Lead Applied AI Engineer II

The Lead Applied AI Engineer II role at Deloitte focuses on hands-on, outcome-focused engineering across multiple high-visibility initiatives. The position combines technical leadership with delivery of advanced AI and agentic solutions, including end-to-end automation from discovery through production and operations.

Responsibilities

• Drive a culture of accountability for customer and business outcomes by building engineering solutions to address complex problems with measurable value, while maintaining high-quality, lean designs and implementations.
• Act as a technical advocate for products by ensuring code integrity, feasibility, and alignment with business and customer goals; lead requirement analysis, low-level architecture, component design, development, testing, integrations, and support.
• Own architectural and technical stack integrity against enterprise standards and strategy, including dependency management; stay hands-on with self-driven continuous learning; produce technical specifications; write scalable, supportable code; review other engineers’ work to ensure quality KPIs are met or exceeded.
• Deliver lean solutions through rapid, inexpensive experimentation; work with customers and product teams before, during, and after delivery to ensure the right solution ships at the right time.
• Apply an action-and-evidence mindset to navigate complexity and uncertainty, delivering solutions that remain lean, supportable, and maintainable.
• Collaborate with empowered, cross-functional teams across product management, experience, and delivery; integrate diverse perspectives to balance feasibility, viability, usability, and value, and strengthen team synergy and innovation.
• Use modern software engineering practices, including AI and agentic SSDLC, to enable daily product deployments with full automation across discovery to production to operations, supported by quality checks through the SSDLC lifecycle.
• Quickly build domain knowledge relevant to the business or product; translate business and user needs, architectures, and UX/UI designs into technical specifications and code; support teammates while prioritizing quality and technical debt payoff.
• Communicate complex technical concepts clearly and persuasively; influence teammates and product teams with evidence-based trade-offs and well-structured technical narratives that align to business objectives.
• Engage with product engineering teams at all organizational levels, including customers as needed; build constructive relationships that support co-creation and shared momentum toward product goals.

Requirements

• Bachelor’s degree in computer science, software engineering, data science, machine learning, or a related discipline. Experience is the most relevant factor.
• 6+ years of experience with most of: Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, and unit testing frameworks.
• 3+ years of experience building AI/ML applications, including hands-on GenAI experience with LLM integration (OpenAI, Anthropic, or open-source models), RAG pipelines, prompt engineering, and vector databases.
• 3+ years of experience in 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+ years of experience establishing engineering standards, actively leading, mentoring, and guiding teams in adoption and continuous improvement of those standards.
• Software engineering experience including familiarity with Business Context Diagrams (BCD), sequence/activity/state/entity relationship/data flow diagrams, OOP/OOD, data structures, algorithms, and code instrumentation, as well as AI-augmented spec-driven development.
• Experience with methodologies and tools such as XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, MLflow, and agentic AI frameworks (for example, LangFuse, LangSmith, or equivalent multi-agent orchestration tools) to deliver high-quality products rapidly.
• Must be located within commutable distance to one of the select locations for this role.
• Ability to work in the local office at least 3 days per week.
• Limited immigration sponsorship may be available.
• Ability to travel 0-10% on average, based on work, clients, and industries/sectors supported.

Technologies

• Angular, React, NodeJS, Python, C#, .NET, Java
• SQL/NoSQL, PyTorch, TensorFlow
• LangChain, LangGraph
• Unit testing frameworks
• OpenAI, Anthropic
• RAG pipelines, prompt engineering, vector databases
• FaaS, PaaS, micro-services
• Azure, AWS, GCP; Azure OpenAI, AWS Bedrock, Vertex AI
• XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, MLflow
• LangFuse, LangSmith

Benefits

• You may be eligible to participate in a discretionary annual incentive program, subject to program rules, where any award depends on factors including individual and organizational performance.

The Team

Deloitte Technology Product Engineering modernizes software and product delivery through a scalable, cost-effective model focused on value and outcomes, using a progressive and responsive talent structure. As Deloitte’s primary internal development team, Product Engineering delivers innovative digital solutions for businesses, service lines, and internal operations, supporting proven bottom-line results. The team develops and deploys cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market.

Location, Salary, and Work Details

• Location: Tampa, FL (onsite)
• Salary: USD 113,100 - 232,300 per year
• Wage range note: the disclosed range estimate is not adjusted for applicable geographic differential; a reasonable estimate is $113,100 - 232,300
• Work location requirement: minimum of 3 days per week in the local office