Artificial Intelligence Engineer

SolomonEdwards; Raymond (OH); On-site; USD 120,000 - 180,000; Full time

Job summary

SolomonEdwards is seeking an on-site AI-enabled software engineer in Raymond, Ohio to collaborate with cross-functional teams. The role focuses on applying existing AI capabilities, building data-processing pipelines, and delivering production-grade tools that improve engineering productivity and workflows.

You will design and implement back-end services, leverage AWS/GCP, and ensure secure, maintainable solutions with strong documentation and stakeholder communication.

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, a related technical field, or equivalent practical experience.
• Two or more years of professional experience in software engineering, including building, delivering, and maintaining production-quality applications, services, or internal tools.
• Strong proficiency in Python, including writing clean, maintainable, testable code and debugging software issues.
• Hands-on experience integrating existing AI capabilities into software solutions, such as LLM APIs, managed AI platforms, computer-vision services, or AI libraries.
• Experience building backend services, APIs, data-processing workflows, automation, or system integrations.
• Experience developing and deploying cloud-based applications using AWS, Azure, GCP, or similar platforms.
• Ability to evaluate technical options and recommend practical tools, frameworks, and architecture approaches based on user needs, security, maintainability, delivery timeline, and existing team capabilities.
• Ability to work effectively within established architecture, coding standards, version-control practices, and software-development processes with minimal onboarding.
• Experience collaborating with engineering and non-engineering stakeholders to translate operational needs into practical technical solutions.
• Strong written and verbal communication skills, including the ability to document technical decisions, communicate trade-offs, and clearly report delivery status, risks, and dependencies.
• Ability to work full-time, onsite in Raymond, Ohio, five days per week during standard business hours.

Responsibilities

• Engage with requirements, validation, UX/UI, and engineering stakeholders to understand workflows, pain points, and opportunities for automation or AI-enabled improvement.
• Elicit and clarify ambiguous business needs; translate into problem statements, user journeys, functional requirements, acceptance criteria, and technical designs.
• Assess solution options and recommend architecture, AI services, cloud platforms, and implementation approaches based on value, feasibility, security, maintainability, cost, and timeline.
• Design, develop, test, deploy, and maintain internal AI-enabled software tools that improve engineering productivity and workflows.
• Build end-to-end applications and pipelines processing engineering artifacts and data to produce reports, summaries, classifications, etc.
• Integrate and orchestrate AI capabilities including LLM APIs and computer-vision tools; focus on applying existing models rather than training from scratch.
• Create prototypes to validate feasibility and value; evolve concepts into production solutions.
• Establish AI-output evaluation and validation methods, tests, error handling, observability, logging, and human reviews where needed.
• Collaborate with cross-functional teams throughout discovery, implementation, testing, rollout, and continuous improvement; communicate scope, decisions, and risks clearly.
• Participate in technical design reviews, code reviews, testing, troubleshooting, release activities, and ongoing support; maintain documentation.
• Perform assigned duties independently and timely; adhere to policies, security expectations, and quality requirements.

Skills

Python

AI integration

Cloud experience

Backend services

Data pipelines

DevOps

Communication

Education

Bachelor’s degree in CS/Engineering

Tools

AWS

Docker

CI/CD

GCP

LLM APIs

Job description

• Independently engage with requirements, validation, UX/UI, and other engineering stakeholders to understand current workflows, pain points, process gaps, and opportunities for automation or AI-enabled improvement.


• Elicit and clarify ambiguous business needs; translate them into practical problem statements, user journeys, functional requirements, acceptance criteria, technical designs, and incremental delivery plans.


• Assess solution options and independently recommend appropriate architecture, AI services, cloud platforms, frameworks, and implementation approaches based on user value, technical feasibility, security, maintainability, cost, delivery timeline, and the existing engineering environment.


• Design, develop, test, deploy, and maintain internal AI-enabled software tools that improve engineering productivity and operational workflows.


• Build end-to-end applications and pipelines that process engineering artifacts and data—including documents, spreadsheets, structured data, images, and video and produce useful outputs such as reports, summaries, classifications, etc.


• Integrate and orchestrate existing AI capabilities, including LLM APIs, managed AI services, computer-vision tools, and supporting libraries. This role focuses on applying existing models and services rather than training or developing foundational AI/ML models.


• Create prototypes or proof-of-concepts when useful to validate technical feasibility and user value, then evolve validated concepts into secure, reliable, supportable production solutions.


• Establish appropriate AI-output evaluation and validation methods, including test cases, structured output controls, error handling, observability, logging, and human review where the workflow requires it.


• Collaborate closely with cross-functional teams throughout discovery, implementation, testing, rollout, and continuous improvement; communicate scope, decisions, trade-offs, status, risks, dependencies, and technical limitations clearly.


• Participate in technical design reviews, code reviews, testing, troubleshooting, release activities, and ongoing support; maintain clear technical documentation, user guidance, and required project records.


• Perform assigned duties independently and in a timely, accurate, and professional manner.


• Adhere to organizational policies, procedures, security expectations, and applicable quality and safety requirements.

What you need for this

• Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, a related technical field, or equivalent practical experience.


• Two or more years of professional experience in software engineering, including building, delivering, and maintaining production-quality applications, services, or internal tools.


• Strong proficiency in Python, including writing clean, maintainable, testable code and debugging software issues.


• Hands-on experience integrating existing AI capabilities into software solutions, such as LLM APIs, managed AI platforms, computer-vision services, or AI libraries.


• Experience building backend services, APIs, data-processing workflows, automation, or system integrations.


• Experience developing and deploying cloud-based applications using AWS, Azure, GCP, or similar platforms.


• Ability to evaluate technical options and recommend practical tools, frameworks, and architecture approaches based on user needs, security, maintainability, delivery timeline, and existing team capabilities.


• Ability to work effectively within established architecture, coding standards, version-control practices, and software-development processes with minimal onboarding.


• Experience collaborating with engineering and non-engineering stakeholders to translate operational needs into practical technical solutions.


• Strong written and verbal communication skills, including the ability to document technical decisions, communicate trade-offs, and clearly report delivery status, risks, and dependencies.


• Ability to work full-time, onsite in Raymond, Ohio, five days per week during standard business hours.

Preferred Qualifications

• Experience with AWS services; the current team primarily uses AWS, with services such as S3, Lambda, EC2, Bedrock, IAM, CloudWatch, and API Gateway potentially relevant depending on the solution.


• Experience applying generative AI to business or engineering workflows.


• Familiarity with prompt engineering, structured outputs, model evaluation, retrieval-augmented generation (RAG), and validation methods for AI-generated results.


• Experience working with enterprise engineering artifacts and data sources, such as Excel files, documents, video, databases, or structured and unstructured data.


• Familiarity with Docker, CI/CD pipelines, automated testing, infrastructure-as-code, application monitoring, and production deployment practices.


• Familiarity with secure development, identity and access management, data privacy, logging, and responsible-AI practices.


• Experience working in agile or another structured enterprise software-development environment.