As an Associate Director, Applied AI Platform Engineering, you will set the engineering vision and technical direction for the Applied AI engineering platform-the frameworks, tooling, control plane, and data platform that every other engineering team builds on-treating the platform as a product and solving recurring problems once, well, for many teams. Leading across teams and product groups, you will stay hands-on in your craft-shaping architecture, design, and code-while driving the golden paths, reusable components, and governed, self-service capabilities that engineering teams depend on. Your leadership will be pivotal in delivering tangible leverage and value across Deloitte's AI engineering investments, maximizing reuse and reducing per-team toil, and advancing Applied AI platform engineering across the organization.
You will bring extensive engineering craftsmanship and deep expertise across platform engineering, distributed systems, and modern AI/ML and data infrastructure, together with an exemplary track record of high-quality, reusable, outcome-focused delivery at scale. The ideal candidate is a role-model engineering leader who leads by doing-setting vision, elevating standards, developing engineers and emerging leaders, and building trusted relationships with stakeholders from engineering teams to executives.
Work You'll Do:
Strategic Vision and Alignment: Craft and articulate a vision for the Applied AI engineering platform-the frameworks, tooling, accelerators, control plane, and data platform that every other engineering team builds on-in alignment with the Business Strategy and US Deloitte Technology strategy. Treat the platform as a product, mapping the needs of consuming engineering teams to reusable, self-service capabilities. Collaborate with diverse stakeholders across product, engineering, SRE, security and risk, data governance, and infrastructure at all organizational levels.
Advocacy and Technology Roadmap: Advocate for, develop, and communicate the integrated platform engineering strategy and its implementation roadmap, positioning the platform as a product to the engineering teams who consume it and to business stakeholders. Ensure the organization is well-informed about objectives, KPIs, adoption, maturity, compliance, and progress. Promote a culture of reuse, quality, and speed-solving recurring problems once, well, for many teams to reduce per-team build and operate toil, maximize engineering leverage, and minimize total cost of ownership.
Craft Mastery and Objectives Realization: Define, measure, and drive the achievement of platform KPIs and NFRs-adoption, reliability-by-design, developer experience, performance, scalability, and security. Establish and evolve platform reference architectures, golden paths, and reusable components-including the AI control plane (with the model/LLM gateway) and agent-runtime patterns, MLOps/LLMOps tooling, model serving, retrieval and vector infrastructure and RAG-as-a-Service, Eval-as-a-Service and observability tooling, prompt management, and feature store; governance-as-code enforcement, control codification, and ontology management; the data platform (data catalog and marketplace, DataOps, data management and enterprise integration, master data, pipelines, and metadata/lineage); and CI/CD at platform scale-delivered through the AI and Agentic SSDLC as self-service, governed capabilities with full automation from discovery to production to operations and quality checks through the SSDLC lifecycle. Remain hands-on with design, architecture, and code-contributing to the leverage and velocity of the engineering teams and product groups that build on the platform-while reviewing code, driving tech-debt reduction, and experimenting with new technology.
Capability Evolution and Development: As a recognized engineering leader, mentor and develop engineers and emerging engineering leaders, coaching modern platform engineering practices-internal developer platforms, distributed systems, the AI control plane and agentic patterns, MLOps/LLMOps, cloud-native design and container orchestration, platform-scale infrastructure-as-code, and the data platform. Lead by example through thought leadership-showcasing experiments internally, speaking at conferences, publishing whitepapers or blogs, and leading R&D collaborations, including with academia. Cultivate a growth mindset and modern engineering behaviors across the organization.
Iterative Value Delivery: Embrace an iterative and incremental approach to platform engineering, delivering platform capabilities as lean, adoption-validated increments rather than big-bang builds. Apply a leaning-forward approach and empirical methods to navigate complexity and uncertainty, keeping capabilities supportable and maintainable and ensuring each increment delivers value and stays aligned with consuming-team and business goals.
