Staff Software Engineer

DataRobot; Boston (MA); On-site; USD 120,000 - 150,000; Full time

Benefits offered by this job

Medical, Dental & Vision Insurance

Flexible Time Off Program

Paid Holidays

Paid Parental Leave

Global Employee Assistance Program (EAP)

Job summary

A leading AI solutions company in Boston is seeking a Staff Software Engineer focused on Application Scalability & Performance. This role requires leading the design and operation of backend systems critical for high-throughput AI applications. Candidates should have over 7 years of experience in backend engineering, strong programming skills, and the ability to optimize system performance. This position offers competitive pay and various employee benefits.

Qualifications

• 7+ years of backend engineering experience in scalable systems.
• Experience with performance optimization techniques.
• Ability to operate across multiple cloud providers.

Responsibilities

• Lead design and implementation of backend systems.
• Collaborate with teams on high-impact projects.
• Optimize for latency, throughput, and reliability.

Skills

Backend engineering experience

Performance optimization

Autoscaling

Resource management

Load balancing

Strong programming skills

Monitoring and observability

Tools

Python

Java

Go

C++

Docker

Job description

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.

As a Staff Software Engineer focused on Application Scalability & Performance, you will lead the design, implementation, and operation of backend systems that power high-throughput AI applications. Your work will ensure our applications perform with high accuracy, minimal latency, and robust scalability (including autoscaling), all while maintaining reliability, cost-effectiveness, and maintainability. You will collaborate closely with Product, Platform, and AI/ML teams to deliver high impact.

Key Responsibilities

• Architect, build, and lead backend services that scale to handle large workloads, high concurrency, and low latency requirements.
• Design and implement autoscaling strategies (horizontal/vertical), dynamic resource allocation, and load balancing to ensure responsive, cost-efficient service.
• Improve end-to-end request pipelines, optimizing for latency, throughput, reliability, and correctness.
• Instrument, monitor, and profile systems in production; identify bottlenecks, troubleshoot performance issues, and proactively tune services.
• Collaborate with ML/AI teams to ensure models serving pipelines uphold accuracy, consistency, and performance under load.
• Drive best practices in systems reliability, observability, error handling, capacity planning, resilience, and failover.
• Mentor and coach other engineers; provide technical leadership and influence across teams.
• Contribute to defining architecture, coding standards, performance benchmarks, and technical roadmap items related to scalability and performance.

Knowledge, Skills, and Abilities

• 7+ years of backend engineering experience building scalable, high-performance distributed systems / services.
• Strong experience with performance optimization: profiling, latency tuning, concurrency, caching strategies.
• Deep experience with autoscaling, resource management, load balancing, throughput/latency SLAs.
• Solid programming skills in one or more backend languages (Python, Java, Go, C++, or equivalent).
• Strong understanding of observability and monitoring: metrics, tracing, logging; and instrumentation of services.
• Ability to solve ambiguous challenges and influence technical direction across teams, balancing performance, accuracy, and cost.
• Experience operating across multiple cloud providers (AWS, GCP, Azure) and/or hybrid environments.

Nice to Have

• Experience with AI/ML model deployment, serving, inference, and production integration.
• Experience with Gen AI / serving LLMs, embeddings, etc.
• Exposure to on-prem delivery models or regulated environments.
• Experience with Docker and building containerized applications.

Benefits

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

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%. DataRobot encourages 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.

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