AI Data Engineer Visa Sponsorship Jobs in Maryland
Maryland's AI data engineer job market centers on the Baltimore-Washington corridor, where federal contractors like Booz Allen Hamilton, Leidos, and SAIC drive consistent demand alongside biotech firms in the BioHealth Capital Region. Rockville, Bethesda, and Columbia are key hiring hubs, and many employers in this corridor have established visa sponsorship programs for qualified candidates.
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GenAI Full Stack Developer - Senior Consultant
Deloitte's Audit & Assurance professionals help organizations navigate business risks and opportunities - across financial, operational, information technology (IT), business, and regulatory areas - to build resilience and accelerate performance. In this role, you'll design and deliver end-to-end Generative AI (GenAI) solutions - including Retrieval-Augmented Generation (RAG) and agentic AI - that are production-ready, scalable, and aligned to enterprise risk and governance expectations.
Recruiting for this role ends on
Work you'll do
- Lead business and technical requirements elicitation with client stakeholders; own end-to-end gap analysis; translate needs into solution architecture, detailed technical specifications, and delivery-ready backlog artifacts.
- Drive design, build, test, and deployment of full-stack Generative AI (GenAI) applications (web user interface (UI), backend services, and data/model components); ensure non-functional requirements (security, performance, reliability) are met.
- Own end-to-end retrieval-augmented generation (RAG) implementations (ingestion, chunking, embedding, indexing, retrieval, orchestration); define prompt engineering standards and evaluation harnesses to measure quality and reduce hallucinations.
- Architect agentic AI workflows (tool-using agents, multi-step orchestration, multi-agent patterns); integrate into enterprise platforms and business processes with appropriate controls, auditability, and human-in-the-loop checkpoints.
- Lead model training, fine-tuning, and validation; establish evaluation approaches and key performance indicators (KPIs) for quality, robustness, bias/safety, and cost/latency; run benchmarking and iteration cycles to meet acceptance criteria.
- Own API and integration service design; deliver scalable RESTful interfaces; coordinate integration with downstream/upstream systems, identity and access management (IAM), and operational workflows.
- Lead extract, transform, load (ETL) and data engineering pipeline delivery to curate governed datasets for GenAI solutions; partner with data governance and risk teams on lineage, access controls, and data quality standards.
- Operationalize deployments using containerized patterns and cloud services; implement monitoring/observability (performance, cost, drift, quality signals) and drive continuous improvement through incident learnings and release management.
- Advise on emerging GenAI models, frameworks, and toolkits; prototype and recommend options with explicit tradeoffs across value, delivery effort, risk, compliance, and total cost of ownership (TCO).
- Collaborate with cross-functional teams (product, engineering, data, risk, and stakeholders) to deliver adoption-ready solutions and documentation.
The team
Our team culture is collaborative and encourages team members to take initiative and seek on-the-job learning opportunities. Audit & Assurance services are focused on engagements related to independent External Audit services, Accounting, Controls & Reporting Advisory, and Specialized Assurance & Sustainability. We bring together the diverse skills and industry experience of our people, leading-edge technology, and a global network to deliver high-quality audits of financial statements and internal controls over financial reporting, along with assurance reports and valuable advice and insights across the corporate reporting landscape. Learn more about Deloitte Audit & Assurance.
Qualifications
Required:
- Bachelor's degree (or equivalent) in Computer Science, Engineering, Data Science, or a related field (advanced degree a plus).
- 4+ years of experience in software engineering, full stack development, and/or AI/ML solution delivery.
- Python programming (production-grade) and strong SQL.
- Natural Language Processing (NLP) applied to GenAI solutions.
- Agentic AI design/implementation, including LangChain, LangGraph, and LlamaIndex.
- Hands-on experience with RAG architectures and implementation.
- Strong prompt engineering (design, iteration, and evaluation).
- Experience with vector databases (e.g., Pinecone, Chroma, FAISS or similar) and embedding-based retrieval.
- Experience with GenAI model build: training, fine-tuning, and validation; practical LLM evaluation using common metrics.
- Experience with model deployment (serving, monitoring, iteration) and production hardening.
- Experience with containers (e.g., Docker) and scalable runtime patterns.
