AI Engineer - Automation/Robotics 3

Description

Join our dynamic team dedicated to revolutionizing data-center telemetry by automating manual workflows. Our mission is to enhance operational efficiency through scalable onboarding processes.

Typical Day in the Role

As a key member of our team, you will:

• Design and implement automation pipelines to streamline operational, validation, and engineering workflows.
• Gather and analyze requirements from engineering, operations, and program stakeholders, translating ambiguous manual processes into clear technical designs.
• Integrate data from internal systems, databases, work tracking tools, spreadsheets, and document repositories.
• Develop software solutions that ingest, normalize, validate, and report on operational and telemetry-related data.
• Create reusable validation rules, checks, and reporting modules that can scale across multiple workflows.
• Automate manual review processes while preserving appropriate human-in-the-loop approval gates.
• Prepare technical specifications, test plans, and implementation documentation.
• Modify and improve existing automation tools to meet new standards, requirements, and operating models.
• Conduct unit testing, integration testing, and post-implementation validation.
• Troubleshoot issues across new and legacy systems, identify root causes, and implement durable fixes.
• Partner with internal stakeholders to ensure automation outputs are actionable, trusted, and operationally usable.

Candidate Requirements

We are looking for a talented software engineer or automation engineer with a passion for building backend tools, data pipelines, workflow automation, or internal engineering systems.

• Bachelor's degree in computer science, computer engineering, data engineering, or a related technical field is required.
• 5-7 years of software engineering or automation engineering experience is preferred.
• Strong programming experience, preferably with Python, PowerShell, C#, or similar automation-friendly languages.
• Experience integrating with APIs, databases, work item systems, files, and enterprise data sources.
• Ability to work with structured and semi-structured data such as SQL/KQL query results, spreadsheets, JSON, CSV, and logs.
• Experience with validation frameworks, data quality checks, automated reporting, or operational readiness tooling.
• Strong troubleshooting skills across both new and legacy production systems.
• Experience writing unit tests, test data, and validation plans for automation workflows.
• Ability to operate in ambiguous environments and convert manual business processes into reliable software systems.

Preferred Skills

• Experience with cloud or enterprise data platforms.
• Familiarity with telemetry systems, operational monitoring, or industrial/IoT data workflows.
• Experience with Azure DevOps, GitHub, CI/CD pipelines, or similar engineering lifecycle tools.
• Experience building tools used by engineering or operations teams.
• Strong communication skills and the ability to document technical designs for non-specialist stakeholders.

What is the Ideal Background of a Candidate for this Role?

The ideal candidate is a software engineer or automation engineer with experience building backend tools, data pipelines, workflow automation, or internal engineering systems. They should be comfortable turning ambiguous operational processes into reliable software, integrating multiple data sources, and working with structured and semi-structured data such as SQL/KQL results, spreadsheets, CSV, JSON, logs, and APIs. Strong Python, PowerShell, C#, or similar automation-focused programming experience is preferred, along with good troubleshooting, testing, and documentation habits.

Top 3 Must-Have HARD Skills & Years of Experience for Each

• Software engineering with Python, C#, PowerShell, or similar automation/backend language: 5 years
• Building automation pipelines, backend tools, data workflows, or system integrations: 3 years
• Working with structured/semi-structured data sources such as SQL/KQL, APIs, CSV, JSON, logs, or spreadsheets: 3 years

How Will Contractor Performance Be Measured?

Performance will be measured by the contractor's ability to deliver reliable automation that reduces manual effort and improves workflow quality. Key measures include completed automation milestones, successful integration with required data sources, accuracy of validation/reporting outputs, reduction in manual processing time, quality of code and tests, responsiveness to stakeholder feedback, clear documentation, and the ability to troubleshoot and maintain workflows after implementation.