Customer-Centric Problem Solving: Maintain a relentless focus on the real needs of the engineering teams who consume the platform-your primary customers-developing lean capabilities through rapid, inexpensive experimentation and engaging those teams before, during, and after delivery so the right capability is delivered at the right time and adopted, not shelved. Minimize unnecessary technical complexity and avoid overengineering, and drive toward peak performance through continuous learning and collaborative execution.
Expert Proficiency and Continuous Improvement: Possess deep expertise in modern platform engineering and AI/ML and data infrastructure, with a keen ability to identify inefficiencies and opportunities for innovation across the platform and the engineering operating model. Continuously enhance the operating model to be lean, adaptable, and responsive-guiding and transforming the organization to embrace lean principles and foster a culture of innovation.
Tech/Quality Risk Management: Establish and evolve the enterprise tech-stack conformance baseline, platform standards, and quality benchmarks that engineering teams build against-embedding consistency, compliance, and security by default through guardrails (PII redaction, prompt-injection and content controls, tool permissioning and RBAC) and multi-tenant isolation, so that the secure, compliant, and reliable path is the easy path. Build capabilities that are operable, instrumented, performant, and drift-resistant by design to the production standards set by SRE, delivering them admissible-by-design and co-defining service-level objectives with SRE, who own the admission decision. Proactively identify technical risks and develop mitigation strategies through proactive problem-solving and contingency planning.
Influential Communication: 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.
Organizational Engagement and Collaboration:Engage stakeholders at all levels-from team members to middle management to executives-and collaborate with empowered, cross-functional partners across engineering, SRE, security and risk, and data governance, integrating their constraints into the paved roads. Build collaborative, constructive relationships and co-create 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.
Qualifications
Required:
A bachelor's degree in computer science, software engineering, data science, machine learning, or related discipline. Experience is the most relevant factor.
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.
10+ years of software and platform engineering experience with most of the following: Angular, React, NodeJS, Python(Mandatory), , C#, .NET, Java, Rust, SQL/NoSQL, REST/SOAP/GraphQL, SSO/MFA, 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.
7+ years of experience architecting and delivering enterprise solutions and platforms 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, as well as container orchestration (Kubernetes, Docker), Big Data, data platform tooling such as Informatica, Databricks, or Delphix (spanning data governance and observability, data fabric, and data anonymization), CI/CD and infrastructure-as-code at platform scale, and distributed systems.
5+ 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).
2+ years of experience establishing engineering platform 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.
Ability to travel 10%, on average, based on the work you do and products you build.
Limited immigration sponsorship may be available.
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.
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 $130,900 to $268,700
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Benefits
At Deloitte, we know that great people make a great organization. We value our people and offer employees a broad range of benefits. Learn more about what working at Deloitte can mean for you.
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.
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. Learn more.
Professional development
From entry-level employees to senior leaders, we believe there's always room to learn. We offer opportunities to build new skills, take on leadership opportunities and connect and grow through mentorship. From on-the-job learning experiences to formal development programs, our professionals have a variety of opportunities to continue to grow throughout their career.
As used in this posting, "Deloitte" means Deloitte Services LP, a subsidiary of Deloitte LLP. Please see www.deloitte.com/us/about for a detailed description of the legal structure of Deloitte LLP and its subsidiaries.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or protected veteran status, or any other legally protected basis, in accordance with applicable law.
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About the role
This is a Senior Level role in the Technology field (Data, analytics and AI) at Deloitte. Senior roles usually expect substantial experience, ownership of results and often the ability to guide others.
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Estimate for a wage earner: 2026 federal brackets and standard deduction (IRS), Social Security 6.2% up to $184,500, Medicare 1.45% (+0.9% above $200,000 single / $250,000 married), and a state rate you set; set your own state tax rate. It ignores credits, pre-tax deductions, local taxes and benefits. Sources: IRS: tax year 2026 inflation adjustments · SSA wage base per Federal Register notice 2025-19763.
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The job is in Dallas, TX. Below is what the official statistics say about living and working there.
