Lead Applied AI Engineer

Lead full-stack development and enhancement of AI-powered products, focusing on high-quality, cost-efficient, and outcome-driven engineering solutions.

Own end-to-end product engineering including architecture, design, coding, testing, integration, deployment, and ongoing maintenance, aligning with enterprise standards and business goals.

Mentor and guide engineering teams, promote engineering excellence, and collaborate cross-functionally to deliver scalable, lean, and customer-centric AI and agentic solutions.

Bachelor's degree in computer science, software engineering, data science, machine learning, or related discipline.

6+ years of full-stack software engineering experience with frameworks and languages such as Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, and AI/ML frameworks like PyTorch or TensorFlow.

3+ years of hands-on experience developing AI/ML and agentic applications, including GenAI with LLM integrations (OpenAI, Anthropic, or open-source), RAG pipelines, prompt engineering, vector databases, and AI agent orchestration.

3+ years of cloud-native engineering experience on Azure, AWS, or GCP including their AI/ML services; plus 1+ years leading engineering standards, mentoring teams, and managing code quality and cost efficiency.

Experienced technical leader with strong expertise in applied AI and full-stack engineering, able to deliver rapid, scalable solutions focused on customer and business outcomes.

Proficient in integrating and operationalizing AI/GenAI capabilities within products, with a firm grasp on cloud infrastructure cost and FinOps accountability.

Skilled in cross-functional collaboration and mentoring, with a track record of maintaining engineering standards and aligning technical work to strategic business goals.