level of empathy, responsibility, ownership, and accountability
• Excellent verbal and written technical communication skills

Strong candidates may also have experience with:

• Leading major architectural shifts, such as migrating teams from traditional IaC to Operator-driven lifecycle management
• Managing and scaling infrastructure across multi-cloud environments (AWS, GCP, or Azure)
• Designing secure, multi-tenant runtime environments at scale

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 database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database 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 database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and nearly 60,000 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, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Req ID: 426152

We are hiring an experienced Security Software Engineer (Staff or Senior) for our Infrastructure Security team to design and build scalable security controls and services within MongoDB Atlas multi-cloud infrastructure.

The team sits within the Site Reliability Engineering organization and works with other engineering teams to ensure that our infrastructure adheres to the highest security standards.

This role can be based out of our New York City, Austin, Seattle or San Francisco offices, or work fully remotely on standard East Coast business hours.

Responsibilities:

• Design and build core security primitives and services that protect MongoDB Atlas compute, networking, and identity across AWS, Azure, and GCP
• Build secure-by-default infrastructure using Linux security mechanisms (AppArmor, SELinux, seccomp, cgroups), Kubernetes, and eBPF to enforce runtime policies and gain deep visibility into systems behaviour
• Develop APIs, automation, and tooling that manage security posture at scale (CSPM, vulnerability management, workload identity) and provide monitoring, logging, and alerting pipelines that integrate with our tooling (Grafana, Splunk, Victoria Metrics.)
• Integrate security into our CI/CD and infrastructure-as-code workflows (Terraform) so that security controls are versioned, reviewed, and deployed just like any other code
• Lead complex projects end‑to‑end, from problem discovery and design docs to implementation, rollout, and long‑term ownership
• Collaborate with SRE, platform and product engineering teams to define secure architectures for new infrastructure and services

Qualifications:

You might be a great fit if you match some of the following:

• 5+ years of experience in Software Engineering, Site Reliability Engineering, or similar roles, preferably with relevant security work
• Proficiency with at least one programming language (Java, Golang, Rust, Python, or C/C++) and experience with infrastructure-as-code tools (Terraform) to automate security configurations and processes
• A deep understanding of Linux and networking concepts, including low-level fundamentals, and how they work together in complex systems
• Experience building security-related features or platforms such as runtime monitoring, CSPM, or vulnerability management
• Experience with a cloud provider (AWS, GCP, or Azure) and their security best practices and building blocks
• Hands-on experience with Kubernetes and its security ecosystem (e.g. RBAC, OPA/Gatekeeper, Kyverno, eBPF, Falco, Tetragon)
• A systems mindset: you think about failure modes, performance, observability, and operability alongside security and correctness
• Strong communication skills and the ability to explain complex security concepts and tradeoffs to both technical and non-technical stakeholders

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 database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database 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 database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and nearly 60,000 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, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Req ID: 2263171228

About the DevInfra Team

The DevInfra team is Mixpanel’s platform engineering team. Our mission is to be a force multiplier for Mixpanel engineering as a whole. We achieve this by partnering with our engineering teams to build a world-class software development life cycle together.

About the Role

We are looking for an engineer with a strong track record of solving tooling pain points, automating away toil, and helping teams deliver software faster, more safely, and more reliably. Someone who is energized by supporting their fellow engineers. An engineer who has good taste and leverages AI to great effect without generating slop. Frequent forays into uncharted territory requires our team to be highly adaptable and always ready to learn. We serve as trailblazers for the rest of Mixpanel engineering.

Responsibilities

• We partner with a wide variety of teams to build out their software development lifecycle to be optimized for speed, safety, and reliability. We support teams writing front-end UI code as well as teams maintaining our highly stateful storage systems deep in our stack.

• We are responsible for deploying AI tools like Claude Code to our entire engineering team. We are building agents into our platform to do things like augment on-call response and automatically one-shot bugs that come through a team’s triage queue.

• We support systems that ingest more than 1 Trillion user-generated events every month while balancing low end-to-end query latency. Mixpanel queries typically scan more than 1 Quadrillion events over the span of a month. More details in this blog post.

• Mixpanel runs entirely on Google Cloud Platform and Google Kubernetes Engine. DevInfra is the overall admin for our cloud environment, so we wear many hats. We are responsible for things like Terraform, cost management, networking, and security best practices.

• We are the overall service owner for Kubernetes. Individual teams are responsible for maintaining and monitoring their own clusters and workloads. We are responsible for setting standards for deployment, observability, and developer experience. We facilitate efforts like Kubernetes version upgrades and helping teams adopt new Google Kubernetes Engine features.

• Service ownership of our observability pipelines. We have instrumented over 30 million Prometheus metrics time series and use Open Telemetry to ingest over 4 billion distributed tracing spans per month. An example: How We Migrated from StatsD to Prometheus in One Month.

• We maintain our GitHub Actions based CI/CD pipelines. We maintain a robust GitHub-native delivery process that empowers teams to self-serve their needs while ensuring safety and reliability. See this blog post for an example.

• We maintain our devbox system that provisions cloud development environments for individual developers.

• We procure best in breed SaaS tooling for the rest of engineering. We own our relationship with GitHub, Honeycomb, Chronosphere, Sentry, and more.

• We run the new engineer onboarding process. If you join us, your first meeting will probably be with us!

We're Looking For Someone Who Has

• 3+ years of industry experience.

• Experience with at least one of: Go, Python, or JavaScript/TypeScript.

• Production experience working with Kubernetes.

• Production experience managing infrastructure in a major cloud provider such as Google Cloud Platform, Amazon Web Services, or Azure. Preferably Google Cloud Platform.

• Knowledgeable about coding agents like Claude Code

Bonus Points

• Experience with observability solutions like OpenTelemetry, Prometheus, or Distributed Tracing for application monitoring and performance analysis.

• Experience with service mesh.

• You write excellent docs.

• Proficient with GitHub Actions and the GitHub ecosystem.

• Experience building deployment pipelines. We love GitOps!

• Bazel expertise.

• Experience with Terraform.

• Experience with cloud Identity and Access Management (IAM) systems and knowledgeable about security best practices.

• Experience implementing Internal Developer Platforms like Backstage.

• Working knowledge of site reliability engineering (SRE) principles such as implementing Service Level Objectives (SLOs).

• You ❤️ open source.

About the Role

The Data Governance function is pivotal in ensuring the integrity, trustworthiness, and effective management of Chime’s data assets. Our mission is to establish and operationalize data governance frameworks that not only meet compliance requirements, but actively enable high-confidence decision making across the company.  As a Data Governance Engineer, you will develop and implement policies and tools for data quality, developer enablement, certified datasets, and governance automation - with a sharp focus on building trust signals and scorecards that help data consumers quickly understand and act on the reliability of Chime's data.

This is a hands-on engineering role. You will write production-quality code to build automation for governance and data quality processes using Terraform, Python (or similar languages), and contribute to internal libraries, frameworks, and orchestration workflows that enable scalable governance.

