Artificial Intelligence Engineer

Key Responsibilities

AI Application Development & Architecture - 70%

• Design and build Claude-powered applications, AI assistants, agents, and automated workflows.
• Translate client business requirements into scalable AI solution architectures.
• Develop solutions using Claude APIs, tool use, structured outputs, prompt engineering, RAG, and agentic workflows.
• Integrate AI applications with client systems, APIs, databases, document repositories, and business platforms.
• Build prototypes and proofs of concept and transition successful solutions into production.
• Design secure approaches to authentication, permissions, data access, monitoring, and error handling.
• Test and optimize AI applications for accuracy, reliability, performance, and user experience.
• Apply responsible AI, privacy, security, and data-governance standards.
• Create technical documentation and reusable development patterns.

Client Consulting & Enablement - 30%

• Lead or participate in client discovery sessions to understand business challenges and requirements.
• Recommend practical AI solutions based on client needs and workflows.
• Present solution concepts, prototypes, and completed applications to technical and non-technical stakeholders.
• Lead client demonstrations, workshops, and training sessions.
• Train users on Claude-powered applications and effective AI practices.
• Gather client feedback and translate it into technical enhancements.
• Support solution implementation, adoption, and ongoing improvement.
• Act as a trusted technical advisor to client stakeholders.

Qualifications

• Experience developing AI-enabled applications, enterprise applications, or solution architectures.
• Hands-on experience with Claude and/or other LLM APIs.
• Strong understanding of LLM application architecture, including prompting, context management, tool calling, structured outputs, RAG, and agents.
• Strong development skills in Python, TypeScript, or similar technologies.
• Experience integrating applications with APIs, databases, cloud services, and enterprise systems.
• Understanding of application security, privacy, authentication, and data governance.
• Strong client-facing communication, presentation, and facilitation skills.
• Ability to translate business problems into practical technical solutions.
• Comfortable working directly with both technical and non-technical client stakeholders.

Preferred Qualifications

• Direct experience with the Anthropic API and Claude ecosystem.
• Experience with MCP (Model Context Protocol).
• Experience building AI agents and enterprise RAG solutions.
• Experience in consulting, professional services, or another client-facing technology environment.
• Experience delivering technical demonstrations, workshops, or end-user training.