Full stack AI product Software Engineer

Location: Intellias Meet your recruiter Carmen Beck carmen.beck@intellias.com https://www.linkedin.com... Vacancy details Software Engineering Fullstack AI Product Engineer Middle United States Office APPLY NOW REFER A FRIEND See the impact you make as an Applied AI Software Engineer delivering production‑ready solutions from day one. What project we have for you Our client is seeking an Applied AI Software Engineer to design, build, and deliver internal tools that improve the day-to-day effectiveness of engineering teams across requirements, validation, and UX/UI functions. The engineer will develop production-ready, AI-enabled applications that integrate existing models, LLM APIs, and AI services into practical business workflows. Typical solutions may include tools that generate engineering reports from structured inputs and prompts, or video-analysis workflows that identify activities in uploaded video, capture time-stamped events, and produce concise summaries. This is an execution-focused software engineering role, not an AI/ML research or model-development position. The successful candidate will use technologies such as Python, JavaScript/React, and AWS services to build reliable end-to-end pipelines, user-facing applications, and integrations that meet enterprise quality, security, and usability expectations. Working closely with engineers and cross-functional stakeholders, the candidate will help turn operational needs into maintainable AI-enabled tools and deliver them through established development practices. This is a full-time, fully onsite position in Raymond, Ohio, performed five days per week during standard business hours. What you will do 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. Develop maintainable backend services, APIs, data-processing logic, and automation primarily in Python; contribute to JavaScript/TypeScript and React-based user interfaces where needed. 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 with JavaScript or TypeScript and React for internal web applications. 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. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success. Skills AI AWS Python