Lead Applied AI Platform Engineer II
Role Overview: As a Lead Applied AI Platform Engineer II, you will actively engage in your engineering craft, taking a hands-on approach to building the platforms, tooling, accelerators, and frameworks that other engineering teams build on. Your expertise will be pivotal in delivering platform capabilities that delight the engineers who depend on them, while driving tangible leverage and value across Deloitte’s AI engineering investments. You will leverage your extensive engineering craftsmanship and advanced proficiency across platform engineering, distributed systems, and modern AI/ML and Data infrastructure, consistently demonstrating your exemplary track record in delivering high-quality, reusable, outcome-focused solutions. The ideal candidate will be a role-model leader and mentor, collaborating with cross-functional teams to design, build, and operate the enabling layer for AI engineering at scale.
Key Responsibilities:
? Outcome-Driven Accountability: Embrace and drive a culture of accountability for engineering-leverage and adoption outcomes. Build platform capabilities that solve recurring problems once, well, for many teams—reducing per-team build and operate toil while ensuring consistency and compliance by default through high-quality, lean designs and implementations.
? Technical Leadership and Advocacy: Serve as the technical advocate for the platform as a product, ensuring capability integrity, feasibility, and alignment with the needs of the engineering teams who consume it. Lead requirement discovery with consuming teams, low-level architecture and component design of platform services, frameworks, and the AI control plane, and their development, testing, integration, and support.
? Engineering Craftsmanship: Maintain accountability for the integrity of the platform architecture and for the enterprise tech-stack conformance baseline that engineering teams build against. Manage platform dependencies, code design, implementation, the data and policy-as-code enforcement layers, and the OpenTelemetry-based instrumentation substrate—building capabilities that are operable, instrumented, performant, and drift-resistant by design, to the production standards set by SRE. Stay hands-on, self-driven, and continuously learn new approaches, languages, and frameworks. Create technical specifications, codify recurring patterns into reusable components and golden paths, and write high-quality, supportable, scalable code and review code of other engineers, mentoring them, to ensure all platform KPIs (adoption, reliability-by-design, and developer experience) are met or exceeded. Demonstrate collaborative skills to work effectively with diverse teams.
? Customer-Centric Engineering: Develop lean platform capabilities through rapid, inexpensive experimentation to solve the real needs of consuming engineering teams. Engage with those teams before, during, and after delivery to ensure the right capability is delivered at the right time—and adopted, not shelved.
? 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 platform capabilities as lean, adoption-validated increments rather than big-bang builds, and keeping them supportable and maintainable.
? Cross-Functional Collaboration and Integration: Work collaboratively with empowered, cross-functional partners: engineering, SRE, security and risk, data governance, and engineering leadership and architecture. Integrate their constraints into the paved roads so that the secure, compliant, and reliable path is the easy path. Deliver capabilities that are admissible-by-design and submit them for admission, co-defining service-level objectives with SRE, who set production standards and own the admission decision. Foster a collaborative environment that enhances team synergy and innovation.
? Advanced Technical Proficiency: Possess deep expertise in platform engineering and modern AI/ML infrastructure—internal developer platforms, MLOps/LLMOps, model serving, retrieval and vector infrastructure, eval and observability tooling, policy-as-code, container orchestration, IaC, and CI/CD at platform scale—including AI and Agentic SSDLC to deliver self-service, governed capabilities with full automation from discovery to production to operations and all quality checks through the SSDLC lifecycle. Be a role model, leveraging these techniques to optimize platform solutioning and delivery. Demonstrate strong understanding of the full lifecycle of platform and product development, focusing on continuous improvement and learning.
? Domain Expertise: Quickly acquire domain knowledge of the enterprise data estate and the AI use-case patterns the platform must serve. Translate the needs of engineering teams, reference architectures, and governance requirements into reusable frameworks, the data platform, and governance-as-code enforcement. 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.
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.
