Associate Director, Applied AI Engineering - PxE Consulting

Set the engineering vision and technical direction for the firm's enterprise solutions, mapping business capabilities to the enterprise technology landscape and defining how GenAI and agentic capabilities are built directly into the products we deliver.

Responsibilities

• Craft and articulate a vision for Applied AI engineering across the firm's enterprise solutions, aligning with Business Strategy and US Deloitte Technology strategy.
• Collaborate with diverse stakeholders across product, engineering, experience, delivery, security, and infrastructure at all organizational levels.
• Advocate for, develop, and communicate the integrated Applied AI engineering, architecture, and technology strategy and its implementation roadmap to engineering teams and business stakeholders.
• Promote a culture of reuse, quality, and speed, focusing on leverage of existing assets and cost management (inference, token, and cloud costs).
• Define, measure, and drive the achievement of KPIs and NFRs spanning system performance, scalability, security, reliability, and maintainability.
• Establish and evolve Applied AI engineering, architecture, and AI/ML/GenAI reference architectures, standards, and best practices, including spec- and context-driven development, evaluations, AI agent orchestration, and the AI and Agentic SSDLC.
• Remain hands-on with design, architecture, and code, contributing to team and product group velocity, reviewing code, driving tech-debt reduction, and experimenting with new technology.
• Mentor and develop engineers and emerging engineering leaders, coaching modern Applied AI engineering practices (full-stack, micro-services, cloud-native design, AI/ML/GenAI, agentic systems, data engineering, infrastructure-as-code, and advanced deployment techniques).
• Lead by example through thought leadership, showcasing experiments internally, speaking at conferences, publishing whitepapers or blogs, and leading R&D collaborations, including with academia.
• Embrace an iterative and incremental approach to Applied AI product engineering, favoring action and rapid learning over extensive upfront planning.
• Maintain a relentless focus on solving critical challenges faced by customers and users, aligning technical solutions with business outcomes.
• Possess deep expertise in modern Applied AI engineering and architecture practices, identifying inefficiencies and opportunities for innovation across the product lifecycle.
• Continuously enhance the engineering operating model to be lean, adaptable, and responsive.
• Establish and evolve reference architectures, coding standards, and engineering and quality benchmarks for robust, secure, scalable, and reliable/resilient solutions.
• Ensure responsible technology adoption, developing explainable, scalable, reliable, and secure AI and agentic products.
• Proactively identify technical risks and develop mitigation strategies.
• Influence, persuade, and drive decision-making across the organization through clear, structured communication of technical trade-offs.
• Engage stakeholders at all levels, building collaborative relationships and co-creating momentum and value.

Requirements

• Bachelor's degree in computer science, software engineering, data science, machine learning, or related discipline (experience is the most relevant factor).
• 10+ years of full-stack software engineering experience with most of the following: Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, REST/SOAP/GraphQL, SSO/MFA, PyTorch, TensorFlow, LangChain, LangGraph, as well as unit and integration testing frameworks.
• 7+ years of experience architecting and delivering enterprise solutions on modern technology stacks (e.g., API Gateways, Message Brokers, Queuing Services, Workflow Automation & Orchestration, ETL/ELT, Event Streaming, Real-Time Data Processing, Service Mesh) and cloud-native engineering using FaaS, PaaS, and micro-services on cloud hyperscalers such as Azure, AWS, or GCP, including their AI/ML services (Azure OpenAI, AWS Bedrock, or Vertex AI), plus application-level infrastructure-as-code and cost-aware engineering (FinOps accountability).
• 5+ years of experience building AI/ML and agentic applications, with hands-on GenAI experience across LLM integration (OpenAI, Anthropic, or open-source models), RAG pipelines, prompt engineering, vector databases, evaluations, and AI agent orchestration.
• 2+ years of experience in establishing engineering standards, actively leading, mentoring, and guiding team members in 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 instrumentations, and AI-augmented spec-driven development.
• Prior experience using methodologies & 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).
• Ability to work in your local office at a minimum of 3 days per week.
• Must be located within a commutable distance to one of the select locations available for this role.
• Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.
• Ability to travel 0-10%, on average, based on the work you do and the clients and industries/sectors you serve.

Benefits

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Pay

The wage range for this role is $130,900 to $268,700, taking into account skill sets, experience, training, licensure, certifications, and other business and organizational needs. The range has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled.

About the team

US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model focused on value and outcomes. As Deloitte's primary internal development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom-line results. It powers Deloitte's success and serves many of the world's largest, most respected companies. The team develops and deploys cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market.