You will partner closely with data engineering, analytics, product engineering, and compliance teams to:

• Support Chime in data compliance and risk reduction initiatives
• Establish data quality as a product discipline
• Build trust signals and scorecards that make data reliability transparent and data context valuable for a variety of use cases
• Implement governance workflows upstream, where data are created
• Ensure data context and metadata are sufficient for downstream use cases, including AI applications

You will be involved in reviews of technical designs and implementation plans to provide guidance on appropriate development from a data governance and compliance perspective, acting as a trusted advisor to teams innovating at Chime. You will also be a strong advocate and leader for Artificial Intelligence tooling and adoption at Chime, bringing curiosity and a practical eye for where AI creates leverage in data governance workflows. This role is 40% strategic influence, 40% development and building, and 20% stakeholder management and support.

The base salary for this role and level of experience will begin at $160,000.00 and go up to $221,000.00. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.

In this role, you can expect to

• Build Data Trust Infrastructure: Design and implement trust scorecards, trust signals, and quality indicators that give data consumers real-time visibility into data reliability - and partner with producers upstream to embed quality checks at the source before issues propagate downstream.
• Drive Data Quality Strategy: Own and evolve Chime's data quality strategy end-to-end. Design and partner with engineering teams to implement data quality frameworks and monitoring systems that proactively identify, surface, and resolve data issues at scale.
• Develop and Implement Data Governance Policies: Create and enforce policies for data classification, quality, and lifecycle management, ensuring data integrity and compliance with SOX and other applicable regulatory standards.
• Enable the Data Catalog: Collaborate on the development, adoption, and enrichment of Chime's data catalog - improving discoverability, context richness (lineage, ownership, definitions, usage guidance), and the overall experience of working with Chime's data.
• Automate Governance Processes: Develop and deploy automation solutions for data governance tasks, such as metadata management, data lineage tracking, access controls, and quality remediation workflows.
• Champion SOX Compliance: Play an active role in Chime's SOX compliance efforts, ensuring that data governance practices, controls, and audit trails meet regulatory requirements and are well-documented.
• Lead AI Adoption for Data Governance: Serve as a leader and advocate for AI tooling within the data governance space - identifying opportunities to apply AI to automate governance workflows, improve data context, enhance trust scoring, and accelerate adoption of governance best practices across engineering teams.
• Collaborate Across Teams: Work closely with data engineers, analysts, and compliance officers to align data governance initiatives with business needs and regulatory requirements.

To thrive in this role, you have

• Experience: 5+ years in data engineering, data governance, or a related field, with hands-on experience in data classification, cataloging, quality assurance, and trust frameworks. Engineering ability to design and implement data governance and quality processes is critical to success.
• Trust & Quality Expertise: Demonstrated experience building data trust signals, quality scorecards, or similar frameworks that make data reliability visible and actionable for both engineers and non-technical stakeholders.
• Programming Experience: Proficiency in Python or a comparable programming language, and experience building scalable data tooling or automation pipelines.
• Curiosity and Relentlessness: You are genuinely curious about data, technology, and the problems that sit at the intersection of the two. You don't let ambiguity stop you - you dig in, ask the right questions, and keep pushing until you've found the right answer or built the right solution. You bring energy and persistence to hard problems and don't need external pressure to drive yourself forward.
• Composure in Complexity: Data governance at a fintech means navigating competing priorities, regulatory constraints, sprawling data ecosystems, and stakeholders with different mental models of "good." You thrive in this environment rather than shrinking from it - you can hold complexity without getting overwhelmed, break it into manageable pieces, and make steady progress without waiting for perfect conditions.
• Exceptional Communication: You are a terrific communicator in both verbal and written form. You can write a crisp one-pager that earns buy-in from a skeptical audience, run a meeting that ends with clarity instead of confusion, and translate deeply technical concepts into plain language that moves people to action. You treat communication as a core part of the job, not an afterthought.
• Product Management Mindset: You think like a product manager as much as an engineer. You ask "who is this for and what problem does it solve?" before writing a line of code. You prioritize ruthlessly, define success before you start building, and care about adoption and outcomes - not just delivery. You treat your internal stakeholders as customers and design solutions with their experience in mind.
• AI Curiosity and Advocacy: Genuine curiosity about AI and its applications in the data governance space, with an appetite for identifying and piloting new tools and workflows that improve the experience of working with Chime's data.
• Technical Proficiency: Strong knowledge of data governance tools and platforms, and experience with cloud data warehouses like Snowflake. Experience with data catalog platforms and driving adoption across engineering organizations is a strong plus.
• Bonus: Compliance Knowledge: Familiarity with SOX, CCPA, and other data privacy and financial regulations, and ability to apply technical skills to governance practices that meet audit and compliance requirements.

#LI-Onsite #LI-GC1

About the role

We are looking for an early-career Security Engineer to join our Product Security team,  someone who has a builder’s mindset, is eager to learn, and is excited to contribute to both planned initiatives and dynamic, real-time security needs with enough guidance and mentorship.

In this role, you’ll be part of a hands-on security team working across Infrastructure, Application, and Enterprise Security where responsibilities sometimes overlap. You’ll contribute to the design and implementation of security controls and solutions, review technical designs, and respond to findings from security researchers and penetration testers. You’ll also write code and build automation, using AI tools to help accelerate your work and strengthen security practices. Along the way, you’ll gain exposure to a wide range of security challenges that will accelerate your growth as a security engineer.

The base salary offered for this role and level of experience will begin at $130,000and up to $180,000. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience. 

In this role, you can expect to 

• Develop assistive automation and workflows to streamline the detection and reporting of security findings
• Contribute to tracking and remediation of discovered security vulnerabilities
• Participate in projects that reduce security risks and attack surface within our infrastructure and corporate applications
• Get the opportunity to use top notch AI systems in your daily work and play a role in strengthening their security

To thrive in this role, you have

• 1–3 years of experience in a security role, or in a development role with a focus on or enthusiasm for security
• Flexibility and a willingness to take on a variety of tasks in different security domains
• Practical coding experience preferably in Go, Python, or Ruby
• Hands-on experience with AWS and ideally GCP
• Exposure to cloud and application security concepts
• Experience with Terraform (a plus)

#LI-Hybrid #LI-JL1

Staff Engineer — API Core Platform

About the role

Together AI is seeking an experienced Backend Engineer to found Together’s API Platform team within the Production Foundations organization. In this role, you will define, build, and scale the core systems and architecture that power Together’s mission-critical APIs — including public customer APIs used directly by customers and via SDKs, CLIs, as well as the client APIs powering Together’s Cloud UI.

In the near term, you will improve and standardize the backend API layer within our primary Next.js monolith, raising the bar on reliability, performance, and consistency. In parallel, you will design and lead the evolution toward scalable, purpose-built next-gen API platform solutions optimized for different Public API and Client API use cases and traffic patterns — defining the long-term architecture and driving its incremental rollout.

This is a deeply hands-on role for an engineer who thrives on writing critical-path code and building platforms that unify engineering efforts across teams. You will work across backend systems, infrastructure layers, identity and access flows, and developer tooling to establish a cohesive API strategy that supports Together’s rapidly growing AI Cloud.

