RESPONSIBILITIES
Kforce's client is seeking an experienced Full Stack AI Engineer to support the development of innovative, AI-powered applications and solutions.
The ideal candidate is a self-motivated, hands-on engineer who thrives in a fast-paced environment and can independently deliver high-quality, production-ready solutions.
This role will last 6 months, with potential for conversion to full-time employment.
This position offers the opportunity to contribute to high-priority AI initiatives, leveraging modern full stack technologies, generative AI capabilities, and cloud infrastructure.
Key Responsibilities
- Design, develop, and deploy AI-powered applications and features using model APIs
- Build and maintain full stack applications using Python, JavaScript, TypeScript, React, HTML, and CSS
- Explore and implement AI agents, agentic frameworks, and tool-calling capabilities
- Develop effective prompt and context designs, structured outputs, and solutions grounded in trusted information
- Integrate retrieval-augmented generation (RAG), semantic search, and knowledge bases into AI applications
- Implement automated testing, AI evaluation methodologies, and production-quality engineering practices
- Develop and maintain scalable cloud-based solutions leveraging AWS services
- Support infrastructure automation, CI/CD pipelines, and DevOps best practices
- Monitor, troubleshoot, and optimize applications using logs, metrics, and distributed tracing
- Incorporate security, data privacy, access controls, and responsible AI principles throughout the development lifecycle
- Collaborate with engineering teams and stakeholders to deliver reliable, high-quality solutions
REQUIREMENTS
- Hands-on experience developing AI-powered applications or features using model APIs
- Strong programming experience with Python, JavaScript, and TypeScript
- Experience developing modern web applications using React, HTML, and CSS
- Understanding of prompt engineering, context design, structured outputs, and AI response grounding
- Familiarity with AI agents, agentic frameworks, and tool calling
- Knowledge of modern software engineering practices, automated testing, and application troubleshooting
- Experience working with cloud technologies and CI/CD processes
- Strong problem-solving abilities, communication skills, and a demonstrated ability to work independently
- Ability to quickly learn new technologies and deliver high-quality solutions in a collaborative engineering environment
Preferred Qualifications
- Experience with retrieval-augmented generation (RAG), Model Context Protocol (MCP), semantic search, and knowledge bases
- Familiarity with AI evaluation frameworks and testing methodologies
- Experience with AWS services, including Bedrock, AgentCore, ECS, EKS, and MSK
- Experience with Terraform or other infrastructure-as-code technologies
- Familiarity with observability tools, including logging, metrics, and tracing
- Understanding of AI security considerations, including prompt injection, data privacy, and access management
Additional Information
Candidates are not expected to have experience with every technology listed.
Equivalent technical experience, strong engineering fundamentals, and a demonstrated ability to learn and adapt to emerging AI technologies are highly valued.