Lead Applied AI Engineer II

Deloitte’s Honolulu team seeks a hands-on Lead Applied AI Engineer II to deliver AI-powered software across high-visibility projects. This onsite role blends technical leadership, cross-functional collaboration, and practical engineering craft to translate AI concepts into production-ready solutions that drive measurable outcomes for clients and the business. The position offers a competitive annual salary range of USD 118,700 to 243,700.

Responsibilities

• Outcome-driven accountability: champion customer and business outcomes by designing lean, high-quality engineering solutions that solve complex problems and deliver valuable results.
• Technical leadership and advocacy: act as the technical advocate for products, ensuring code integrity and alignment with goals; lead requirement analysis, low-level architecture, component design, development, testing, integrations, and post-delivery support.
• Engineering craftsmanship: uphold architecture and tech-stack integrity to enterprise standards; manage dependencies, design quality, data handling, and ongoing maintenance; stay hands-on, learn new approaches, create technical specifications, write and review scalable code, and mentor peers.
• Customer-centric engineering: develop lean solutions through rapid experimentation to meet 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: favor action and evidence over extensive planning; navigate complexity with a forward-leaning approach to deliver lean, maintainable solutions.
• Cross-functional collaboration and integration: work with product management, experience, and delivery teams; integrate diverse perspectives to balance feasibility, viability, usability, and value, fostering collaboration and innovation.
• Advanced technical proficiency: bring deep expertise in modern software engineering practices, including AI and agentic SDLC to enable daily product deployments with end-to-end automation and quality checks throughout the lifecycle; model best practices to optimize solutioning and delivery.
• Domain expertise: quickly acquire relevant domain knowledge and translate business needs, architectures, and UX/UI designs into technical specifications and code; be a flexible, quality-focused teammate focused on tech debt payoff.
• Effective communication and influence: articulate complex technical concepts clearly, influence teammates and product teams with evidence-based trade-offs, and craft narratives that align technical solutions with business goals.
• Engagement and collaborative co-creation: collaborate with product engineering teams at all levels, including customers as needed; build constructive relationships that promote co-creation and shared momentum toward product goals, aligning diverse perspectives to reach feasible solutions.

Requirements

• Bachelor’s degree in computer science, software engineering, data science, machine learning, or a related field.
• 6+ years of experience with most of the following: Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, plus unit testing frameworks.
• 3+ years building AI/ML applications, with hands-on GenAI experience across LLM integration (OpenAI, Anthropic, or open-source models), RAG pipelines, prompt engineering, and vector databases.
• 3+ years of cloud-native engineering using FaaS, PaaS, or micro-services on Azure, AWS, or GCP, including AI/ML services such as Azure OpenAI, AWS Bedrock, or Vertex AI.
• 1+ year establishing engineering standards, including actively leading, mentoring, and guiding team members in adopting and improving these standards.
• Prior software engineering experience with Business Context Diagrams, sequence/activity/state/entity relationship/data flow diagrams, OOP/OOD, data structures, algorithms, code instrumentation, and AI-augmented spec-driven development.
• Experience with XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, MLflow and agentic AI frameworks (e.g., LangFuse, LangSmith, or equivalent multi-agent orchestration tools) to deliver high-quality products rapidly.

Technologies

• Angular
• React
• NodeJS
• Python
• C#
• .NET
• Java
• SQL/NoSQL
• PyTorch
• TensorFlow
• LangChain
• LangGraph
• OpenAI
• Anthropic
• LangFuse
• LangSmith
• MLflow
• Azure
• AWS
• GCP
• Vertex AI
• Azure OpenAI
• AWS Bedrock

Benefits

• Discretionary annual incentive program

Other

• Ability to travel up to 10 percent on average, depending on work and product delivery needs
• Limited immigration sponsorship may be available