Responsibilities

• Design and drive the evolution of Together’s API platform, defining how APIs are built, versioned, secured, tested, and operated across the company
• Own and improve the backend API layer within our primary Next.js monolith, raising the bar on consistency, reliability, and performance
• Architect and lead the transition toward scalable, purpose-built API platforms optimized for different traffic patterns and product surfaces
• Write and maintain critical-path platform code that multiple services and product teams depend on
• Design and implement robust authentication, authorization, and identity-aware access patterns across public and internal APIs
• Establish performance standards for high-throughput APIs, implementing caching, rate limiting, fan-out control, and graceful degradation strategies
• Raise the bar on API observability and reliability, defining SLOs, monitoring, alerting, and incident response practices
• Drive API data modeling and schema generation strategies to ensure long-term maintainability and developer ergonomics
• Partner with infrastructure and security teams to maintain a strong security posture and evolve toward zero-trust architectures
• Mentor engineers, influence architectural direction across teams, and help define hiring standards as the API Platform grows

Required Qualifications

• 8+ years of experience building and operating large-scale, distributed backend systems in production environments
• Proven experience building or significantly evolving an API platform used by multiple teams or customer-facing products
• Expert-level proficiency in one or more of Golang, TypeScript, C++, or Java
• Deep expertise in API performance and scalability, including caching strategies, rate limiting, parallelization, fan-out control, and graceful degradation
• Strong experience designing and implementing production-grade authentication and authorization systems for customer-facing APIs
• Demonstrated ability to drive cross-team architectural initiatives without formal authority, aligning multiple stakeholders around long-term platform direction
• Experience building and operating systems using Infrastructure as Code (Terraform, AWS CDK, Pulumi) and modern CI/CD workflows
• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or equivalent practical experience

Nice to Have

• Experience with GraphQL or schema-based API federation systems
• Experience evolving APIs from monoliths to modular, platform-oriented architectures
• Experience designing and operating API schema generation and validation systems
• Experience building developer-facing SDKs or command-line tools
• Experience designing and operating multi-region, globally distributed API systems
• Experience designing horizontally scalable API systems capable of handling high request volume and burst traffic patterns
• Experience running production workloads in Kubernetes-based environments
• Experience building services in zero-trust or identity-aware architectures
• Experience with AWS networking, traffic management, and load balancing
• Experience with Cloudflare or CDN-level API performance optimization

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $240,000 - $275,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy 

About the Role

Together AI is seeking a Staff Backend Engineer to own the technical vision, architecture, and execution of the commerce platform powering Together's Cloud products. As a staff engineer on the Commerce Engineering team, you will set the engineering direction for mission-critical capabilities — including usage-based billing, payment processing, customer-facing analytics, and product entitlements — while raising the bar for the engineers around you.

This role is ideal for a seasoned engineer who can operate at multiple altitudes: driving system design and long-term architecture decisions while staying hands-on in code. You'll be the connective tissue between engineering, product, finance, and go-to-market — translating complex business requirements into durable, scalable backend primitives that directly impact revenue and customer experience. You'll be expected to define not just what we build, but how we build it well.

Requirements

• 8+ years of experience building large-scale, fault-tolerant API-driven services and backend systems
• Demonstrated track record of tech lead or staff-level scope — owning system architecture decisions, influencing team direction, and delivering multi-quarter initiatives
• Deep expertise in designing relational database schemas and backend APIs that support complex product and business requirements at scale
• Strong experience leading and influencing cross-functional teams — comfortable partnering with product, finance, and non-technical stakeholders
• Expert-level proficiency in one or more of Golang, TypeScript, Python, C++, or Java
• Deep knowledge of distributed systems tradeoffs: consistency, availability, fault tolerance, and performance at scale
• Strong understanding of low-level systems concepts: multi-threading, memory management, networking, storage, and I/O
• Experience with infrastructure as code (Terraform, AWS CDK, Pulumi) and mature CI/CD workflows
• Experience with payment processors (e.g. Stripe) and billing systems strongly preferred
• Experience with Kubernetes and containerized deployments a plus
• Bachelor's or Master's degree in Computer Science, Computer Engineering, or equivalent practical experience

Responsibilities

• Define and own the technical roadmap for Together's monetization and billing pipeline infrastructure, spanning usage metering, contract billing, entitlements, spend governance, and payments processing
• Lead architecture reviews for major systems investments, ensuring long-term scalability, correctness, and maintainability across the commerce stack
• Drive cross-functional alignment with Product, Finance, and Go-To-Market teams — translating business strategy into clear engineering requirements and system designs
• Mentor and grow engineers on the team through design feedback, code reviews, technical coaching, and setting high standards for craft
• Own data modeling and schema design for core commerce entities, making principled tradeoffs between flexibility, performance, and correctness
• Establish and evolve API contracts in collaboration with client engineering teams, enabling high-quality customer-facing product experiences
• Champion reliability and scalability — lead incident response, drive postmortems, and systematically improve the resilience of commerce APIs and distributed systems
• Identify and reduce technical debt proactively, balancing pragmatic delivery with sustainable engineering practices

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $230,000 - $270,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy

About the Role

Our team focuses on enabling custom models and dedicated inference on Together. We are responsible for building a container platform, optimizing autoscaling, minimizing cold starts, achieving the best end-to-end model performance, and providing a best-in-class developer experience with great tooling. We often focus on video or audio generation across the stack: CUDA kernels, pytorch optimization, inference engines, container orchestration, queueing theory, etc. An ideal candidate will be great at profiling/optimization but know the word kubernetes, or be intimately familiar with multi-cluster scheduling and have some sense of ML bottlenecks.

Responsibilities

• New hires may work on multi-cluster orchestration, portfolio optimization, predictive autoscaling, control panes, model bring-up, model optimization, APIs for managing deployments, inference worker SDKs, and CLI tools.
• Analyze and improve the robustness and scalability of existing distributed systems, APIs, databases, and infrastructure
• Partner with product teams to understand functional requirements and deliver solutions that meet business needs
• Write clear, well-tested, and maintainable software and IaC for both new and existing systems
• Conduct design and code reviews, create developer documentation, and develop testing strategies for robustness and fault tolerance

Requirements

• 5+ years of demonstrated experience in building large scale, fault tolerant, distributed systems.
• Experience running serverless inference platforms, doing model bring-up on short notice, being on call, or running a cloud provider is a very big plus
• Good taste and ability to thoughtfully discuss how what you’ve built has failed over time
• Experience designing, analyzing and improving efficiency, scalability, and stability of various system resources
• Excellent understanding of low level operating systems concepts including concurrency, networking and storage, performance and scale
• Expert-level programmer in one or more of Python, Golang, Rust, C++, or Haskell
• Proficiency in writing and maintaining Infrastructure as Code (IaC) using tools like Terraform
• Experience with Kubernetes internals or other container orchestration systems
• Sound judgement for when to use and when to not use LLMs for code
• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience
• Writing-heavy roles or companies are a plus

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $160,000 - $250,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

Together AI is looking for a Senior Data Engineer to help define, build, and operate the data infrastructure that handles millions of events every day to power Together’s mission-critical systems. As a Senior Data Engineer, you will work with our Data and Commerce engineering team to scale the data processing components of Together’s usage-based billing system, real-time customer-facing analytics product, and internal business intelligence tools. You will work across both cloud-native services and globally distributed data centers.

If you thrive in fast-paced environments and have a passion for defining and building early-stage data platforms for a rapidly scaling and data-intensive company, this is for you.

