Salas O'Brien Logo

Salas O'Brien

Data & AI Product Engineer

Reposted 2 Days Ago
Remote
Hiring Remotely in United States
95K-115K Annually
Mid level
Remote
Hiring Remotely in United States
95K-115K Annually
Mid level
Build and operate Lakehouse data pipelines, product features, machine learning and generative AI components, testing, monitoring, instrumentation, and documentation. Collaborate with product managers, engineers, and business users to clarify requirements, deliver production solutions, investigate defects, and improve reliability and performance. Participate in code reviews, technical design discussions, and backlog-driven development while following engineering standards and contributing to scalable Data & AI products.
The summary above was generated by AI

 

Data & AI Product Engineer

At Salas O’Brien we tell our clients that we’re engineered for impact. This passion for making a difference applies just as much to our team as it does to our projects. That’s why we’re committed to living our values every day: inspiring, achieving, and connecting as shared owners of our success with a focus on a sustainable future.

Building for the long-term means that all of our team members can expect to work on amazing projects with a people-first approach to problem solving. It also means that each member of our team has truly limitless potential to build a unique, meaningful, and high-impact career—and they’ll receive great total rewards along the way.

About Us

Founded in 1975, Salas O’Brien is an employee-owned engineering and professional services firm focused on achieving impact for our clients, our team, and the world. We know that tomorrow’s requirements are today’s opportunities, and we are here to design lasting solutions for pressing challenges.

We work across a variety of industries providing integrated engineering and consulting services. Our specialized experience includes design for data centers, healthcare, science and technology, high-rise buildings, clean energy, education, and other building types as well as structural and building sciences, infrastructure asset management, advanced robotics, and more.

Our technical expertise is paired with an exceptional team of business development, human resources, finance and accounting, information technology, and marketing professionals, all of whom play a key role in bringing our commitments to life every day.

Job Summary

As a Data & AI Product Engineer, you will help build and support the pipelines, models, and applications that power practical Data & AI products. You will contribute to meaningful product features while working within established platform patterns, engineering practices, and quality standards.

This is a hands-on engineering role with room to grow. You will work on real business problems, collaborate with experienced teammates, and help bring solutions from idea through production.

You will be part of a small product pod, working closely with a Product Manager and other engineers to deliver useful, reliable products and improve them over time.

Reporting and Scope

This role reports to the Data & AI Product Manager for the assigned product, with technical guidance from the Senior Data & AI Product Engineer on the pod.

As your experience grows, there is a path toward a Senior Data & AI Product Engineer role based on demonstrated technical depth, reliable independent delivery, and the ability to lead design for meaningful work.

Responsibilities
  • Build and operate data pipelines on the Lakehouse, including ingestion, transformation, quality checks, and the monitoring that catches failures early.
  • Develop product features from requirements through production, including testing and documentation as part of the delivery process.
  • Build machine learning or generative AI components when they support the product roadmap, including evaluation practices to confirm performance and usefulness.
  • Follow platform patterns and engineering standards for the pod, and share feedback when standards can be improved.
  • Participate in code reviews to improve quality, share knowledge, and support consistent engineering practices.
  • Support what you build by investigating defects, addressing root causes, and communicating updates clearly to the Product Manager.
  • Add instrumentation so product usage, reliability, and performance can be measured and improved.
  • Work directly with business users to clarify requirements, understand intent, and shape practical solutions.
  • Contribute to design discussions and technical decisions with the product pod.
  • Maintain clear documentation for the components and workflows you support.
How the Work Arrives

Work is driven by a prioritized product backlog and often begins with a business problem to solve. You will help clarify needs, recommend an approach, and partner with the team to build solutions that are practical, scalable, and useful.

You will have support and technical guidance as you learn the platform and products. Over time, demonstrated judgment and delivery will lead to broader ownership and more complex technical work.

