AI Solutions Engineer

Gravity IT Resources; United States; On-site; USD 110,000 - 160,000; Full time

Job summary

Gravity IT Resources is seeking an AI Solutions Engineer to transform approved business concepts into secure, scalable production tools. You will design, build, deploy, and continuously improve internal applications, AI agents, automations, and data solutions, partnering with executives and operations teams to deliver measurable impact.

You will translate real-world needs into practical software, establish architecture and security standards, and drive integration across cloud, data sources, and

Qualifications

• 3–6+ years of hands-on software engineering, data engineering, or related experience.
• Advanced experience with AI-assisted and agentic software-development workflows, including large language model APIs and orchestration tools.
• Proficiency in modern programming languages used for application development, automation, data processing, and systems integration.
• Advanced SQL skills and database design fundamentals.
• Experience with cloud infrastructure, CI/CD, deployment, observability, and production monitoring.
• Proven ability to take a solution from concept to production and support.
• Bachelor’s degree in CS/Software Engineering or equivalent portfolio of verified apps.

Responsibilities

• Translate approved concepts into production-ready applications, AI agents, automations, and data solutions.
• Lead the design, development, testing, deployment, and ongoing improvements of internal software solutions.
• Build integrations across cloud infra, databases, and business apps.
• Develop workflows for unstructured data from operational documents.
• Establish source control, code reviews, testing, and deployment practices.
• Implement monitoring, logging, alerts, and recovery processes.
• Provide clear technical docs, user guidance, and training materials.

Skills

Strong communication

Analytical thinking

Collaboration

Problem solving

Education

Bachelor's degree in CS/CE/IS

Tools

LLM APIs

Agent frameworks

Orchestration tools

Cloud services

Job description

Term: Direct Hire

Position Overview

A growing national organization is seeking an AI Solutions Engineer to turn approved business concepts into secure, reliable, and scalable production solutions. Working closely with executive leadership and operational teams, this individual will lead the technical design, development, integration, deployment, and continuous improvement of internal applications, AI agents, automations, and data solutions.

The AI Solutions Engineer will translate real-world needs from estimating, project management, field operations, and other business functions into practical tools that improve speed, accuracy, visibility, and execution. This person will also establish strong architecture, documentation, security, and reliability standards that enable the organization to expand its technology capabilities without creating unnecessary complexity or long-term technical risk.

Scope of Responsibility

• Develop and deploy approved internal applications, AI agents, automations, integrations, and data solutions.
• Establish software architecture, technical standards, code-quality expectations, documentation, testing, and deployment practices.
• Integrate solutions across cloud infrastructure, databases, business systems, data sources, and knowledge-management platforms.
• Maintain application reliability, monitoring, error management, performance tracking, security, and ongoing technical support.
• Automate the capture, organization, and processing of operational documents, workflows, and unstructured data.
• Evaluate emerging technologies and technical approaches that support the organization’s technology roadmap.

Key Outcomes

• Approved technology concepts consistently deployed into production.
• Reliable, monitored applications with minimal downtime and timely error resolution.
• Consistent architecture, security, and development standards across deployed solutions.
• Clean, documented, and maintainable codebases.
• Measurable improvements in operational speed, accuracy, visibility, and manual-effort reduction.

Core Responsibilities

• Translate approved concepts, demonstrations, and wireframes into secure, reliable, and production-ready applications, AI agents, automations, and data solutions.
• Lead the technical design, development, testing, deployment, and continuous improvement of internal software solutions.
• Build integrations across cloud infrastructure, databases, business applications, data sources, and knowledge-management platforms.
• Develop workflows that capture, organize, extract, and process information from operational documents and other forms of unstructured data.
• Establish and maintain source-control, code-review, documentation, testing, deployment, and software-architecture practices.
• Implement application monitoring, error logging, alerting, performance tracking, and recovery processes.
• Maintain clean, secure, supportable codebases that can be effectively managed, extended, and transferred to other team members.
• Partner with project managers, estimators, field supervisors, and other business users to understand operational needs, gather feedback, and prioritize improvements.
• Create clear technical documentation, user guidance, and brief training materials to support adoption and ongoing maintenance.
• Evaluate emerging technologies, development approaches, and automation opportunities, and recommend priorities to organizational leadership.
• Ensure solutions comply with established security, privacy, architecture, and technology-governance standards.

Authority and Decision-Making

• Own day-to-day technical design, development, and implementation decisions for approved initiatives within established business, security, budget, and governance parameters.
• Recommend architecture, development approaches, tools, libraries, and integration methods based on scalability, reliability, maintainability, cost, and business fit.
• Prioritize and sequence technical work according to the approved technology roadmap and established business priorities.
• Define appropriate standards for source control, testing, documentation, deployment, monitoring, and ongoing application support.
• Collaborate with business stakeholders to define requirements, evaluate tradeoffs, and recommend practical solutions.
• Escalate material decisions involving security, data privacy, architecture risk, significant cost, external vendors, or major changes to enterprise systems.
• Contribute to new business initiatives and the broader technology roadmap while working within established executive approval processes.

Required Qualifications

• Three to six or more years of hands-on software engineering, data engineering, systems integration, or related experience.
• Advanced experience with AI-assisted and agentic software-development workflows, including large language model APIs, agent frameworks, orchestration tools, and modern coding assistants.
• Proficiency in modern programming languages used for application development, automation, data processing, and systems integration.
• Advanced SQL skills, including complex queries, schema design, database integration, and data-modeling fundamentals.
• Practical experience with cloud infrastructure, databases, source control, CI/CD pipelines, application deployment, API integrations, observability, and production monitoring.
• Experience applying software architecture, security, testing, documentation, and code-quality practices to production applications.
• Proven ability to independently move a solution from concept or prototype through production deployment and ongoing support.
• Strong communication skills with the ability to translate operational needs into practical technical solutions.
• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related field, or an equivalent portfolio of verified applications, integrations, automations, or AI solutions that have been built and deployed.

Preferred Qualifications

• Experience supporting construction management, specialty contracting, electrical, mechanical, HVAC, warehouse automation, logistics, or field-service operations.
• Experience working directly with operational and executive stakeholders in a growing organization.
• Familiarity with document extraction, knowledge-management platforms, unstructured data, and workflow automation.
• Experience creating internal applications or AI tools used by both office-based and field-based teams.

Success Metrics

• Number and quality of approved solutions successfully deployed to production.
• Application reliability, uptime, and speed of error resolution.
• Adherence to architecture, security, documentation, and code-quality standards.
• User adoption of deployed tools across field and office teams.
• Measurable operational impact, including time savings, error reduction, improved accuracy, and increased throughput.

Role Impact

This role directly influences operational efficiency, execution speed, and the organization’s ability to scale its technology capabilities. By turning approved concepts into secure, reliable, and maintainable production solutions, the AI Solutions Engineer will reduce manual effort, improve decision-making, and deliver practical tools that support both field and office teams.