Requirements

• 5+ years of demonstrated experience in building large scale, fault tolerant, distributed data platforms, stream processing pipelines, ETLs, etc
• Expert-level skills in designing, building, and operating stream processing pipelines with services like AWS Kinesis, Apache Kafka, or Redpanda
• Expert-level knowledge of building real-time customer facing analytics systems using services like AWS TimeStream or Clickhouse
• Proficiency in writing and maintaining Infrastructure as Code (IaC) using tools like Terraform, AWS CDK, or Pulumi
• Proficiency in version control practices and integrating IaC with CI/CD pipelines.
• Proficiency in implementing and managing GitOps workflows with tools such as ArgoCD, Github Actions, TeamCity, or similar
• Proficiency in one or more of Golang, Rust, Python, Java, or TypeScript
• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience
• Experience with Kubernetes, or containers a plus

Responsibilities

• Identify, design, and develop foundational data infrastructure components capable of handling millions or billions of events daily
• Analyze and improve the robustness and scalability of existing data processing infrastructure
• Partner with product teams to understand functional requirements and deliver solutions that meet business needs
• Write clear, well-tested, and maintainable infra-as-code and software for both new and existing systems
• Conduct design and code reviews, create developer documentation, and develop testing strategies for robustness and fault tolerance
• Participate in an on-call rotation to address critical incidents when necessary

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $160,000 - $240,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

As a Senior Developer Productivity Engineer at Together AI, you’ll own the systems and tooling that empower engineers to ship high-quality software faster. You’ll optimize workflows, enhance testing, enable reliable and reusable CI/CD, and work with developers to build out stable local environments. Your work will directly impact release velocity, developer happiness, and cross-cutting enablement ensuring engineers spend less time churning on infrastructure and more time building.

Responsibilities

• Automate CI/CD pipelines for zero-downtime deployments (e.g., Canary, Blue/Green).
• Create smart pipelines encouraging reusable workflows and simplicity
• Streamline build/test/deploy workflows.
• Build shared tooling (CLIs, codegen, IDE plugins) to accelerate teams.
• Reduce friction (e.g., faster builds, hot-reload, test tooling).
• Collaborate with developers to identify pain points and streamline workflows.
• Champion best practices through documentation.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or related field or 5+ years of industry experience in DevOps/SRE, developer tooling, or infrastructure engineering.
• Proficiency in Python, Go, and JavaScript/TypeScript (for tooling, automation, and FE enablement).
• Strong experience with CI/CD tools (GitHub Actions, ArgoCD, Gitops methodology) for building scalable, reusable pipelines.
• Experience with local dev environment tooling (e.g., Skaffold) and containerized development workflows
• Experience with creating starter templates in coordination with engineering for enabling rapid spin up of new services 
• Strong ownership and a builder mindset, you love creating tools others rely on.
• Problem-solving rigor and attention to detail (e.g., diagnosing flaky tests, build latency).

Nice to have

• Kubernetes expertise (EKS, K3s) and optimizing containerized builds.
• Infrastructure as Code (Terraform, Ansible, Pulumi).
• Front-end tooling familiarity (e.g., React, Next.js, Jest) to optimize FE dev workflows.
• Monitoring/observability (Prometheus, Grafana, Honeycomb) to debug bottlenecks.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $150,000 - $230,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy

About the Role

Together AI is building the AI Acceleration Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art AI cloud infrastructure.

As a Senior AI Infrastructure Engineer, you will play a key role in building the next generation AI cloud platform – a highly available, global, blazing-fast cloud infrastructure that virtualizes cutting-edge ML hardware (GB200s/GB300s, BlueField DPUs) and enables state-of-the-art ML practitioners with self-serve AI cloud services, such as on-demand + managed Kubernetes and Slurm clusters. This platform serves both our internal SaaS products (inference, fine-tuning) and our external cloud customers, spanning dozens of data centers across the world.

Responsibilities

• Design, build, and maintain performant, secure, and highly-available backend services/operators that run in our data centers and automate hardware management, such as Infiniband partitioning, in-DC parallel storage provisioning, and VM provisioning.
• Design and build out the IaaS software layer for a new GB200 data center with thousands of GPUs.
• Work on a global multi-exabyte high-performance object store, serving massive datasets for pretraining.
• Build advanced observability stacks for our customers with automated node lifecycle management for fault-tolerant distributed pretraining.
• Perform architecture and research work for decentralized AI workloads
• Work on the core, open-source Together AI platform
• Create services, tools, and developer documentation
• Create testing frameworks for robustness and fault-tolerance

To be successful, you’ll need to be deeply technical and possess excellent communication, collaboration, and diplomacy skills. You have strong fundamental software development skills. In addition, you have strong systems knowledge and troubleshooting abilities. 

Requirements

• 5+ years of professional software development experience and proficiency in at least one backend programming language (Golang desired)
• 5+ years experience writing high-performance, well-tested, production quality code
• Demonstrated experience with building and operating high-performance and/or globally distributed micro-service architectures across one or more cloud providers (AWS, Azure, GCP)
• Excellent communication skills – able to write clear design docs and work effectively with both technical and non-technical team members
• Deep experience with Kubernetes internals a big plus, such as implementing non-trivial Kubernetes operators, device/storage/network plugins, custom schedulers, or patches thereon or Kubernetes itself
• Deep experience with VMs/hypervisors a big plus, such as QEMU/KVM, cloud-hypervisor, VFIO, virtio, PCIE passthrough, Kubevirt, SR-IOV
• Deep experience with DC networking tech + solutions a big plus, such as VLAN, VXLAN, VPN, VPC, OVS/OVN
• Experience with Cluster API or similar a big plus
• Experience working on high-performance compute, networking, and/or storage a big plus
• Experience virtualizing GPUs and/or Infiniband a big plus
• Strong systems knowledge across compute, networking, and storage, including concurrency, memory management, performant I/O, and scale
• Experience with infrastructure automation tools (Terraform, Ansible), monitoring/observability stacks (Prometheus, Grafana), and CI/CD pipelines (GitHub Actions, ArgoCD)
• Experience building IaaS or PaaS systems at scale a plus
• Experience with DPUs/SmartNICs a plus
• GPU programming, NCCL, CUDA knowledge a plus 

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $160,000 - $230,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

As an AI Infrastructure Engineer at Together, you are responsible for keeping all user-facing services and production systems running smoothly. You are a blend of a pragmatic operator and a software engineer that applies sound engineering principles, operational discipline, and mature automation to our operating environments and codebase.

You specialize in systems (operating systems, storage subsystems, networking), while implementing best practices for availability, reliability and scalability, with varied interests in algorithms and distributed systems.

Responsibilities

• Participate in on-call rotation (Pagerduty) to respond to production incidents
• Build and run our infrastructure with Ansible, Terraform, and Kubernetes to enable scaling to a massive number of concurrent users
• Build monitoring systems to ensure the highest quality service for our customers
• Design and implement operational processes (such as deployments and upgrades)
• Debug production issues across all services and levels of the stack
• Identify improvements for the product architecture from the reliability, performance and availability perspectives 
• Plan the growth of Together AI’s infrastructure

Requirements

• 5+ years of professional AI Infra or related experience
• Bachelor's degree in Computer Science or a related field or equivalent work experience
• Knowledge of Ansible (roles, playbooks), Terraform, and Kubernetes
• Proficiency in programming/scripting languages
• Direct experience in monitoring and observability practices
• Knowledge of cloud services
• Ability to thrive in a collaborative environment involving different stakeholders and subject matter experts

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $190,000 - $270,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

The Role

Pilot is hiring a Software Engineer to join our Bookkeeping Automation team.

