Engineer Jobs

About The Position

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience.
• Proficiency in one or more programming languages, such as C# or Python, and relevant frameworks.
• Strong understanding of software design principles, algorithms, and data structures.
• Knowledge of cloud platforms such as Azure, AWS, or GCP, and experience with data engineering technologies such as Spark, Databricks, or Microsoft Fabric.
• Knowledge and experience with modern data engineering patterns, such as Data Vault, dimensional modeling, data products, lakehouse architecture, feature flags, event-driven systems, and DAGs.
• Familiarity with Git or similar version control systems and collaborative coding workflows.
• Ability to write unit, integration, and end-to-end tests.
• Strong problem-solving skills and ability to work independently and as part of a team.
• Strong communication skills and ability to explain technical concepts to technical and non-technical stakeholders.
• Demonstrated experience using AI-assisted development platforms such as GitHub Copilot, Cursor, Claude Code, or similar tools to deliver production work.
• Strong prompt engineering skills and experience with AI-assisted testing and AI-enabled delivery practices.
• Experience with machine learning data pipelines, vector search technologies, document processing pipelines, or AI data preparation techniques.
• Working knowledge of data governance, lineage, quality, and observability practices supporting AI-enabled solutions.
• High-speed home internet over 10 Mbps.

Responsibilities

• Design, develop, test, and maintain software applications using modern programming languages and frameworks.
• Collaborate with product managers, designers, and engineers to translate requirements into technical specifications.
• Write clean, maintainable, efficient code that follows best practices and coding standards.
• Participate in code reviews to support code quality, functionality, and maintainability.
• Troubleshoot, debug, and resolve technical issues and bugs.
• Optimize applications for performance, scalability, and reliability.
• Contribute to continuous improvement of development processes, tools, and methodologies.
• Stay up to date with emerging technologies and industry trends and apply them to products and solutions.
• Apply AI-assisted engineering techniques across requirements analysis, pipeline and code development, testing, debugging, documentation, and operational monitoring.
• Iterate with AI on solution design and architecture, evaluate alternatives, revise architecture, and produce design artifacts for review.
• Validate AI-generated outputs for correctness, security, maintainability, compliance, and business appropriateness, including AI-assisted work by other engineers.
• Design and support data platforms and governed datasets for machine learning, analytics, and generative AI workloads.
• Contribute reusable prompts, skills, agents, engineering playbooks, and AI-assisted development patterns.
• Ensure AI usage complies with enterprise policies for intellectual property protection, security, privacy, PHI handling, and Responsible AI standards.

Benefits

• Comprehensive benefits, including health insurance benefits, for qualifying employees.
• Work/life balance and flexibility to suit work to employees’ lives.
• Autonomy to get work done.