Senior Data and AI Engineer

Evolent

. Lead the design, development, and deployment of complex, scalable, and maintainable software solutions .

Posted 10/15/2026full-timeRemote • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in software development, data engineering, and AI-assisted engineering, with a strong focus on designing scalable solutions and optimizing data pipelines. Proficient in collaborating with cross-functional teams to translate business needs into technical implementations while ensuring adherence to best practices and compliance standards.

Highest-signal resume keywords

Software Development ExperienceData Engineering TechnologiesAI-Assisted Development PlatformsCloud PlatformsDatabase Design and Optimization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

C#PythonData VaultDimensional ModelingSparkDatabricksSQLNoSQLMachine Learning Data PipelinesPrompt Engineering

Soft Skills

Problem-SolvingCommunication

Tools & Technologies

AzureAWSGCPGitHub CopilotCursorClaude Code

Certifications & Qualifications

Bachelor’s Degree in Computer ScienceMaster’s Degree in Software Engineering

Industry Keywords

Data GovernanceData QualityObservability PracticesAI-Enabled SolutionsResponsible AI Standards

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformNoSQLPythonSparkSQLVault

About the role

Key responsibilities & impact

Lead the design, development, and deployment of complex, scalable, and maintainable software solutions
Architect and implement high-performance data pipelines supporting critical business functions
Collaborate with product managers, UX designers, and engineers to translate business needs into technical solutions
Conduct code reviews and ensure adherence to best coding practices
Mentor and coach junior engineers
Improve the software development lifecycle through automation, testing, and CI/CD pipelines
Troubleshoot production issues and ensure service availability and reliability
Evaluate and integrate tools, frameworks, and technologies
Drive technical vision, architectural discussions, and long-term project planning
Apply AI-assisted engineering across requirements analysis, development, testing, debugging, documentation, and operational monitoring
Iterate with AI on solution design and architecture and produce design artifacts
Validate AI-generated outputs for correctness, security, maintainability, compliance, and business appropriateness
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 intellectual property, security, privacy, PHI handling, and Responsible AI standards

Requirements

What you’ll need

Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience
5+ years of professional software development experience
Proficiency in one or more programming languages, such as C# or Python, and relevant frameworks
Knowledge of cloud platforms such as Azure, AWS, or GCP
Experience with data engineering technologies such as Spark, Databricks, or Microsoft Fabric
Knowledge and experience with modern data engineering patterns, including Data Vault, dimensional modeling, data products, lakehouse architecture, feature flags, event-driven systems, and DAGs
Expertise in database design and optimization for SQL and NoSQL databases
Excellent problem-solving skills
Strong communication skills, including leading technical discussions, presenting to stakeholders, and writing detailed documentation
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
Experience in 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 internet over 10 Mbps at home
Government-issued photo ID submission and identity verification during interviews
Comprehensive background check
In-person I-9 verification
May be subject to drug screening prior to employment
AI tools prohibited during interviews

Benefits

Comp & perks

Comprehensive benefits, including health insurance benefits, for qualifying employees
Work/life balance
Flexible work arrangements
Autonomy to get things done