- Experience building ETL pipelines and data engineering solutions (data quality, preprocessing, and curation).
- API development and integration (RESTful services); backend development using FastAPI (or equivalent).
- Full stack web development with JavaScript/TypeScript.
- Proficiency with HTML/CSS and preprocessors (SASS/LESS).
- Experience with front-end frameworks (React, Angular, or Vue).
- Working knowledge of UI/UX design principles (accessibility, usability, responsive design).
- Experience with cloud AI/ML services across Azure, AWS, and GCP, including Vertex AI.
- You should reside within a commutable distance of your assigned office with the ability to commute daily, if required.
- You can expect to co-locate on average 3 times a week with variations based on types of work/projects and client locations.
- Ability to travel up to 50%, on average, based on the work you do and the clients/sectors you serve.
- Limited immigration sponsorship may be available.
Preferred:
- Experience with deep learning frameworks (e.g., TensorFlow, PyTorch, Keras).
- Familiarity with AI/GenAI ethics, governance, and responsible AI implementation practices.
- Cloud certification (AWS, Azure, or GCP) and/or AI/ML certification.
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 $124,658 to $179,431.
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

GenAI Full Stack Developer - Senior Consultant
Deloitte's Audit & Assurance professionals help organizations navigate business risks and opportunities - across financial, operational, information technology (IT), business, and regulatory areas - to build resilience and accelerate performance. In this role, you'll design and deliver end-to-end Generative AI (GenAI) solutions - including Retrieval-Augmented Generation (RAG) and agentic AI - that are production-ready, scalable, and aligned to enterprise risk and governance expectations.
Recruiting for this role ends on
Work you'll do
- Lead business and technical requirements elicitation with client stakeholders; own end-to-end gap analysis; translate needs into solution architecture, detailed technical specifications, and delivery-ready backlog artifacts.
- Drive design, build, test, and deployment of full-stack Generative AI (GenAI) applications (web user interface (UI), backend services, and data/model components); ensure non-functional requirements (security, performance, reliability) are met.
- Own end-to-end retrieval-augmented generation (RAG) implementations (ingestion, chunking, embedding, indexing, retrieval, orchestration); define prompt engineering standards and evaluation harnesses to measure quality and reduce hallucinations.
- Architect agentic AI workflows (tool-using agents, multi-step orchestration, multi-agent patterns); integrate into enterprise platforms and business processes with appropriate controls, auditability, and human-in-the-loop checkpoints.
- Lead model training, fine-tuning, and validation; establish evaluation approaches and key performance indicators (KPIs) for quality, robustness, bias/safety, and cost/latency; run benchmarking and iteration cycles to meet acceptance criteria.
- Own API and integration service design; deliver scalable RESTful interfaces; coordinate integration with downstream/upstream systems, identity and access management (IAM), and operational workflows.
- Lead extract, transform, load (ETL) and data engineering pipeline delivery to curate governed datasets for GenAI solutions; partner with data governance and risk teams on lineage, access controls, and data quality standards.
- Operationalize deployments using containerized patterns and cloud services; implement monitoring/observability (performance, cost, drift, quality signals) and drive continuous improvement through incident learnings and release management.
- Advise on emerging GenAI models, frameworks, and toolkits; prototype and recommend options with explicit tradeoffs across value, delivery effort, risk, compliance, and total cost of ownership (TCO).
- Collaborate with cross-functional teams (product, engineering, data, risk, and stakeholders) to deliver adoption-ready solutions and documentation.
The team
Our team culture is collaborative and encourages team members to take initiative and seek on-the-job learning opportunities. Audit & Assurance services are focused on engagements related to independent External Audit services, Accounting, Controls & Reporting Advisory, and Specialized Assurance & Sustainability. We bring together the diverse skills and industry experience of our people, leading-edge technology, and a global network to deliver high-quality audits of financial statements and internal controls over financial reporting, along with assurance reports and valuable advice and insights across the corporate reporting landscape. Learn more about Deloitte Audit & Assurance.
Qualifications
Required:
- Bachelor's degree (or equivalent) in Computer Science, Engineering, Data Science, or a related field (advanced degree a plus).
- 4+ years of experience in software engineering, full stack development, and/or AI/ML solution delivery.
