Staff Software Engineer

Posted 3 Days Ago
5 Locations
In-Office or Remote
Expert/Leader
Artificial Intelligence • Information Technology • Machine Learning • Software
The Role
Provides technical leadership for scalable Kubernetes-based infrastructure across multi-cloud and hybrid environments. Architects control plane services, tenancy models, deployment pipelines, observability, and reliability capabilities. Drives modernization through GitOps, policy-as-code, networking, autoscaling, CI/CD, and container lifecycle practices. Collaborates with SRE, platform, and application teams, mentors engineers, influences technical roadmaps, participates in on-call rotations, and improves infrastructure performance, resilience, and developer experience.
Summary Generated by Built In

Job Description:

DataRobot delivers AI that maximizes impact and minimizes business risk. Our platform and applications integrate into core business processes so teams can develop, deliver, and govern AI at scale. DataRobot empowers practitioners to deliver predictive and generative AI, and enables leaders to secure their AI assets. Organizations worldwide rely on DataRobot for AI that makes sense for their business — today and in the future. 

You’ll be responsible for technical leadership and vision. You’ll lead by example—rolling up your sleeves as a technical contributor to solve complex problems, shaping architecture, and mentoring engineers to do their best work and advance their careers. You’ll work across our control plane systems, influence cross-team roadmaps, and bring pragmatic engineering practices into how we build, test, and operate infrastructure software.

This is not a “stay in your swim lane” role. You’ll question assumptions, challenge complexity, and help drive a high-performance culture. You’ll be trusted to bring clarity where there’s ambiguity, and momentum where there’s inertia.

This role includes participation in an on-call rotation—we believe in shared ownership of our platform and aim to build systems that are resilient, observable, and require minimal intervention.

What You’ll Do:

  • Architect and implement scalable, secure Kubernetes-based infrastructure for multi-cloud and hybrid environments.

  • Lead technical direction for core Fleet initiatives—control plane services, tenancy models, deployment pipelines, observability layers, and more.

  • Mentor engineers across the team, fostering a strong engineering culture of ownership, curiosity, and excellence.

  • Drive modernization efforts—introducing patterns like GitOps, Policy-as-Code (Kyverno), Cilium networking, autoscaling, and better resource efficiency.

  • Collaborate deeply with SRE, Platform, and Application teams to align infrastructure capabilities with real-world product demands.

  • Champion best practices in CI/CD, reliability, container lifecycle management, and dev experience.

  • Be a thought partner to engineering leadership and help shape how Fleet scales its impact across the company.

What We’re Looking For:

  • 7-10+ years of engineering experience, with at least 5+ in infrastructure, platform, or backend systems roles.

  • Strong proficiency in modern programming languages such as Python or Go. Experience building production-quality, reliable, and observable systems that are used across engineering organizations.

  • Proven ability to design and build systems from scratch, making pragmatic tradeoffs along the way.

  • Deep expertise in Kubernetes internals and operations, including networking, scheduling, scaling, and controller patterns.

  • A growth-oriented mindset—driven to teach, learn, and improve systems as well as people.

  • Experience operating across multiple cloud providers (AWS, GCP, Azure) and/or hybrid environments.

  • Strong experience with Helm, container orchestration patterns, and CI/CD automation.

  • Comfortable working with IaC (Terraform, Pulumi) and GitOps workflows.

  • Ability to influence without authority and align diverse stakeholders around technical decisions.

Nice to Have:

  • Familiarity with Cilium, Kyverno, KEDA, Gateway API, OPA, or similar technologies.

  • Experience building and running multi-tenant SaaS platforms.

  • Exposure to on-prem delivery models or regulated environments.

  • Experience with performance tuning for large-scale data or compute workloads.

  • Past success driving infrastructure transformation or decomposing legacy systems.

  • Experience working with GPU infrastructure for training and inference.

The talent and dedication of our employees are at the core of DataRobot’s journey to be an iconic company. We strive to attract and retain the best talent by providing competitive pay and benefits with our employees’ well-being at the core. Here’s what your benefits package may include depending on your location and local legal requirements: Medical, Dental & Vision Insurance, Flexible Time Off Program, Paid Holidays, Paid Parental Leave, Global Employee Assistance Program (EAP) and more!

DataRobot Operating Principles:

  • Wow Our Customers
  • Set High Standards
  • Be Better Than Yesterday
  • Be Rigorous
  • Assume Positive Intent
  • Have the Tough Conversations
  • Be Better Together
  • Debate, Decide, Commit
  • Deliver Results
  • Overcommunicate


Research shows that many women only apply to jobs when they meet 100% of the qualifications while many men apply to jobs when they meet 60%. At DataRobot we encourage ALL candidates, especially women, people of color, LGBTQ+ identifying people, differently abled, and other people from marginalized groups to apply to our jobs, even if you do not check every box. We’d love to have a conversation with you and see if you might be a great fit. 

DataRobot is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. DataRobot is committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. Please see the United States Department of Labor’s EEO poster and EEO poster supplement for additional information.


Use of Artificial Intelligence in Our Hiring Process


DataRobot uses approved AI-powered tools to support the hiring process in selected regions. These tools may assist in writing job descriptions, reviewing applications, assessing qualifications, and evaluating candidate materials. All decisions regarding applications are made by members of the DataRobot team.

All applicant data submitted is handled in accordance with our Applicant Privacy Policy.

Skills Required

  • 7-10+ years of engineering experience
  • At least 5+ years in infrastructure, platform, or backend systems roles
  • Strong proficiency in Python or Go
  • Experience building production-quality, reliable, and observable systems
  • Ability to design and build systems from scratch and make pragmatic tradeoffs
  • Deep expertise in Kubernetes internals and operations, including networking, scheduling, scaling, and controller patterns
  • Experience operating across multiple cloud providers such as AWS, GCP, and Azure, and/or hybrid environments
  • Strong experience with Helm, container orchestration patterns, and CI/CD automation
  • Experience with Infrastructure as Code using Terraform or Pulumi
  • Experience with GitOps workflows
  • Ability to influence without authority and align diverse stakeholders around technical decisions
  • Familiarity with Cilium, Kyverno, KEDA, Gateway API, OPA, or similar technologies
  • Experience building and running multi-tenant SaaS platforms
  • Exposure to on-premises delivery models or regulated environments
  • Experience with performance tuning for large-scale data or compute workloads
  • Experience driving infrastructure transformation or decomposing legacy systems
  • Experience working with GPU infrastructure for training and inference

DataRobot Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about DataRobot and has not been reviewed or approved by DataRobot.

  • Fair & Transparent Compensation — Pay is described as competitive and often positioned as fair relative to comparable roles, with salary bands that can reach the upper end for certain positions. Overall compensation is also framed as strong enough to attract and retain top talent.
  • Equity Value & Accessibility — Equity is consistently included as part of the compensation package, with restricted stock awards and stock-related programs featured as meaningful components. The presence of equity for employees is treated as a key differentiator in total rewards.
  • Healthcare Strength — Health, dental, and vision coverage are presented as comprehensive, and the overall benefits bundle is portrayed as strong. Additional coverage like pet insurance further reinforces the breadth of healthcare-related support.

DataRobot Insights

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The Company
HQ: Boston, MA
1,610 Employees
Year Founded: 2012

What We Do

DataRobot is the AI Cloud leader, delivering a unified platform for all users, all data types, and all environments to accelerate delivery of AI to production. Trusted by global customers across industries and verticals, including a third of the Fortune 50, delivering over a trillion predictions for leading companies globally.

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