AI Data Engineer Jobs at Deloitte with Visa Sponsorship
Deloitte hires AI Data Engineers across its consulting and technology practices, working on client-facing data infrastructure, machine learning pipelines, and enterprise AI solutions. The firm has a well-established visa sponsorship process and works with international candidates across multiple nonimmigrant and immigrant visa categories.
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Get Access To All JobsAI Data Engineer - Manager
Our Human Capital practice is at the forefront of transforming the nature of work. As converging forces reshape industries, our team uniquely addresses the complexities of work, workforce, and workplace dynamics. We leverage sector-specific insights and cross-domain perspectives to help organizations tackle their most challenging workforce issues and align talent strategies with their strategic visions. Our practice is renowned for making work better for humans and humans better at work. Be part of this exciting era of change and join us on this transformative journey.
Recruiting for this role ends on August 30, 2026
Work You'll Do:
The AI Data Engineer will lead the data architecture and engineering delivery that enables AI/ML/GenAI solutions, ensuring data is trusted, secure, observable, and scalable from ingestion through consumption. You will design and operationalize modern data and retrieval foundations to support LLM-powered applications (e.g., Claude, GPT/Codex, Gemini) including patterns such as RAG, embeddings, vector search, and governed access to structured and unstructured data. You will manage day-to-day delivery with an onshore/offshore team, partnering with data science, ML engineering, and product stakeholders to translate use cases into production-ready pipelines and platforms with strong data governance, lineage, quality controls, and monitoring. This role blends hands-on technical leadership with delivery management and team development, driving consistent engineering standards and measurable outcomes in client environments.
Strategic Alignment and Vision
Help define the AI/ML/GenAI technical direction and vision, ensuring alignment with strategic goals and digital transformation efforts.
Translate the vision of business leaders into realistic technical implementations, while identifying misaligned initiatives and impractical use cases
Architectural Design
* Design end-to-end AI architectures, from data ingestion to model deployment, integrating with cloud and on-premises systems.
Design and Technology Selection
Select appropriate technologies from a pool of open-source and commercial offerings, considering deployment models and integration with existing tools.
Understand and contribute to MLOps and LLMOps, focusing on operational capabilities and infrastructure to deploy and manage machine learning models and large language models.
Research and Development
Conduct research to provide technical solutions to scale AI/ML powered features for real-world challenges, making trade-offs based on quality, scalability, performance, and cost.
Lead the development of AI models (e.g., machine learning, natural language processing, computer vision) and implement scalable AI solutions.
Collaboration and Stakeholder Engagement
Collaborate with Enterprise, Application, Data & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot use cases and discuss best design.
Gather inputs from multiple stakeholders to align technical implementation with existing and future requirements.
Consulting & Advisory
* Serve as a technical advisor to leadership, providing insights on AI trends, potential business impacts, and implementation best practices.
Operational Excellence and Continuous Improvement
Be responsible for the successful execution of AI-powered applications using agile methodology.
Audit AI tools and practices across data, models and software engineering, focusing on continuous improvement and feedback mechanisms.
* Contribute to standardizing CI/CD pipelines, user and service roles, and container creation, model consumption, testing, and deployment methodology based on business and security requirements.
Risk Management and Ethical Considerations
Work closely with security and risk leaders to foresee and mitigate risks, ensuring ethical AI implementation and compliance with upcoming regulations.
Address potential issues such as training data poisoning, AI model theft, and adversarial samples.
Product Strategy and Business Understanding
Help AI product managers and business stakeholders understand the potential and limitations of AI when planning new products.
Break down client problems and bring an understanding of leading technology, analytics methods, tools, and operating model approaches.
Tool Development and Data Management
Build tools and capabilities that assist with data ingestion, feature engineering, data management, and organization.
Design, implement, and maintain distributed computing solutions for data processing and model training, ensuring the security, scalability, and reliability of machine learning infrastructure.