- Python programming (production-grade) and strong SQL.
- Natural Language Processing (NLP) applied to GenAI solutions.
- Agentic AI design/implementation, including LangChain, LangGraph, and LlamaIndex.
- Hands-on experience with RAG architectures and implementation.
- Strong prompt engineering (design, iteration, and evaluation).
- Experience with vector databases (e.g., Pinecone, Chroma, FAISS or similar) and embedding-based retrieval.
- Experience with GenAI model build: training, fine-tuning, and validation; practical LLM evaluation using common metrics.
- Experience with model deployment (serving, monitoring, iteration) and production hardening.
- Experience with containers (e.g., Docker) and scalable runtime patterns.
- Experience building ETL pipelines and data engineering solutions (data quality, preprocessing, and curation).
- API development and integration (RESTful services); backend development using FastAPI (or equivalent).
- Full stack web development with JavaScript/TypeScript.
- Proficiency with HTML/CSS and preprocessors (SASS/LESS).
- Experience with front-end frameworks (React, Angular, or Vue).
- Working knowledge of UI/UX design principles (accessibility, usability, responsive design).
- Experience with cloud AI/ML services across Azure, AWS, and GCP, including Vertex AI.
- You should reside within a commutable distance of your assigned office with the ability to commute daily, if required.
- You can expect to co-locate on average 3 times a week with variations based on types of work/projects and client locations.
- Ability to travel up to 50%, on average, based on the work you do and the clients/sectors you serve.
- Limited immigration sponsorship may be available.
Preferred:
- Experience with deep learning frameworks (e.g., TensorFlow, PyTorch, Keras).
- Familiarity with AI/GenAI ethics, governance, and responsible AI implementation practices.
- Cloud certification (AWS, Azure, or GCP) and/or AI/ML certification.
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 $124,658 to $179,431.
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
AI Data Engineer Job Roles in Maryland
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Search AI Data Engineer Jobs in MarylandAI Data Engineer Jobs in Maryland: Frequently Asked Questions
Which companies sponsor visas for AI data engineers in Maryland?
Federal contractors and defense technology firms are among the most active sponsors in Maryland, including Booz Allen Hamilton, Leidos, SAIC, and Northrop Grumman. In the commercial sector, biotech and health IT companies such as Veeva Systems and various NIH-adjacent research organizations have also sponsored AI data engineer roles. Sponsorship availability varies by role, clearance requirements, and current headcount needs.
Which visa types are most common for AI data engineer roles in Maryland?
The H-1B is the most common visa category for AI data engineers in Maryland, as the role typically qualifies as a specialty occupation requiring at least a bachelor's degree in computer science, data science, or a related field. Candidates already holding L-1B, O-1, or F-1 OPT status may also find pathways through Maryland employers, particularly at larger contractors with established immigration support infrastructure.
How to find ai data engineer visa sponsorship jobs in Maryland?
Migrate Mate filters job listings specifically for visa sponsorship eligibility, making it straightforward to browse AI data engineer openings in Maryland without sorting through roles that won't support international candidates. You can narrow results to Maryland employers across the Baltimore-Washington corridor, including federal contractors, health IT firms, and research-driven organizations that have a track record of sponsoring technical roles.
Which cities in Maryland have the most AI data engineer sponsorship jobs?
Bethesda, Rockville, and Columbia account for a significant share of Maryland's AI data engineer sponsorship activity, largely due to concentration of federal agencies, contractors, and biotech companies in Montgomery County and Howard County. Baltimore also has a growing presence, driven by academic medical centers like Johns Hopkins and University of Maryland Medical System, which increasingly hire data engineering talent for clinical AI initiatives.
Are there state-specific considerations for AI data engineers seeking sponsorship in Maryland?
Maryland's high concentration of federal contractors introduces a clearance dimension that affects international candidates. Many federal contract roles require U.S. citizenship or permanent residency for security clearance eligibility, which can limit sponsorship opportunities at those employers specifically. Candidates without clearance eligibility often find better pathways through commercial biotech, health IT, or academic research employers operating in the state's BioHealth Capital Region.
What is the prevailing wage for sponsored ai data engineer jobs in Maryland?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.
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