Lead Applied AI Engineer II

Lead Applied AI Engineer II at Deloitte, delivering hands-on, outcome-focused engineering across multiple high-visibility projects with full automation from discovery through production and operations.

Responsibilities

• Drive a culture of accountability for customer and business outcomes; deliver high-quality, lean designs and implementations to solve complex problems.
• Act as the technical advocate for products by ensuring code integrity, feasibility, and alignment with business and customer goals.
• Lead requirement analysis, low-level architecture, and component design; oversee development, testing, integrations, and support.
• Maintain accountability for architecture and technical stack integrity aligned to enterprise standards and strategy.
• Manage dependencies, code design, implementation, quality, data, and ongoing maintenance and operations while staying hands-on and self-driven.
• Continuously learn new approaches, languages, and frameworks; produce technical specifications and write scalable, supportable code.
• Review other engineers’ code and mentor teams to help ensure quality KPIs are met or exceeded.
• Deliver lean solutions via rapid, inexpensive experimentation to address customer needs.
• Collaborate with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time.
• Use an action and evidence mindset to navigate complexity and uncertainty; build lean, maintainable solutions.
• Work with empowered cross-functional teams (product management, experience, delivery) to balance feasibility, viability, usability, and value.
• Model daily product deployment using AI and agentic SSDLC concepts with full automation across discovery to production to operations, including quality checks through the SSDLC lifecycle.
• Acquire domain knowledge quickly and translate business/user needs, architectures, and UX/UI designs into technical specifications and code.
• Support teammates with a focus on quality and tech debt payoff.
• Communicate complex technical concepts clearly; influence stakeholders with evidence-based trade-offs and coherent technical narratives aligned to business objectives.
• Collaborate with product engineering teams at all organizational levels, including customers as needed; build constructive relationships to drive shared momentum.
• Align diverse perspectives and drive consensus to deliver feasible solutions.

Requirements

• Bachelor’s degree in computer science, software engineering, data science, machine learning, or 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 building AI/ML applications, including hands-on GenAI work: LLM integration (OpenAI, Anthropic, or open-source models), RAG pipelines, prompt engineering, and vector databases.
• 3+ years 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 establishing engineering standards, actively leading, mentoring, and guiding teams on adoption and continuous improvement.
• Prior software engineering experience with Business Context Diagrams (BCD), sequence/activity/state/entity relationship/data flow diagrams, OOP/OOD, data structures, algorithms, and code instrumentation, plus AI-augmented spec-driven development.
• Experience with methodologies and tools such as 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.
• Must be located within a commutable distance to an available select location for this role.
• Ability to work from 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.

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

• Discretionary annual incentive program eligibility, subject to applicable program rules and factors including individual and organizational performance.

The Team

• US Deloitte Technology Product Engineering modernized software and product delivery with a scalable, cost-effective model focused on value and outcomes.
• As Deloitte’s primary internal development team, Product Engineering delivers innovative digital solutions for businesses, service lines, and internal operations.
• Develops and deploys cutting-edge internal and go-to-market solutions to help Deloitte operate effectively and lead in the market.
• Built on a tradition of delivering with excellence.

Compensation

• Salary range: USD 113,100 - 232,300 per year
• Disclosed range estimate may not reflect geographic differential for the location where the position may be filled; reasonable estimate is $113,100 - $232,300.

Location & Work Details

• Tampa, FL (onsite)
• Local office work requirement: minimum 3 days per week
• Travel: 0-10% on average