Lead Applied AI Engineer 2

Role Overview: As a Lead Applied AI Engineer II, you will actively engage in your engineering craft, taking a hands-on approach to multiple high-visibility projects. Your expertise will be pivotal in delivering solutions that delight customers and users, while also driving tangible value for Deloitte's business investments. You will leverage your extensive engineering craftsmanship and advanced proficiency across multiple programming languages and modern frameworks, 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, develop, and deploy advanced software solutions.

Key Responsibilities:

• Outcome-Driven Accountability: Embrace and drive a culture of accountability for customer and business outcomes. Develop engineering solutions that solve complex problems with valuable outcomes, ensuring high-quality, lean designs and implementations.
• 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, supportive of teammates, and focused on quality and tech debt payoff.
• Effective Communication and Influence: Exhibit exceptional communication skills, capable of articulating complex technical concepts clearly and compellingly. Inspire and influence teammates and product teams through well-structured arguments and trade-offs supported by evidence. Create coherent narratives that align technical solutions with business objectives.
• Engagement and Collaborative Co-Creation: Engage and collaborate with product engineering teams at all organizational levels, including customers as needed. Build and maintain constructive relationships, fostering a culture of co-creation and shared momentum towards achieving product goals. Align diverse perspectives and drive consensus to create feasible solutions.

The team: US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model that focuses on value/outcomes that leverages a progressive and responsive talent structure. 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 and outcomes. It helps power Deloitte’s success. It is the engine that drives Deloitte, serving many of the world’s largest, most respected companies. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence.

Required Qualifications:

• A 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 the following: Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, as well as unit testing frameworks.
• 3+ years of experience 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 experience with cloud-native engineering, using FaaS, PaaS, or micro-services on any of the cloud hyperscalers such as Azure, AWS, or GCP, including their AI/ML services such as Azure OpenAI, AWS Bedrock, or Vertex AI.
• 1+ years of experience in establishing engineering standards, including actively leading, mentoring, and guiding team members in the adoption and continuous improvement of these standards.
• Prior software engineering experience with the understanding of 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) etc. to deliver high-quality products rapidly.
• Candidates must be located within a commutable distance to one of the select locations available for this role 
• Ability to work in your local office at a minimum of 3 days per week
• Limited immigration sponsorship may be available.
• Ability to travel 0-10%, on average, based on the work you do and the clients and industries/sectors you serve

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $113,100 – 232,300.

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. 

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