The Team
Our Insights, Innovation & Operate Offering is designed to enhance key aspects of our clients' businesses by leveraging cutting-edge technology, data, and a blend of deep technical and human expertise. We innovate and deliver creative, industry-specific solutions that streamline operations and accelerate speed-to-value.
Required Qualifications:
Bachelor's degree in Computer Science, Statistics, Data Science, Information Systems or related field.
6+ years of consulting experience leading delivery teams, including onshore and offshore team members
6+ years of experience gathering non-functional requirements and defining application architecture frameworks, including validation and testing deliverables
5+ years of experience working in an AI environment
5+ years of experience translating requirements into client ready design documents
5+ years of experience in software application architecture analysis, design, and delivery
5+ years of experience executing full system development life cycle implementations
Ability to travel 0-25%, on average, based on the work you do and the clients and industries/sectors you serve.
* Limited immigration sponsorship may be available.
Preferred Qualifications:
Advanced degrees such as Masters or PhD are preferred
Certifications in AI/ML technologies and Cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Azure AI Engineer, Azure Data Scientist, or Azure Solutions Architect
5+ years of experience in Data Science, Statistics, and Machine Learning
5+ years of experience in Generative AI/LLMs, preferably experienced in delivering and productionizing
5+ years of experience in machine learning model development, natural language processing, and data analysis; Experienced in Supervised and Unsupervised learning, feature engineering, model training, and deployment
5+ year of experience in implementing cloud-based AI/ML workloads on any of AWS, Microsoft and Azure.
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 $130,800-241,000.
Possible Locations:
Atlanta, Austin, Baltimore, Boston, Charlotte, Chicago, Cincinnati, Cleveland, Columbus, Costa Mesa, Dallas, Denver, Detroit, Hartford, Houston, Indianapolis, Jacksonville, Kansas City, Las Vegas, Los Angeles, McLean, Miami, Milwaukee, Nashville, New Orleans, New York, Philadelphia, Pittsburgh, Portland, Raleigh, Richmond, Sacramento, San Antonio, San Diego, San Francisco, San Jose, Seattle, St. Louis, Stamford, Tampa, Tempe
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.
Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html
For more information about Human Capital, visit our landing page at: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-human-capital-consulting-jobs.html
HCFY26 #IIOFY26
AI Data Engineer - Manager
Our Human Capital practice is at the forefront of transforming the nature of work. As converging forces reshape industries, our team uniquely addresses the complexities of work, workforce, and workplace dynamics. We leverage sector-specific insights and cross-domain perspectives to help organizations tackle their most challenging workforce issues and align talent strategies with their strategic visions. Our practice is renowned for making work better for humans and humans better at work. Be part of this exciting era of change and join us on this transformative journey.
Recruiting for this role ends on August 30, 2026
Work You'll Do:
The AI Data Engineer will lead the data architecture and engineering delivery that enables AI/ML/GenAI solutions, ensuring data is trusted, secure, observable, and scalable from ingestion through consumption. You will design and operationalize modern data and retrieval foundations to support LLM-powered applications (e.g., Claude, GPT/Codex, Gemini) including patterns such as RAG, embeddings, vector search, and governed access to structured and unstructured data. You will manage day-to-day delivery with an onshore/offshore team, partnering with data science, ML engineering, and product stakeholders to translate use cases into production-ready pipelines and platforms with strong data governance, lineage, quality controls, and monitoring. This role blends hands-on technical leadership with delivery management and team development, driving consistent engineering standards and measurable outcomes in client environments.
Strategic Alignment and Vision
Help define the AI/ML/GenAI technical direction and vision, ensuring alignment with strategic goals and digital transformation efforts.
Translate the vision of business leaders into realistic technical implementations, while identifying misaligned initiatives and impractical use cases
Architectural Design
* Design end-to-end AI architectures, from data ingestion to model deployment, integrating with cloud and on-premises systems.
Design and Technology Selection
Select appropriate technologies from a pool of open-source and commercial offerings, considering deployment models and integration with existing tools.
