Mind Computing is seeking an AI Engineer for designing, developing, and deploying AI-enabled applications that improve healthcare workflows, automate complex processes, and support data-driven decision-making. The engineer will work within a collaborative development environment to build scalable systems and integrate modern AI capabilities into cloud-based platforms.
The ideal candidate is a hands-on engineer with experience building AI-driven services, integrating large language models, and developing secure, scalable applications that support mission-critical systems.
The candidate must reside within the continental US.
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.
Additional Qualifications
- 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.
Benefits
- Medical/Dental/Vision
- 401k with Employer Match
- PTO + Federal Holidays
- Corporate Laptop
- Training Opportunities
Note: Selected candidates will be required to complete fingerprinting at a government facility and undergo a background check as part of the hiring process.
Mind Computing is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, or protected veteran status.
At this time, we are unable to offer sponsorship.
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