This team builds the systems and tooling that power high-quality bookkeeping, including secure and reliable agentic workflows, integrations with third-party systems, and the infrastructure needed to operate them effectively in production. We focus on improving the accuracy, efficiency, and reliability of bookkeeping at scale.

As a Software Engineer on the team, you’ll build product and platform capabilities that help transform financial data into dependable bookkeeping outcomes. You’ll work closely with engineers, product managers, designers, and operational experts to ship systems that are practical, measurable, and robust.

This is a strong fit for someone who enjoys building real-world automation systems and is excited about the engineering challenges that come with agentic workflows, including orchestration, security, evaluation and observability.

Pilot’s backend is written in fully typed Python, and our frontend stack includes JavaScript, TypeScript, and Vue.js. We use Terraform to manage infrastructure, deploy containerized services on AWS, and rely on Postgres and modern observability tooling in production.

Location: San Francisco, CA (3 days/week in office - Mondays, Tuesdays, and Thursdays).

Key Responsibilities

• Build, test, and deploy software in a continuous manner
• Develop systems that power bookkeeping automation, including agentic workflows and integrations with third-party platforms
• Design and implement reliable workflow orchestration across services, tools, and operational processes
• Build observability into automation systems so teams can understand performance, investigate failures, and improve quality over time
• Contribute to the security and reliability of systems that handle sensitive financial data and operational decisions
• Help design and improve evaluation frameworks that measure workflow quality, correctness, and business impact
• Partner with PMs, designers, and cross-functional stakeholders to turn ambiguous problems into practical solutions
• Write clear technical designs, contribute thoughtful code reviews, and maintain high engineering standards
• Investigate production issues, improve system reliability, and support services as needed
• Ability to work in our San Francisco office Mondays, Tuesdays, and Thursdays

About You

Even if you don’t have experience with every part of our stack, we’d still love to talk.

We’re looking for someone who has:

• 3+ years of experience as a software engineer
• Experience building production software and shipping customer-facing or business-critical systems
• Strong coding fundamentals and the ability to write clean, maintainable, well-tested code
• Good product and systems judgment, especially in ambiguous or evolving problem spaces
• Strong communication skills and comfort working cross-functionally
• Interest in building automation systems that are reliable, observable, and secure
• A thoughtful approach to building systems that are trustworthy, practical, and effective in production

Nice to Have

• Experience with Python in production
• Experience with workflow orchestration, automation platforms, or distributed systems
• Familiarity with agentic or AI-assisted systems in production environments
• Experience building observability, alerting, or operational debugging tools
• Experience with system security, permissions, or handling sensitive data
• Experience building evaluation or quality measurement frameworks
• Experience with fintech, accounting, or financial operations tooling
• Experience integrating with third-party APIs and external systems

Why This Role Matters

The Bookkeeping Automation team is building systems that expand what Pilot can automate while preserving quality, trust, and control. Agentic workflows are only valuable when they are observable, secure, measurable, and reliable in production. This role is an opportunity to shape those foundations and help define how modern automation can improve financial operations at scale.

About Pilot

Pilot launched in 2017 to bring the back office into the modern era. Pilot provides small businesses with dedicated finance experts - which Pilot hires as full-time, U.S.-based employees - who learn the ins-and-outs of their business. Pilot integrates directly with the billing, banking, expense, and payroll systems customers already use. With a special blend of custom software and expert bookkeepers, Pilot delivers accurate, consistent bookkeeping and financial management and tax services that give entrepreneurs the freedom to focus on their business.

Pilot has over 3,000 customers and has raised over $170 million in financing from Sequoia, Index Ventures, Stripe, Bezos Expeditions, and Whale Rock.  Our investors also include a long list of world-class entrepreneurs, including Patrick and John Collison, Drew Houston, and Diane Greene.  Our most recent funding round doubled our valuation to $1.2 billion – Meet Fintech’s Newest Unicorn.

Why Pilot?

• We invest in our employees’ development and happiness because our employees are the keys to our success and ensuring happy customers
• The opportunity to join a seasoned founding team that has led companies through two prior successful startups and acquisitions (by Oracle and Dropbox).
• Flexible vacation/time-off policy
• All federal holidays are observed
• Competitive benefits package including additional wellness benefits
• Parental leave for birthing or non-birthing parents – 100% pay for 12 weeks
• 401(k) plan

The base pay range target for the role seniority described in this job description is $138,000 - $186,000 in San Francisco, CA. Final offer amounts depend on multiple factors such as candidate experience and expertise, geographic location, total compensation, and market data. In addition to cash pay, full-time regular positions are eligible for equity, 401(k), health benefits, and other benefits; some of these benefits may be available for part-time or temporary positions.

Pilot commits to provide a work environment free of discrimination and harassment, as well as equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. You may view all of Pilot’s recruiting notices here, including our EEO policy, information about requesting a reasonable accommodation in the job application process, recruitment agency policy, recruitment scam notice, and important E-Verify information. You may view our job candidate privacy policy here.

About the role

Anthropic's Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand.

Cluster Infra owns the full lifecycle of compute clusters at Anthropic. We build agent-driven automation for cluster provisioning and lifecycle management across all major cloud providers and our own datacenters. Our systems stand up clusters that are interconnected with high bandwidth, secure-by-default, and able to automatically drain and recover in response to failure. As a Staff engineer on this team, you'll set the technical direction for how Anthropic brings compute online - at a moment when the scale of that compute is growing faster than at almost any company in the world.

Key responsibilities

• Own the technical strategy and roadmap for agent-driven cluster lifecycle management - provisioning, updates and decommissioning
• Partner across teams to ensure new compute capacity is ingested on time
• Align with partner teams on physical build-out and leverage cloud solutions to deliver high-bandwidth inter-cluster connectivity
• Collaborate with security owners to ensure clusters are provisioned secure-by-default
• Define and drive strategy on cluster scalability, homogeneity and fault tolerance
• Work closely with cloud providers and internal research, inference and product teams to shape long-term compute, data, and infrastructure strategy
• Establish and evolve operational-excellence practices: incident response, postmortem culture and on-call health
• Support the growth of engineers around you through technical mentorship and coaching

Minimum qualifications

• Deep expertise in distributed systems, reliability, and cloud platforms (e.g., Kubernetes, IaC, AWS/GCP/Azure)
• Strong proficiency in at least one systems language (e.g., Rust, Go, or Python), IaC proficiency with Terraform.
• Track record of leading complex, multi-quarter technical initiatives spanning multiple teams or systems
• Ability to build alignment across senior stakeholders and communicate effectively at all levels

Preferred qualifications

• 8+ years of software engineering experience, including time as a technical lead setting direction for a team
• Experience operating large-scale compute infrastructure at hyperscale (100+ clusters, 10K+ nodes)
• Depth in one or more of: Kubernetes internals, cluster provisioning and management systems, cluster orchestration systems (Mesos, Borg-like)
• Experience with cloud networking: VPC design and peering, Shared VPC/Transit Gateway, Cloud Interconnect/Direct Connect, Cloud NAT, cross-cloud private connectivity, BGP and route control, edge load balancing and DDoS mitigation (Cloud Armor / AWS Shield)
• Experience with cluster and host networking: CNI (Cilium), eBPF, NetworkPolicy, multi-NIC, sFlow, service mesh (Istio/Envoy/Linkerd, mTLS)
• Experience with cluster security: pod security standards and admission control, RBAC and least-privilege IAM, node and container hardening, supply-chain/image provenance
• Deep experience with infrastructure-as-code (Terraform, Atlantis), workflow orchestration (Temporal, Argo Workflows)
• Skill in quickly understanding systems design tradeoffs and keeping track of rapidly evolving software systems

What we are looking for

Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all.