? 6+ years of software and platform engineering experience with most of the following: Angular, React, NodeJS, Python(Mandatory), , C#, .NET, Java, Rust, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, LangSmith, LangFuse, Terraform, as well as unit, integration, and end-to-end testing frameworks & tools, specifically BDD, Gherkin, Cucumber, Playwright, and Selenium.
? 3+ years of experience designing, building, and operating AI/ML platform or infrastructure, with hands-on experience across building tooling for MLOps/LLMOps, model serving, retrieval and vector infrastructure, and eval/observability instrumentation for LLM integration (OpenAI, Anthropic, or open-source models).
? 3+ years of experience with cloud-native engineering 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—as well as container orchestration (Kubernetes, Docker), Big Data, Databricks, CI/CD at platform scale, and distributed systems.
Technical Skills:
? Deep expertise in SAP HR modules, with a strong background in payroll schema, rules, and custom function development.
? Proven experience designing and implementing custom solutions for HR processes, including payroll calculations, data integration, and reporting.
? Extensive hands-on experience with:
? SAP Reports (including ALV)
? Interfaces (file-based; IDOC, ALE preferred)
? Enhancements (User Exits, Customer Exits, BADI; BTE and Enhancement Framework a plus)
? Forms (SAP Scripts, Smart Forms; Adobe Forms preferred)
? Conversions (BDC, BAPI; LSMW a plus)
? HR ABAP (Forms, Enhancements, Interfaces, Exits, Function Modules, Payroll Operations/Functions, Data Replication)
? Advanced knowledge of SAP Gateway, OData, and Enterprise Services.
? Strong experience with ALE/IDOCs, Adobe Forms, RFCs, BAPIs, and Data Dictionary elements.
? Proficient in ATC and code inspector configurations, performance tuning, enhancements, and modifications.
? Hands-on experience with SAP UI technologies (Fiori/UI5), including:
? Development of Fiori applications (FreeStyle SAPUI5/Fiori Elements)
? Experience with Business Integration Builder (BIB) framework for employee data replication and integration.
? Familiarity with SAP BTP Services (CI, API, Discovery Centre) and connectivity between BTP and ECC (Destination Service, Connectivity Service, Cloud Connector).
? Knowledge of SAP SuccessFactors Employee Central.
? Leadership & Project Management:
? Proven ability to lead and manage cross-functional engineering teams from inception to delivery.
? Establish and maintain detailed project plans, metrics, schedules, resource plans, and status reports.
? Identify project risks and develop effective mitigation strategies.
? Provide project leadership, direction, and feedback to team members.
? Motivate and influence teams beyond direct authority to achieve project milestones and deliverables.
? Convey project status and updates to global business leads and key stakeholders.
? Present formal presentations and executive summaries to Leadership, including recommendations and status updates.
Operational Responsibilities:
? Ensure SAP Payroll solutions are delivered according to business specifications and statutory requirements.
? Resolve escalated payroll issues, collaborating with Talent, Finance, and IT teams.
? Support and coordinate efforts of Subject Matter Experts, Development, QA, Usability, Training, Transport Management, and other internal resources for successful system enhancements and fixes.
? Contribute to the development of standards, guidelines, and best practices to ensure consistency across projects.
? Oversee the creation and maintenance of internal documentation and end-user training materials.
? 1+ years of experience establishing engineering standards and golden paths, including actively leading, mentoring, and guiding team members in the adoption and continuous improvement of these standards, treating the platform as a product.
? Prior experience with AI control-plane and agent-runtime patterns: model/LLM gateway, A2A and MCP integration, agent runtimes (e.g., Google ADK, Amazon Bedrock AgentCore), guardrails (PII redaction, prompt-injection, content, tool permissioning/tool-RBAC), policy-as-code, and multi-tenant isolation.
? Prior experience with enterprise data platform engineering: data pipelines, self-service and data-product enablement, governance-as-code enforcement, and metadata/lineage.
? 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, and ArgoCD to deliver high-quality platforms and products rapidly.
