Ai Engineer

AI Engineer Overview

• The AI Engineer will lead structured discovery sessions to assess workflows and technology environments, architecting innovative AI solutions.
• Collaborate with cross-functional teams to design scalable AI solutions tailored to business needs and technical constraints.
• Develop prototypes using advanced AI/ML tools, LLM APIs, and low-code platforms to demonstrate feasibility and business value.
• Translate validated use cases into production-ready specifications and scalable modules for implementation.
• Serve as the primary intake point for AI-related opportunities, ensuring alignment with organizational goals.
• Partner with engineering teams to ensure clarity and precision in requirement handoffs during solution development.
• Define success criteria and performance expectations for AI solutions, supporting continuous improvement initiatives.
• Collaborate with leadership and sales teams to evaluate the feasibility and fit of new AI opportunities.
• Monitor alignment between designed solutions and delivered outcomes to ensure optimal results.

AI Engineer Key Responsibilities & Duties

• Lead discovery sessions to assess workflows and technology environments for AI solution development.
• Architect end-to-end AI solutions integrating people, processes, and technology components.
• Develop prototypes using AI/ML tools, LLM APIs, and low-code platforms independently.
• Design and execute proof-of-concept models to demonstrate feasibility and business value.
• Translate validated use cases into scalable modules and detailed production specifications.
• Collaborate with engineering teams to ensure clarity and precision in requirement handoffs.
• Define success criteria and technical constraints for AI solutions, supporting continuous improvement.
• Evaluate feasibility and fit of new opportunities in collaboration with sales and leadership teams.
• Monitor alignment between designed solutions and delivered outcomes to ensure optimal results.

AI Engineer Job Requirements

• Bachelor’s degree in Computer Science, Engineering, Business, or a related field (Master’s preferred).
• 8–12+ years of experience in solutions architecture, product strategy, or technical consulting.
• Hands-on experience with AI/ML technologies, Large Language Models (LLMs), and automation tools.
• Proven ability to prototype and validate complex technical solutions independently.
• Strong stakeholder management skills with the ability to influence cross-functional teams.
• Deep understanding of insurance industry workflows or related complex business environments.
• High level of autonomy and comfort navigating ambiguity in an innovation-focused role.
• Experience in client-facing solution design and end-to-end architecture development.
• Preferred certifications in AI/ML technologies or related fields are advantageous.