We're searching for a Staff Client Platform Engineer to join our Enterprise Site Reliability (SRE) team to lead the management of our enterprise Windows, Mac, and Ubuntu clients. The team is responsible for designing, implementing, and maintaining scalable and secure client device infrastructure. They also automate device deployment, configuration, and management processes.

This role will contribute to delivering the benefits of self-driving by leading the development of tailored client device solutions that address Aurora-wide and team-specific requirements for software and hardware development and manufacturing.

In this role you will

• Guide the approach and execution of the Client Platform Engineering Team
• Plan, design, and implement scalable solutions to manage Aurora's physical and virtual client platforms (Macs, Windows, Ubuntu) to ensure they receive security patches, configuration, and software package updates
• Partner with IT Support, InfoSec, and Developer Experience on strategy and implementation of client platform management solutions
• Handle escalations from IT Support, with an emphasis on mentoring and empowering IT Support to address similar problems
• Participate in the Enterprise SRE 24/7 on-call rotation

Required qualifications

• Experience of at least 8 years in Client Platform engineering and at least 3 years in leading engineering solutions (design to implementation) at scale.
• Expertise with client device lifecycle management, including experience across multiple client operating systems and various hardware platforms.
• Experience with MacOS, Windows, and Linux system administration.
• Experience deploying configuration management tools such as Intune, Kandji, Puppet, Ansible, or Chef.
• Experience with automation and tool development, preferably using Powershell, Go, or Python.
• Strong change management skills, including rollout planning and communication, and collaborating with stakeholders.
• Understanding of client endpoint security concepts and experience applying security hardening to client devices, such as CIS Benchmarks.
• Outstanding written and verbal communication skills that drive executional impact at scale. 
• Experience with automating testing for imaging, provisioning, and configuration management.

Desirable qualifications

• Experience working within cloud environments such as AWS, GCP, or Azure.
• Experience in environments deploying containerized workflows, using tools such as Docker or Kubernetes.
• Familiarity with SRE concepts such as SLIs, SLOs, SLAs, incident response, and best practices and partnering with teams on them.
• Experience with Infrastructure as Code (IaC) tools such as Terraform, Pulumi, or CloudFormation

The base salary range for this position is  $181,000 - $262,000 per Year. Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

P8841_3271246

About the role

Starburst is looking for an experienced Staff Software Engineer to sit at the intersection of software engineering and data engineering — building the internal platforms, pipelines, and data products that power how we understand our customers and our business. You'll work across Starburst Enterprise and Starburst Galaxy, using our own technology to solve real problems at scale, while also contributing software that other teams depend on.

Because data engineers are one of our primary target personas, you'll bring a uniquely valuable perspective: you'll use our products daily and feed that experience directly back into how we build and improve them. You'll work closely with a dynamic, talented, globally distributed team, writing production-quality software alongside building reliable data systems — with a consistent emphasis on quality, maintainability, and speed to insight.

As a Staff Software Engineer at Starburst you will:

• Design, build, and operate a high-quality data lake and the software systems that feed it, supporting product management, finance, customer support, and engineering
• Write production-grade software — services, APIs, tooling, and automation — that enables data workflows and integrations at scale
• Find innovative ways to use Trino and Starburst to solve complex data management and software architecture challenges
• Collaborate with technical leads, product managers, and data analysts to build robust data products and analytics
• Leverage AI to democratize access to datasets for users throughout Starburst, including building and maintaining the software infrastructure that makes this possible
• Enable dataset preparation and model evaluation for Starburst's AI projects
• Define and evolve engineering processes and best practices that span both software and data domains, with a focus on reliability and actionable results
• Work closely with leaders across teams to iterate on data architecture and the software systems that implement it, keeping quality high at every layer
• Identify emerging patterns in data management and software engineering, and work with Starburst's product teams to bring those innovations to market

Some of the things we look for

• A Trino enthusiast looking to push the bounds in an AI future
• At least 7 years of combined experience in software engineering and/or data engineering, with genuine depth in both
• Strong software engineering fundamentals: writing clean, testable, well-reviewed code in Java, Python, or Scala
• Experience building and optimizing data pipelines using Trino, Spark, dbt, and related frameworks
• Experience designing and building backend services, APIs, and data platform components
• Experience managing data and application infrastructure in public clouds, particularly AWS (EMR, EC2, S3, IAM); multi-cloud experience (GCP/Azure) is a plus
• Experience using and managing orchestration frameworks such as Apache Airflow or Dagster
• Knowledge of RAG and other design patterns for AI-powered applications
• Fluency in SQL and comfort moving between SQL and general-purpose programming as the task demands
• Experience building API integrations for extracting data from third-party sources
• Knowledge of data modeling techniques appropriate for modern data lakes
• Proficiency with Configuration-as-Code and Infrastructure-as-Code tools such as Pulumi, Terraform, and/or Ansible
• A track record of shipping reliable software and data systems on time, with disciplined practices around testing, code quality, and review
• Strong written and verbal communication skills, with the organizational ability to coordinate across teams

Where could this role be based?

• San Francisco, US

About the Role

Our Engineering team creates innovative product experiences that power personalized marketing at massive scale. We develop cutting-edge applications and systems that process 100s of billions of messages and events per year, enabling marketers to connect effectively with hundreds of millions of consumers. Joining our team offers a high-growth career opportunity to work with some of the world’s most talented engineers in a high-performance and high-impact culture.

As a Senior Software Engineer in our Intelligent Messaging, you will pioneer the future of personalized 1:1 marketing by architecting robust, scalable backend systems powered by advanced AI and LLMs, including cutting-edge Generative AI and GPT technologies. Collaborating with top-tier engineers, data scientists, product managers, and designers, you’ll craft the foundation and reshape the platform of multi-channel messaging experimentation to support innovative, AI-driven applications that empower marketers to forge deep, meaningful connections with consumers at scale. Your impactful work will drive the delivery of billions of tailored messages, transforming consumer shopping experiences and fueling success for the world’s leading brands.

What You’ll Accomplish

• Develop and maintain scalable backend systems for our customer-facing products, ensuring high performance and reliability.
• Collaborate with cross-functional teams to build applications that support multi-channel communications for marketers.
• Implement and optimize systems that process and deliver billions of messages daily.
• Improve code quality through code reviews, testing, and advocating for best practices.
• Identify and address technical debt to ensure the long-term health of our codebase.
• Drive architectural design and technical decisions, and stay current with emerging technologies to enhance our products.

Your Expertise

• 5+ years of professional experience in software development focusing on backend systems.
• Proficiency in Java, Python, or Go, with a strong understanding of object-oriented programming.
• Experience building and maintaining scalable, high-performance applications.
• Proven ability to collaborate effectively with cross-functional teams.
• Solid understanding of software development best practices, including code reviews, writing tests, and continuous integration.

Nice to Haves

• Experience with service-oriented architecture and distributed systems.
• Familiarity with AWS services and cloud infrastructure.
• Knowledge of databases such as DynamoDB, Postgres, or Redis.
• Experience with messaging systems or streaming platforms (e.g., Kafka, Pulsar).
• Familiarity with frontend development with React and TypeScript.
• Experience with DevOps practices and tools such as Docker and Kubernetes.