Understand and contribute to MLOps and LLMOps, focusing on operational capabilities and infrastructure to deploy and manage machine learning models and large language models.
Research and Development
Conduct research to provide technical solutions to scale AI/ML powered features for real-world challenges, making trade-offs based on quality, scalability, performance, and cost.
Lead the development of AI models (e.g., machine learning, natural language processing, computer vision) and implement scalable AI solutions.
Collaboration and Stakeholder Engagement
Collaborate with Enterprise, Application, Data & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot use cases and discuss best design.
Gather inputs from multiple stakeholders to align technical implementation with existing and future requirements.
Consulting & Advisory
* Serve as a technical advisor to leadership, providing insights on AI trends, potential business impacts, and implementation best practices.
Operational Excellence and Continuous Improvement
Be responsible for the successful execution of AI-powered applications using agile methodology.
Audit AI tools and practices across data, models and software engineering, focusing on continuous improvement and feedback mechanisms.
* Contribute to standardizing CI/CD pipelines, user and service roles, and container creation, model consumption, testing, and deployment methodology based on business and security requirements.
Risk Management and Ethical Considerations
Work closely with security and risk leaders to foresee and mitigate risks, ensuring ethical AI implementation and compliance with upcoming regulations.
Address potential issues such as training data poisoning, AI model theft, and adversarial samples.
Product Strategy and Business Understanding
Help AI product managers and business stakeholders understand the potential and limitations of AI when planning new products.
Break down client problems and bring an understanding of leading technology, analytics methods, tools, and operating model approaches.
Tool Development and Data Management
Build tools and capabilities that assist with data ingestion, feature engineering, data management, and organization.
Design, implement, and maintain distributed computing solutions for data processing and model training, ensuring the security, scalability, and reliability of machine learning infrastructure.
The Team
Our Insights, Innovation & Operate Offering is designed to enhance key aspects of our clients' businesses by leveraging cutting-edge technology, data, and a blend of deep technical and human expertise. We innovate and deliver creative, industry-specific solutions that streamline operations and accelerate speed-to-value.
Required Qualifications:
Bachelor's degree in Computer Science, Statistics, Data Science, Information Systems or related field.
6+ years of consulting experience leading delivery teams, including onshore and offshore team members
6+ years of experience gathering non-functional requirements and defining application architecture frameworks, including validation and testing deliverables
5+ years of experience working in an AI environment
5+ years of experience translating requirements into client ready design documents
5+ years of experience in software application architecture analysis, design, and delivery
5+ years of experience executing full system development life cycle implementations
Ability to travel 0-25%, on average, based on the work you do and the clients and industries/sectors you serve.
* Limited immigration sponsorship may be available.
Preferred Qualifications:
Advanced degrees such as Masters or PhD are preferred
Certifications in AI/ML technologies and Cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Azure AI Engineer, Azure Data Scientist, or Azure Solutions Architect
5+ years of experience in Data Science, Statistics, and Machine Learning
5+ years of experience in Generative AI/LLMs, preferably experienced in delivering and productionizing
5+ years of experience in machine learning model development, natural language processing, and data analysis; Experienced in Supervised and Unsupervised learning, feature engineering, model training, and deployment
5+ year of experience in implementing cloud-based AI/ML workloads on any of AWS, Microsoft and Azure.
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 $130,800-241,000.
Possible Locations:
Atlanta, Austin, Baltimore, Boston, Charlotte, Chicago, Cincinnati, Cleveland, Columbus, Costa Mesa, Dallas, Denver, Detroit, Hartford, Houston, Indianapolis, Jacksonville, Kansas City, Las Vegas, Los Angeles, McLean, Miami, Milwaukee, Nashville, New Orleans, New York, Philadelphia, Pittsburgh, Portland, Raleigh, Richmond, Sacramento, San Antonio, San Diego, San Francisco, San Jose, Seattle, St. Louis, Stamford, Tampa, Tempe
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.
Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html
For more information about Human Capital, visit our landing page at: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-human-capital-consulting-jobs.html
HCFY26 #IIOFY26
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Get Access To All JobsTips for Finding AI Data Engineer Jobs at Deloitte Jobs
Align your portfolio to client delivery work
Deloitte's AI Data Engineer roles are consulting-oriented, not pure product engineering. Highlight experience delivering data pipelines or ML infrastructure for external clients or stakeholders, not just internal tooling. Projects with measurable business outcomes translate best.
Verify your role qualifies as a specialty occupation
USCIS requires that your specific job duties demand a bachelor's degree in a directly related field. For AI Data Engineering at a consulting firm, make sure your offer letter specifies technical requirements precisely. Vague duty descriptions have caused H-1B denials even at large sponsors.
Target Deloitte's federal and regulated industry practices
Deloitte's Government and Public Services and Financial Services practices frequently staff AI and data roles on long-running client engagements. These practices have more predictable hiring cycles and tend to initiate sponsorship conversations earlier in the offer process.
Clarify sponsorship scope before accepting an offer
Ask whether Deloitte will support both the initial nonimmigrant visa and future Green Card filing through PERM. Some practice groups move faster than others on immigrant visa sponsorship, and understanding the timeline upfront protects your long-term status planning.
Use Migrate Mate to find open AI Data Engineer roles at Deloitte
Deloitte posts AI Data Engineer positions across multiple portals and practice areas, making it hard to track what's actively sponsoring. Search Migrate Mate to filter specifically for Deloitte roles that have a verified visa sponsorship history for this function.
Prepare your credentials for E-3 or H-1B1 if eligible
Australian and Singaporean or Chilean nationals can pursue the E-3 or H-1B1 respectively, both of which skip the H-1B lottery. Deloitte sponsors both categories. Have your degree equivalency documentation and a certified Labor Condition Application from DOL ready before your interview stage concludes.
AI Data Engineer at Deloitte jobs are hiring across the US. Find yours.
Find AI Data Engineer at Deloitte JobsFrequently Asked Questions
Does Deloitte sponsor H-1B visas for AI Data Engineers?
Yes, Deloitte sponsors H-1B visas for AI Data Engineers. The firm participates in the annual H-1B lottery each April for cap-subject candidates and also files for cap-exempt situations where eligible. Because H-1B selection is not guaranteed, Deloitte also supports alternative visa categories depending on the candidate's nationality and situation.
Which visa types does Deloitte commonly use for AI Data Engineer roles?
Deloitte sponsors H-1B, H-1B1, and E-3 visas for AI Data Engineers depending on nationality. For longer-term pathways, the firm also pursues EB-2 and EB-3 immigrant visa sponsorship through the PERM labor certification process. Australian candidates are often directed toward the E-3, which has no lottery and can move faster than H-1B.
How do I apply for AI Data Engineer jobs at Deloitte?
You can apply directly through Deloitte's careers portal or find open AI Data Engineer positions filtered by visa sponsorship eligibility on Migrate Mate. Deloitte's hiring process typically includes an initial recruiter screen, technical assessments covering data engineering and AI concepts, and panel interviews with practice leads. Sponsorship discussions usually happen after a verbal offer is extended.
What qualifications does Deloitte expect for AI Data Engineer roles?
Deloitte typically looks for a bachelor's or master's degree in computer science, data science, engineering, or a closely related field. Hands-on experience with cloud data platforms such as AWS, Azure, or GCP, combined with proficiency in Python, SQL, and ML pipeline tooling, is expected. Consulting experience or the ability to communicate technical work to non-technical clients is a strong differentiator.
How do I manage H-1B timing if I receive an offer from Deloitte?
If you need H-1B sponsorship, Deloitte must file your petition during the April registration window for an October 1 start date. If you're on OPT with a STEM extension, you have up to 36 months of work authorization to bridge the gap. Deloitte's immigration team typically coordinates filing through an outside immigration counsel once an offer is accepted.
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