Mind Computing is seeking an AI Engineer for designing, developing, and deploying AI-enabled applications that improve healthcare workflows. The engineer will work within a collaborative development environment to build scalable systems and integrate modern AI capabilities into cloud-based platforms.
Responsibilities:
- Design and develop AI-enabled services and applications using Python and modern cloud-native architectures
- Integrate large language models (LLMs) and AI APIs into production systems to enable intelligent automation and decision support
- Build scalable microservices and APIs that support AI-driven workflows and data processing
- Develop pipelines and services that process structured and unstructured data to support intelligent applications
- Implement secure APIs and event-driven architectures that support data integration and AI-enabled services
- Optimize AI-powered applications for performance, reliability, and scalability in cloud environments
- Collaborate with engineers, product teams, and stakeholders to translate AI concepts into deployable solutions
- Take on additional tasks and responsibilities as needed to support team objectives and ensure the success of the project
Requirements:
- Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, or a related technical discipline
- 3–6 years of professional software engineering experience for mid-level candidates, or 6+ years for senior candidates, with hands-on experience developing or deploying AI-enabled applications
- Strong programming skills in Python for developing AI-enabled applications, APIs, and microservices
- Hands-on experience integrating Large Language Models (LLMs) or AI APIs (such as OpenAI, Bedrock, Claude, or similar) into production environments
- Experience developing cloud-native applications using platforms such as AWS, Azure, or Google Cloud
- Experience building REST APIs, microservices, and distributed systems that support scalable AI workflows
- Familiarity with AI development frameworks and tools such as LangChain, Hugging Face, vector databases, or similar technologies
- Experience working with modern development practices including Git, CI/CD pipelines, containerization, and DevOps workflows
- Strong analytical and problem-solving abilities with the ability to troubleshoot complex systems
- Effective communication and collaboration skills within cross-functional engineering teams
- Strong attention to detail and commitment to building reliable, high-quality software solutions
- Experience deploying AI solutions within regulated environments such as healthcare or government systems
- Familiarity with FHIR, HL7, or healthcare interoperability standards
- Experience with LLM orchestration frameworks or agent-based architecture
- Experience with containerization technologies such as Docker or Kubernetes
- Experience working with the Department of Veterans Affairs (VA)
- Ability to obtain a U.S. government clearance