How Dallas compares. Among the 120 largest places in Texas, Dallas is #3 by population, #112 for homeownership (#1 = highest), #42 for remote work (#1 = most), #46 for college degrees (#1 = most). Its county, Dallas County, is #8 of 254 counties for average pay ($89,284).
The place in numbers
Dallas has 1,307,930 residents (ACS 2020–2024), about 4.3% of the population of Texas. It covers 340 square miles of land, which works out to roughly 3,850 people per square mile. The median age is 33.4, 6% younger than the state median (33.4 against 35.6).
Housing
The median gross rent is $1,472 a month (rent plus utilities), 5% above the state median ($1,472 against $1,403). Over a year that is 25.0% of the median household income. US housing guidance treats housing as affordable when it takes 30% of income or less, so the typical household is under that line. The median home value is $320,700, which is 4.5 times the median household income ($70,518). 42.4% of households own their home, 32% below the state average (42.4% against 62.6%). A low ownership share points to a rental-heavy market with more apartments and shorter stays.
Work and pay
The Dallas-Fort Worth-Arlington, TX metropolitan area has 4,049,800 jobs in the BLS wage survey, and the median pay across all occupations is $51,440 a year, about the same as the national median ($51,440 against $50,980). The biggest occupation groups are office and administrative support (490,190 jobs, median $47,080); transportation and material moving (423,430 jobs, median $44,570); management (379,320 jobs, median $128,140). The area is most specialised in computer and mathematical (1.4 times) and management (1.3 times), where the share of workers is above the national share. The best-paying groups with at least 5,000 jobs are management ($128,140) and computer and mathematical ($121,440). In 2026M09 the unemployment rate of Dallas County was 4.2%. 68.6% of residents aged 16 and over are in the labour force. The city lies in Dallas County; its jobs, pay by industry and GDP are on the county page.
Getting around
Among workers, 66.6% drive alone, 2.1% use public transit, 2.1% walk, 15.8% work from home. 14.1% of workers commute 45 minutes or more, 17% below the state average (14.1% against 16.9%).
People and education
38.2% of adults aged 25 and over hold a bachelor's degree or higher, 13% above the state share (38.2% against 33.8%). 23.4% of residents were born outside the United States, 33% above the state share (23.4% against 17.6%). The poverty rate is 16.7%, 21% above the state rate (16.7% against 13.8%).
Climate
The warmest month is Aug, averaging 86°F (30.1°C), and the coolest is Jan at 44°F (6.4°C). About 921 mm (36 inches) of precipitation falls in a year; May is the wettest month (116 mm) and Jul the driest (55 mm). These values come from NASA satellite-based climatology on a grid of about 50 km, so they describe the wider area, not a weather station in the city.
Nearby cities to compare
Closest cities in this guide: Mesquite (11 miles, similar rent); Garland (11 miles, rent 11% higher); Farmers Branch (11 miles, rent 27% higher); Irving (13 miles, rent 10% higher). Rent differences are against Dallas; use the Compare tab to put any two cities side by side.
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What is the Associate Director, Applied AI Platform Engineering (PxE Platforms) job at Deloitte?
A senior level role in technology (data, analytics and ai) listed 7 days ago. The full description is on this page and on The Muse.
Where is this job?
Dallas, TX.
How do I apply?
Use the "View this job and apply on The Muse" button. AtiveSite does not receive applications.
How much does it pay?
The listing does not publish pay, and we could not match the title to one official occupation.
What is the cost of living there?
Median rent in Dallas is $1,472 a month and median household income $70,518 (ACS 2020–2024).
How old is this listing?
It was posted on 2026-11-02 (7 days ago). Jobs older than 90 days are not shown.
Are there similar jobs?
Yes: browse data, analytics and ai jobs in Texas.
Sources and terms
Job data: The Muse public API (listing dated 2026-11-02). The job disappears from this site when it disappears from the source.
Wages and projections: BLS OEWS (May 2025) and Employment Projections 2025–35.
City and county figures: Census Bureau ACS 2020–2024, BEA, BLS QCEW and LAUS, NASA POWER climatology; distances from Census Gazetteer coordinates.
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