Qualifications and ExperienceWho You Are
  • You enjoy building reliable solutions and seeing your work make it into production.
  • You ask thoughtful questions, seek context, and help the team stay focused on the right solution.
  • You are curious about the business, not only the technology.
  • You see code review as a collaborative way to improve quality, learn from others, and strengthen the product.
  • You are motivated to keep growing and welcome feedback from teammates with deeper experience.
Required
  • Three or more years of professional experience in data engineering, machine learning engineering, analytics engineering, or software development.
  • Working Python and SQL skills, including the ability to write, test, and debug production code without close supervision.
  • Experience with a cloud data platform and distributed data processing concepts.
  • Experience with version control and collaborative development practices, including branching, pull requests, and code review.
  • Understanding of data modeling and data quality fundamentals.
  • Ability to work from a backlog, communicate progress clearly, and raise risks or timing considerations early.
  • Bachelor's degree in engineering, computer science, mathematics, or a related discipline, or equivalent experience.
Preferred

Hands-on Databricks experience, including workflows, Delta Lake, and Unity Catalog, is highly valued. Experience with continuous integration and deployment practices for data workloads is also helpful.

Experience delivering solutions for internal business users is beneficial, especially when requirements begin as process needs or business questions rather than detailed technical specifications.

Nice to Have
  • Databricks certification at the associate or professional level.
  • Experience with MLflow, model serving, or generative AI application patterns.
  • Front-end development experience, including React or a comparable framework.
  • Familiarity with architecture, engineering, or professional services operations.
Location

This position is remote within the United States.

Compensation & Benefits

The expected base salary range for this role is $95,000 - $115,000 USD per year. Actual compensation will be determined based on a number of factors including skills, experience, qualifications, and location.

This role is also eligible for performance-based bonuses, equity participation, and a comprehensive U.S.-based benefits package, including:

  • Medical, dental, and vision insurance
  • 401(k) with company match
  • Paid time off and company holidays
  • Wellness programs and employee assistance resources
  • Professional development support
Equal Opportunity Employment Statement

Salas O’Brien provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, colour, 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/provincial, or local laws. Salas O’Brien will accommodate the disability-related needs of applicants as required by law.

Third-Party Agency Notice

Salas O’Brien does not accept unsolicited resumes from external recruiters or agencies. We only work with approved partners engaged directly by our Talent Acquisition team for specific searches. Unsolicited submissions will not be eligible for placement fees.

Qualifications Education Required Bachelors or better. Experience Required 3+ years of professional experience in data engineering, machine learning engineering, analytics engineering, or software development. Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

Salas O'Brien Seattle, Washington, USA Office

10202 5th Avenue NE, Suite 300, Seattle, United States, 98125

Similar Jobs

6 Minutes Ago
In-Office or Remote
124K-195K Annually
Expert/Leader
124K-195K Annually
Expert/Leader
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Enterprise solution seller responsible for driving new business and expansion across AMER and APAC. Develops strategic plans, exceeds bookings and OKR targets, closes complex six- and seven-figure SaaS transactions, builds CXO-level relationships, generates pipeline with sales and channel partners, presents forecasts, and monitors market and competitive shifts. Requires extensive enterprise cloud software sales experience and expertise in Strategic Portfolio Management, PPM, ERP, or CRM solutions.
Top Skills: Cloud-Based SoftwareCRMErpPpmSaaSStrategic Portfolio Management
6 Minutes Ago
In-Office or Remote
81K-128K Annually
Entry level
81K-128K Annually
Entry level
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Manage the full customer lifecycle for DX customers, including implementation, adoption, success planning, renewals, expansion, and executive engagement. Track account metrics, forecast renewals, resolve retention risks, identify growth opportunities, and align customer use cases with business goals. The role requires proactive collaboration across internal teams and four days per week onsite in Salt Lake City.
Top Skills: AtlassianDx Platform
6 Minutes Ago
In-Office or Remote
180K-283K Annually
Senior level
180K-283K Annually
Senior level
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Lead a team of 6–10 enterprise account executives, develop sales strategies, achieve revenue targets, manage key customer relationships, and drive high-performance culture. Responsibilities include coaching, recruiting, performance management, pipeline analysis, executive negotiations, cross-functional collaboration, and reporting to senior leadership.
Top Skills: Analytics ToolsCRMPipeline ManagementSaaS

What you need to know about the Seattle Tech Scene

Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.

Key Facts About Seattle Tech

  • Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Amazon, Microsoft, Meta, Google
  • Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
  • Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Madrona, Fuse, Tola, Maveron
  • Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account