Lead Applied AI Engineer II

Role Overview: As a Lead Applied AI Engineer II, you will actively engage in your engineering craft, taking a hands-on approach to building and enhancing high-visibility, full-stack products that serve the business and its users. Your expertise will be pivotal in delighting customers and users, while driving tangible value across Deloitte’s product and AI investments. You will leverage your extensive engineering craftsmanship and advanced proficiency across full-stack software engineering and modern frameworks—together with applied AI fluency that lets you build GenAI and agentic capabilities directly into the products you deliver—consistently demonstrating your exemplary track record in delivering high-quality, outcome-focused solutions. The ideal candidate will be a role-model leader and mentor, collaborating with cross-functional teams to design, build, and ship products end to end, from concept through production.

Key Responsibilities:

• Outcome-Driven Accountability: Embrace and drive a culture of accountability for customer and business outcomes—and for the cost of achieving them. Develop engineering solutions that solve complex problems with valuable outcomes, ensuring high-quality, lean designs and implementations, and owning the inference, token, and cloud cost of what you build.
• Technical Leadership and Advocacy: Serve as the technical advocate for products, ensuring code integrity, feasibility, and alignment with business and customer goals. Lead requirement analysis, low-level architecture and component design, development, testing, integrations, and support.
• Engineering Craftsmanship: Maintain accountability for the integrity of architecture and technical stack to the enterprise standards and strategy. Manage dependencies, code design, implementation, quality, data, and ongoing maintenance and operations. Stay hands-on, self-driven, and continuously learn new approaches, languages, and frameworks. Create technical specifications, and write high-quality, supportable, scalable code and review code of other engineers, mentoring them, to ensure all quality KPIs are met or exceeded. Demonstrate collaborative skills to work effectively with diverse teams.
• Customer-Centric Engineering: Develop lean engineering solutions through rapid, inexpensive experimentation to solve customer needs. Engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time.
• Incremental and Iterative Delivery: Adopt a mindset that favors action and evidence over extensive planning. Utilize a leaning-forward approach to navigate complexity and uncertainty, delivering lean, supportable, and maintainable solutions.
• Cross-Functional Collaboration and Integration: Work collaboratively with empowered, cross-functional teams including product management, experience, and delivery. Integrate diverse perspectives to make well-informed decisions that balance feasibility, viability, usability, and value. Foster a collaborative environment that enhances team synergy and innovation.
• Advanced Technical Proficiency: Possess deep expertise in modern software engineering practices and principles, including AI and Agentic SSDLC to deliver daily product deployments using full automation from discovery to production to operations with all quality checks through SSDLC lifecycle. Be a role model, leveraging these techniques to optimize solutioning and product delivery. Demonstrate strong understanding of the full lifecycle product development, focusing on continuous improvement and learning.
• Domain Expertise: Quickly acquire domain-specific knowledge relevant to the business or product. Translate business/user needs, architectures, and UX/UI designs into technical specifications and code. Be a valuable, flexible, and dedicated team member, suppo