Solution Engineer (Data & AI)

Location: Remote, Brentwood, Tennessee, United States

Company

hirify.global is a technology services company delivering professional and managed services across hybrid cloud infrastructure, networking, cybersecurity, data and AI, autonomous operations, and enterprise service management.

What you will do

• Design, build, and maintain reliable batch and streaming data pipelines using lakehouse architecture, data contracts, schema evolution, quality checks, testing, and monitoring.
• Design analytical data models, analyze data quality and business requirements, and apply governance practices that keep data secure, traceable, and discoverable.
• Build, train, evaluate, deploy, and operate machine learning, generative AI, LLM-based, and agentic applications with production reliability, observability, and maintainability.
• Build CI/CD pipelines for code, data, and models; manage cloud resources through infrastructure as code; and implement versioning, deployment, monitoring, drift detection, and retraining.
• Use agentic coding tools such as Claude Code for development, testing, documentation, and refactoring while reviewing and validating all generated code.
• Depending on the path, deliver fixed-price client projects across Azure, AWS, and GCP or integrate and model internal CRM, PSA, finance, ERP, and HR data in Azure Databricks to support analytics and quote-to-cash automation.

Requirements

• 4+ years in software and platform engineering, including meaningful experience on a collaborative software development team.
• Hands-on experience building production data and ML solutions in the cloud, with strong demonstrable Databricks experience in production environments.
• Practical experience using agentic coding tools, including examples of how they changed the development workflow.
• Strong proficiency in Python and SQL, with solid knowledge of Git workflows, code review, unit and integration testing, modular design, containerization, environment management, and automated deployment.
• Hands-on experience with CI/CD tooling and infrastructure as code.
• Working knowledge of Azure, AWS, and GCP, with deep hands-on experience in at least one; understanding of cloud storage, identity, networking, security, and native data and AI services.
• Deep hands-on Databricks experience across data engineering, governance, and ML/AI, including deployment and management using software engineering and DevOps practices.
• Ability to design scalable batch and streaming pipelines, apply dimensional and modern lakehouse modelling patterns, and use data quality frameworks, testing, and observability.
• Experience building, evaluating, and deploying ML models; generative AI patterns such as retrieval-augmented generation, agents, and LLM evaluation; and full-lifecycle MLOps.
• Ability to decompose work, write clear specifications, manage context for AI agents, and apply disciplined judgment when reviewing and testing AI-assisted output.

Culture & Benefits

• Remote work within the Brentwood, Tennessee, United States location designation.
• Engineering practices emphasize version control, automated testing, CI/CD, infrastructure as code, observability, code reviews, documentation, and disciplined software delivery.
• Client delivery work includes technical discovery, workshops, demos, knowledge transfer, and collaboration with Architects and Engineering Managers.
• Engineers may move between client delivery and internal data and analytics paths as priorities and interests evolve.
• Inclusive equal opportunity work environment with accommodations available throughout the interview process and beyond.