Summary

Position Summary

Director, Applied AI Engineering

Role Overview: As a Director, Applied AI Engineering , you will shape and own the engineering strategy and technical direction for your service line—translating business objectives into engineering strategy, mapping business capabilities to the enterprise technology landscape, and defining how GenAI and agentic capabilities are built directly into the products we deliver. You will develop and execute a forward-looking technology roadmap that drives simplification, scalability, and efficiency—rationalizing the landscape and integrating the service line’s portfolio within the wider enterprise across multiple upstream and downstream systems. Leading across product groups and the service line, you will stay hands-on in your craft—shaping architecture, integration, design, and code—while driving the standards and enterprise reference architectures that engineers build against.

Your leadership will be pivotal in delivering tangible value across the service line’s product and AI investments, aligning technical solutions with business and technology strategy, and advancing Applied AI engineering across the organization. You will bring extensive engineering craftsmanship and deep expertise across software and data engineering, enterprise and integration architecture, and AI/ML and GenAI, together with an exemplary track record of high-quality, outcome-focused delivery at scale. The ideal candidate is a role-model engineering leader who leads by doing —owning strategy, elevating standards, developing engineers and emerging leaders, and building trusted relationships with stakeholders from engineering teams to senior executives and service-line leadership.

Key Responsibilities:

- Accountable for defining, communicating, and continuously refining the engineering strategy for the service line—translating business objectives into actionable strategy, mapping business capabilities to the enterprise technology landscape, defining how GenAI and agentic capabilities are built directly into the products we deliver, and shaping how those products integrate within the enterprise across multiple upstream and downstream systems—in alignment with the Business Strategy and US Deloitte Technology strategy. Collaborate with diverse stakeholders and executives, including businesses and enabling areas as well as product, engineering, experience, delivery, security, and infrastructure teams, across all organizational levels.
- Champion, own, and execute the integrated Applied AI engineering, architecture, and technology strategy and its implementation roadmap across the service line—driving simplification, scalability, and efficiency, and actively rationalizing the landscape by removing unnecessary systems, integrations, and bottlenecks. Ensure the organization is well-informed about objectives, KPIs, maturity, compliance, and progress. Promote a culture of reuse, quality, and speed—keeping an eye on leverage of existing assets and on the inference, token, and cloud cost of what we build, to maximize outcomes and minimize total cost.
- Define, measure, and drive the achievement of KPIs and NFRs spanning system performance, scalability, security, reliability, interoperability, auditability, and maintainability, and own engineering health and delivery KPIs across the product groups and the service line. Establish and evolve Applied AI engineering, enterprise and integration 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 that carries work from discovery to production to operations with full automation and quality checks through the SSDLC lifecycle. Remain hands-on with design, architecture, integration, and code—contributing to product group and service line velocity and staying engaged with engineers across the SSDLC—while reviewing standards and code, driving tech-debt reduction, and experimenting with new technology.
- As a recognized engineering leader, mentor and develop engineers and emerging leaders, building the engineering talent bench across the product groups and the service line. Coach modern Applied AI engineering practices—full-stack and micro-services,



integration tools and practices, cloud-native design, AI/ML/GenAI and agentic systems, data engineering, application-level infrastructure-as-code, and advanced deployment techniques (Blue-Green, Canary, A/B testing) that minimize downtime. Lead by example through thought leadership—showcasing experiments internally, speaking at conferences, publishing whitepapers or blogs, and leading R&D; collaborations, including with academia and communities. Cultivate a growth mindset and modern engineering behaviors across the organization.
- Embrace an iterative and incremental approach to Applied AI product engineering and integration architecture, favoring action and rapid learning over extensive upfront planning. Apply a leaning-forward approach and empirical methods to navigate complexity and uncertainty, ensuring each iteration delivers value and stays aligned with customer and business goals.
- Maintain a relentless focus on solving the most critical challenges faced by customers and users, aligning technical solutions with business outcomes. Minimize unnecessary technical complexity and avoid overengineering—features, functionality, and integration approaches that do not add value—and drive teams toward peak performance through continuous learning and collaborative execution. Collaborate, challenge, and own technical decisions advocated by business or other groups that do not fit or advance the enterprise ecosystem.
- Possess deep expertise in modern Applied AI engineering and architecture practices, with a keen ability to identify inefficiencies and opportunities for innovation across the technology landscape and the product lifecycle. Continuously enhance the engineering operating model to be lean, adaptable, and responsive—guiding and transforming the organization to embrace lean principles and foster a culture of innovation.
- Establish and evolve enterprise reference architectures, coding standards, and engineering and quality benchmarks that ensure robust, secure, scalable, and reliable/resilient solutions. Ensure appropriate, responsible technology adoption—developing explainable, scalable, reliable, and secure AI and agentic products—and proactively identify technical risks, developing mitigation strategies through proactive problem-solving and contingency planning, ensuring operational excellence and resilience across the product groups and the service line.
- Influence, persuade, and drive decision-making across the organization. Communicate effectively in both written and verbal forms, crafting clear, structured arguments and technical trade-offs supported by evidence.
- Engage stakeholders at all levels—from team members and middle management to senior executives and service-line leadership—building collaborative, constructive relationships and co-creating momentum and value across the organization.

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.

The successful candidate will possess:

- Excellent interpersonal and organizational skills, with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care.

Required Qualifications:





- A bachelor’s degree in computer science, software engineering, data science, machine learning, or related discipline. Experience is the most relevant factor.
- 12+ 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.
- 8+ 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 any of the cloud hyperscalers such as Azure, AWS, or GCP, including leveraging their AI/ML services such as 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.
- 5+ years of experience in establishing enterprise engineering standards, including actively leading, mentoring, and guiding large engineering teams 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.

Other:

- Ability to travel 10%, on average, based on the work you do and products you build.
- Limited immigration sponsorship may be available.

Our purpose

Deloitte’s purpose is to make an impact that matters for our people, clients, and communities. At Deloitte, purpose is synonymous with how we work every day. It defines who we are. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities.

Our people and culture

Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ways of thinking, ideas and perspectives, and bring more creativity and innovation to help solve our clients’ most complex challenges. This makes Deloitte one of the most rewarding places to work.

Professional development

At Deloitte, professionals have the opportunity to work with some of the best and discover what works best for them. Here, we prioritize professional growth, offering diverse learning and networking opportunities to help accelerate careers and enhance leadership skills. Our state-of-the-art DU: The Leadership Center in India, located in Hyderabad, represents a tangible symbol of our commitment to the holistic growth and development of our people. Explore DU: The Leadership Center in India .

Benefits To Help You Thrive

At Deloitte, we know that outstanding people make a great organization. Our comprehensive rewards program helps us deliver a distinctly Deloitte experience that helps that empowers our professionals to thrive mentally, physically, and financially—and live their purpose. To support our professionals and their loved ones, we offer a broad range of benefits. Eligibility requirements may be based on role, tenure, type of employment and/ or other criteria. Learn more about what working at Deloitte can mean for you.

Recruiting tips

From developing a stand out resume to putting your best foot forward in the interview, we want you to feel prepared and confident as you explore opportunities at Deloitte. Check out recruiting tips from Deloitte recruiters.

Requisition code: 362675

📌 Applied AI Engineer - Firm Enterprise Solutions Director (Hyderabad)
🏢 Deloitte
📍 Hyderabad