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS.
• Infrastructure tooling includes Istio, Datadog,Terraform, CloudFlare, and Helm.
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, Kinesis, AirFlow, Postgres, Planetscale, and Redis, hosted via AWS.
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and PlaywrightOur automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas.

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $190,000 - $230,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

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The Position: 

OPSWAT is now searching for Tier 2 Technical Support Engineer to join our Customer Support team. The role focuses on diagnosing and resolving complex technical issues and escalated issues from tier 1 support and ensuring customer satisfaction through timely responses. We are looking for an energetic and motivated person who likes interacting with customers, tinkering with software, learning about new technologies, and “doing what it takes,” to contribute to OPSWAT’s quick growth.

Responsibilities:

• Handle complex technical issues and escalated ones from tier 1 support via phone, case system, and chat.
• Provide advanced troubleshooting and support for OPSWAT solutions via log analysis, system diagnostics, network configurations.
• Conduct remote sessions with customers.
• Reproduce customer issues in lab environments and validate solutions and bug fixes.
• Evaluate the complexity of issues and escalate to tier 3 support.
• Collaborate with Tier 1 and Tier 3 support well.
• Work closely with technically oriented customers (typical customers are engineers and IT personnel).
• Provide status updates to customers, adhering to SLA and commitments.
• Maintain clear and professional communication to ensure positive customer experience and CSAT
• Contribute to the KBs creation and updates for customer’s self-service.
• Mentor L1 support and contributes to support process improvement.
• Get involved in professional delivery services.
• Get involved in other side projects and operations per request.

Minimum requirements:

• A good foundation of basic networking concepts.
• Basic knowledge of Linux, with an interest in expanding the knowledge.
• Ability to think logically, analyze logs and troubleshoot computer software and IT related issues.
• Troubleshooting SCADA communications issues
• Hands-on understanding of major DevOps tools: Docker, Kubernetes (GCP GKE), CI/CD tools, Terraform, Ansible, Monitoring & Logging Tools (Zipkin, Sentry, Prometheus, ELK stack).
• Strong spoken and written English.
• Excellent communication and interpersonal skills.
• A proven customer-oriented attitude.
• Strong team collaboration abilities and organizational skills.
• At least 2-4 years of Experience in providing customer support of technical software products or a technical helpdesk environment or a related field.

 Nice to have

• Bachelor’s degree in computer science (CS), or technical discipline, or equivalent experience.
• Experience working with offshore teams. 
• Familiarity with computer programing.
• Technical familiarity with Mac OS.
• Cybersecurity domain experience, including file security, device security, network security, etc.
• Network integration skillsets (e.g. Cisco, Dell-EMC, Juniper, Aruba, Ruckus, Meraki, Aerohive, Extreme, etc).
• Certifications/Training: Relevant SCADA or PLC OEM certifications.
• Experience in Control System Design, PLC Programming, & SCADA Development
• Experience in Cloud Based Services (e.g. AWS, GCP).
• Experience working on Linux based infrastructure.
• Experience working with scripting languages such as bash script, PowerShell, and Python.
• Configuration and management of databases such as MySQL, Mongo.

About Black Forest Labs

We’re the team behind Latent Diffusion, Stable Diffusion, and FLUX—foundational technologies that changed how the world creates images and video. We’re creating the generative models that power how people make images and video—tools used by millions of creators, developers, and businesses worldwide. Our FLUX models are among the most advanced in the world, and we’re just getting started.

Headquartered in Freiburg, Germany with a growing presence in San Francisco, we’re scaling fast while staying true to what makes us different: research excellence, open science, and building technology that expands human creativity.

Why This Role

You'll design, deploy, and maintain the ML infrastructure backbone that makes frontier AI research possible. This isn't abstract systems work—every decision you make directly impacts whether a multi-week training run succeeds, whether inference stays fast enough for production, whether researchers can iterate quickly or wait hours for resources.

What You’ll Work On 

You'll be the person who:

• Designs, deploys, and maintains cloud-based ML training clusters (Slurm) and inference clusters (Kubernetes) that researchers and products depend on
• Implements and manages network-based cloud file systems and blob/S3 storage solutions optimized for ML workloads at scale
• Develops and maintains Infrastructure as Code (IaC) for resource provisioning—because manual configuration doesn't scale and configuration drift breaks things
• Implements and optimizes CI/CD pipelines for ML workflows, making it easy for researchers to go from experiment to production
• Designs and implements custom autoscaling solutions for ML workloads where standard approaches fall short
• Ensures security best practices across the ML infrastructure stack without creating friction that slows down research
• Provides developer-friendly tools and practices that make ML operations efficient—because infrastructure that's hard to use doesn't get used

What We’re Looking For

You've built and managed ML infrastructure at scale and understand that supporting AI research is fundamentally different from traditional cloud infrastructure. You've been paged because a training run failed. You've debugged why storage became the bottleneck. You know the difference between infrastructure that works in demos and infrastructure that works when researchers depend on it for months-long experiments.

You likely have:

• Strong proficiency in cloud platforms (AWS, Azure, or GCP) with focus on ML/AI services—you know which services matter and which are marketing
• Extensive experience with Kubernetes and Slurm cluster management in production environments
• Expertise in Infrastructure as Code tools (Terraform, Ansible, etc.) and the discipline to actually use them
• Proven track record managing and optimizing network-based cloud file systems and object storage for ML workloads
• Experience with CI/CD tools and practices (CircleCI, GitHub Actions, ArgoCD, etc.) in ML contexts
• Strong understanding of security principles and best practices in cloud environments—without making security the enemy of velocity
• Experience with monitoring and observability tools (Prometheus, Grafana, Loki, etc.) that help you understand what's actually happening
• Familiarity with ML workflows and GPU infrastructure management—you understand what researchers need
• Demonstrated ability to handle complex migrations and breaking changes in production environments without losing data or breaking experiments

We'd be especially excited if you:

• Have experience building custom autoscaling solutions for ML workloads that standard tools can't handle
• Bring knowledge of cost optimization strategies for cloud-based ML infrastructure (because GPU hours add up)
• Are familiar with MLOps practices and tools
• Have experience with high-performance computing (HPC) environments
• Understand data versioning and experiment tracking for ML
• Know network optimization techniques for distributed ML training
• Have worked with multi-cloud or hybrid cloud architectures
• Are familiar with container security and vulnerability scanning tools

How We Work Together

We’re a distributed team with real offices that people actually use. Depending on your role, you’ll either join us in Freiburg or SF at least 2 days a week (or one full week every other week), or work remotely with a monthly in-person week to stay connected. We’ll cover reasonable travel costs to make this possible. We think in-person time matters, and we’ve structured things to make it accessible to all. We’ll discuss what this will look like for the role during our interview process.

Everything we do is grounded in four values:

• Obsessed. We are a frontier research lab. The science has to be right, the understanding deep, the product beautiful.
• Low Ego. The work speaks. The best idea wins, no matter who said it. Credit is shared. Nobody is above any task.
• Bold. We take the ambitious bet. We ship, we do not wait for conditions to be perfect.
• Kind. People over politics. We treat each other with genuine warmth. Agency without empathy creates chaos.

If this sounds like work you’d enjoy, we’d love to hear from you.

