AI Software Engineer

Akira Technologies• Rock Island, IL, US, IL

9d•$135,000 - $155,000•Remote

About The Position

Akira Technologies is seeking an experienced AI Software Engineer to design, develop, test, and deploy scalable, production-ready software applications incorporating artificial intelligence and automation technologies. The role combines strong software engineering fundamentals with hands-on integration of AI services and APIs, including OpenAI, into secure, cloud-native applications and operational workflows. The engineer will rapidly prototype AI-enabled solutions, evaluate emerging technologies, and turn successful prototypes into reliable production applications. The position works across the full software development lifecycle, building and integrating APIs, microservices, databases, and external services, while applying cloud-native development, containerization, orchestration, CI/CD, automated testing, and DevOps practices. The engineer collaborates with engineers, technical leads, customers, and stakeholders on technical solutions, architecture, design, code reviews, and process improvements. This is a fully remote position with occasional onsite meetings in Rock Island, Illinois. US citizenship is required, and the candidate must be eligible to obtain a security clearance. The stated salary range is $135,000 to $155,000. Akira offers medical, dental, and vision plan options, a 401(k) plan with employer match, paid time off and other leave, insurance benefits, and tuition, training, and certification reimbursement.

Requirements

Bachelor’s or master’s degree in Computer Science, Software Engineering, or a related technical field.
Strong proficiency in Go and Python, plus at least one additional modern programming language such as Java, C#, or Rust.
Hands-on experience developing and deploying AI-enabled applications, including integrating OpenAI or similar commercial AI platforms or APIs.
Experience with prompt engineering, AI automation, and workflow development.
Experience with AI/ML frameworks and automation platforms such as Power Automate, IBM UFT, or similar technologies.
Strong understanding of cloud-native application development, Docker, and Kubernetes.
Hands-on experience with DevOps practices and CI/CD pipelines.
Experience with distributed systems and microservices architectures.
Experience with SQL and NoSQL databases.
Strong problem-solving, communication, and collaboration skills.
Ability to work independently in a remote environment.
US citizenship and eligibility to obtain a DoD security clearance.

Nice To Haves

Experience with AWS, Azure, or Google Cloud Platform.
Experience with Infrastructure as Code tools such as Terraform or Ansible.
Experience implementing Retrieval-Augmented Generation solutions and working with vector databases or embedding technologies.
Familiarity with MLOps and AI operations, including monitoring, evaluation, deployment, and maintenance of AI-enabled applications.
Experience developing secure applications in federal, defense, or other highly regulated environments.
Familiarity with secure coding practices, application security, and cybersecurity principles.
Experience taking AI prototypes from proof of concept through production deployment.
Relevant certifications such as AWS Developer, Kubernetes CKA/CKAD, or Microsoft Power Automate RPA Developer.

Responsibilities

Design, develop, test, and deploy scalable applications using Go, Python, and other modern programming languages.
Integrate AI capabilities and commercial AI platforms and APIs, including OpenAI, into production applications and workflows.
Develop prompt-engineering strategies, AI automation workflows, and intelligent application features.
Prototype, evaluate, and iterate on emerging AI technologies and concepts to deliver minimum viable products.
Develop solutions that scale from prototypes to secure, reliable, production-ready applications.
Build and integrate APIs, microservices, databases, and external services for AI-enabled applications.
Apply cloud-native development practices, containerization, and orchestration using Docker and Kubernetes.
Implement and maintain CI/CD pipelines, automated testing, and DevOps practices.
Optimize applications for performance, scalability, reliability, security, and maintainability.
Collaborate with engineers, technical leads, customers, and stakeholders to define and implement technical solutions.
Participate in architecture, design, and code reviews and contribute to engineering standards and process improvements.
Stay current with emerging AI technologies, development frameworks, APIs, and industry best practices.