Base Annual Salary: $180,000–$300,000 USD

We're based in Europe and value depth over noise, collaboration over hero culture, and honest technical conversations over hype. Our models have been downloaded hundreds of millions of times, but we're still a ~50-person team learning what's possible at the edge of generative AI.

About ROLLER

ROLLER is not your average software-as-a-service company. With a global presence in over 30 countries, we're here to bring some excitement to the leisure and attractions industry and make a difference! Our mission is to help businesses operate smoothly and create fun and memorable guest experiences by providing seamless ticketing, point-of-sale, self-serve kiosks, memberships and digital waiver processes.

But here's the best part: our team. We're a group of 300+ highly passionate, enthusiastic, and down-to-earth professionals located all around the world who are all working together to build something truly remarkable. We're aiming high and believe that the possibilities are endless. As we continue to grow globally, we're excited to write our success story and have fun along the way.

We genuinely love what we do, and we're looking for like-minded people to join us on this amazing journey. If you're ready to be part of a dynamic team and make a real impact, come aboard, and let's create some unforgettable experiences together at ROLLER!

About the Role

We are seeking a highly technical, hands-on Senior Data Engineer to architect and scale our data infrastructure from the ground up. As a core member of the data function within our Business Technology team, you will be responsible for building the pipelines and models that power smarter decision-making and operational efficiency across the entire organization.

In this foundational role, you will build & architect the modern data stack, ensuring our infrastructure is robust, automated, and governed. You collaborate as a technical partner with GTM ,Product, Finance, P&C to build high-performance data models and pipelines that transform raw data into actionable cross-functional insights.

Joining ROLLER at this pivotal growth stage, you will have the opportunity to make an outsized impact on our technical landscape, directly influencing how we process data to deliver world-class experiences for our customers globally.

What You'll Do

• Scalable Architecture: Design and implement robust Data Modeling and Architecture strategies that support high-volume data processing and maintain long-term scalability.
• Cloud Ecosystem: Develop and manage end-to-end data pipelines using Google Cloud Platform services, specifically leveraging Cloud Run, Cloud Function for compute, BigQuery for storage, and Cloud Composer (Airflow) for orchestration.
• Transformation Excellence: Build, maintain, and document complex data transformation layers using DBT (Data Build Tool) to ensure high data quality and reliability.
• Infrastructure as Code: Automate the provisioning of cloud resources using Terraform and streamline deployment workflows via GitHub Actions CI/CD pipelines.
• Cloud Data Warehousing: Demonstrate expert-level proficiency in managing and optimizing Cloud Data Warehouses, such as Snowflake & BigQuery.
• Team Collaboration: Partner with cross-functional stakeholders to build and scale high-performing data infrastructure that supports engineering, analytics, and Data Program needs.
• Stack Management: Architect and maintain a modern data stack by implementing best-in-class tools including Snowflake, Bigquery, dbt, Fivetran, Looker, Tableau and Airflow.
• Pipeline Engineering: Develop scalable ETL/ELT workflows and robust data models to deliver real-time analytics and unified business reporting.
• Data Visualization: Create and maintain intuitive, high-performance Looker dashboards will be an added advantage.

About You

You are a technical builder who views data as a competitive advantage. You thrive in fast-paced environments and have a proven track record of engineering scalable data foundations from the ground up. Equal parts architect and analytical problem-solver, you excel at balancing long-term technical vision with the daily hands-on execution of complex pipelines.

You are energized by the full lifecycle of data—moving beyond just writing code to actively leading project discovery and analysis alongside cross-functional partners. You take pride in enabling GTM, Product, Finance & P&C teams through clear insights and high-performance systems. Most importantly, you are excited to act as a founding technical force for a high-growth SaaS company that is transforming the guest experience for attractions businesses globally.

• 5+ years of experience in Data & Analytics or Data Engineering with a focus on Scalable cloud driven data pipeline build

• Proven experience in dimensional modeling (Star/Snowflake schema) and designing architectures that support both historical reporting and real-time needs.
• Expert-level proficiency in Snowflake or BigQuery, including performance tuning, cost optimization, and access control (RBAC).
• Hands-on experience with Google Cloud Platform services, specifically Cloud Function, Cloud Run for containerized workloads and Cloud Composer for orchestration.

• Through hands-on experience of dbt (Data Build Tool) to manage transformations, including writing custom macros, implementing tests, and generating documentation.
• Solid experience using Terraform to provision cloud resources, ensuring that infrastructure is version-controlled and reproducible.
• Proficiency in GitHub Actions to automate testing and deployment pipelines for data models and infrastructure.
• Ability to design high-performance dashboards that prioritize user experience and fast load times.

• Experience collaborating with Finance, GTM, and Product to define key metrics (like CAC, LTV, or Churn) and codifying them into the data layer.
• Familiarity with data ingestion tools like Fivetran , Airbyte, Workato, Mulesoft to sync data from various SaaS platforms into the warehouse.

• Operates as a full-stack Data Engineer with the technical authority to architect and build entire data lifecycles, from raw source ingestion to high-impact data visualization.
• Familiarity with business-critical systems like Salesforce, Chargbee, Gainsight, and product analytics tools.
• Strong communicator with a track record of working across technical and non-technical teams to drive alignment.
• You have a high appetite for Technology and AI and a natural curiosity for how it can transform your work. You’re comfortable using AI tools to automate repetitive 'busy work,' freeing you up to focus on high-impact work.

We believe AI is a career-defining inflection point. ROLLER is a fast adopter of new technology like AI, and every team member is empowered to own their learning and use the latest tools to supercharge their impact. We’re looking for candidates with the proficiency and curiosity to embrace AI and technology — not just as a technical skill, but as a core competency to help us achieve big goals

Preferred Qualifications

• Experience partnering with IT or Business Technology teams to drive cross-functional outcomes.
• Exposure to customer success and revenue workflows, such as onboarding journeys, renewal metrics, or support analytics.
• Familiarity with AI/ML pipelines and experimentation frameworks that support data-driven innovation.

Perks!

• You'll get to work on a category-leading product that customers love in a fun, high-growth industry! Check our Capterra and G2 reviews.
• ROLLER Recharge days to celebrate and recharge once we've hit our goals
• Engage in our 'Vibe Tribe' - led by our team members; you can contribute to company-wide initiatives directly. Regular events and social activities, fundraising & cause-related campaigns...you name it. We're willing to make it happen!
• Team Member Assistance Program to proactively support our team's health and wellbeing - access to coaching, education modules, weekly webinars, and more.
• 16 weeks paid Parental Leave for primary carers and 4 weeks paid Parental Leave for secondary carers.
• Work with a driven, fun, and switched-on team that likes to raise the bar in all we do!
• Individual learning & development budget plus genuine career growth opportunities as we continue to expand!

What You Can Expect

1. Initial call with our Talent Acquisition Manager
   You'll have an initial call with our Talent Acquisition Manager to chat through some of your experience to date, salary expectations and you can check off any initial questions you might have.
2. Interview with the Hiring Manager
   You'll get to meet with the hiring manager to learn more about the role & ROLLER whilst also talking through your experience in more detail.
3. Loop Interviews
   This is where you will get to meet our wider ROLLER team to do a 'vibe check' on us to make sure our culture & vibe meet what you are looking for!
4. Offer
   If all lights are green and the fit feel right, we'll conduct reference checks and you'll receive an offer to join!