AI Data Engineer Jobs in USA with Visa Sponsorship
AI Data Engineers are in high demand from H-1B visa and O-1 visa sponsors across tech, finance, and healthcare. The role qualifies as a specialty occupation, and employers regularly file LCAs under computer science and data engineering job codes. For detailed occupation requirements, see the O*NET profile.
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Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible.
Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives.
Position Summary:
Join the Data Discovery Services team within Enterprise Data Platforms, where we deliver and maintain the data foundation platforms that power discovery, search, and data accessibility across the Bristol Myers Squibb enterprise. We run multiple search and discovery services used across the company - and we're building the next generation of AI-powered discovery on top of them. Our work makes enterprise data findable, accessible, and actionable for teams across the organization. At the core of this is a semantic knowledge layer - metadata, taxonomies, and relationships that describe what data means and how it connects - curated as a data inventory that helps AI work reliably across the enterprise. This is a high-impact team where engineering, search, and applied AI come together to solve real problems at scale.
As an AI / Data Engineer, you'll be a hands-on Python developer building the pipelines and integrations that make enterprise data more discoverable. Your primary focus is data engineering - pipelines, metadata enrichment, transformations, and platform integrations. You'll also contribute to search and AI-powered retrieval as you grow into the role. Working alongside data engineers, search engineers, and data scientists, this is a hands-on engineering role - you'll write code, build pipelines, ship features, and own what you deliver.
Why Join Us?
- Work with a modern stack - Databricks, Amazon Web Services (AWS), OpenSearch, vector search, semantic knowledge layers, graph databases, and AI agents.
- Build real AI-powered discovery capabilities, not proofs of concept.
- Grow your skills across data engineering, search, and applied AI on the same team.
- Use AI-assisted development tools (Claude, Copilot) in your daily workflow.
- Contribute to open-source projects and shared accelerators.
- Clear path to grow into senior engineering, search specialization, or AI engineering roles.
- Make enterprise data findable and accessible for teams working to improve patient outcomes.
Job Responsibilities:
As an AI / Data Engineer, you'll be a hands-on Python developer building the pipelines and integrations that make enterprise data more discoverable. Your primary focus is data engineering — pipelines, metadata enrichment, transformations, and platform integrations.
You'll also contribute to search and AI-powered retrieval as you grow into the role. Working alongside data engineers, search engineers, and data scientists, this is a hands-on engineering role — you'll write code, build pipelines, ship features, and own what you deliver.
- Build and maintain Python pipelines that pull metadata from enterprise data catalogs, enrich it with taxonomy tags and ownership information, and publish it to the discovery platform.
- Tune and optimize search indexes - adjust analyzers, boost fields, and test queries - to ensure results match what users need.
- Build a semantic knowledge layer - chunking documents, generating vector embeddings, and enriching them with semantic knowledge metadata - to grow a data inventory that supports retrieval-augmented generation (RAG) and helps AI systems and large language models (LLMs) find and use the right context.
- Maintain integrations that sync ontology and taxonomy changes into the discovery platform, so classifications stay current.
- Investigate and resolve data pipeline issues across Databricks and AWS Glue, trace root causes through metadata enrichment flows, and add data quality checks to prevent recurrence.
- Build API endpoints and Model Context Protocol (MCP) servers that expose search and metadata capabilities to applications and AI agents.
- Design metadata pipelines that map cross-domain dataset relationships and add them to the cross-domain join catalog with confidence scores.
- Analyze search patterns, capture user feedback, and improve the discovery experience so the system learns and improves over time.
Qualifications & Experience:
Required
- Bachelor’s degree in computer science, Data Science, Information Science, Engineering, or a related field. Master's degree preferred.
- Demonstrated proficiency in data engineering, software engineering, or a related technical discipline, with a track record of delivering production data pipelines.
- Proficient Python skills - this is your primary language day-to-day.
- Proficiency in Structured Query Language (SQL).
- Experience with Databricks and AWS Glue for data pipelines and transformations.
- Solid data engineering fundamentals: extract-transform-load (ETL/ELT) patterns, data modeling, data quality, and pipeline orchestration.
- Familiarity with AWS cloud services (S3, Lambda, API Gateway, Glue).
- Experience with OpenSearch or Elasticsearch.
- Understanding of metadata management and data cataloging concepts.
- Effective problem-solving skills and willingness to learn.
- Good communication skills and ability to work collaboratively in a team.
Preferred Qualifications:
- Experience with semantic knowledge layers, RAG patterns, vector search technologies, and building AI-ready data inventories.
- Familiarity with semantic search, embeddings, chunking strategies, relevance tuning, and semantic knowledge metadata (entity relationships, taxonomies, context enrichment).
- Exposure to AI agent patterns, MCP, or large language model orchestration frameworks.
- Experience with ontology or taxonomy technologies (such as Turtle, Resource Description Framework, Web Ontology Language, or SPARQL query language) or management platforms.
- Familiarity with graph databases or knowledge graph technologies.
- Experience with metadata enrichment, data lineage, or data quality frameworks.
- Exposure to Azure OpenAI, Google Vertex AI, or Amazon Bedrock.
- Experience with Docker, Elastic Container Service (ECS), or CloudFormation.
- Prior exposure to pharma or life sciences.
If you come across a role that intrigues you but doesn’t perfectly line up with your resume, we encourage you to apply anyway. You could be one step away from work that will transform your life and career.
Compensation Overview:
Princeton - NJ - US: $87,810 - $106,399
The starting compensation range(s) for this role are listed above for a full-time employee (FTE) basis. Additional incentive cash and stock opportunities (based on eligibility) may be available. The starting pay rate takes into account characteristics of the job, such as required skills, where the job is performed, the employee’s work schedule, job-related knowledge, and experience. Final, individual compensation will be decided based on demonstrated experience.
Eligibility for specific benefits listed on our careers site may vary based on the job and location.
Benefit offerings are subject to the terms and conditions of the applicable plans in effect at the time and may require enrollment. Our benefits include:
- Health Coverage: Medical, pharmacy, dental, and vision care.
- Wellbeing Support: Programs such as BMS Well-Being Account, BMS Living Life Better, and Employee Assistance Programs (EAP).
- Financial Well-being and Protection: 401(k) plan, short- and long-term disability, life insurance, accident insurance, supplemental health insurance, business travel protection, personal liability protection, identity theft benefit, legal support, and survivor support.
Work-life benefits include:
Paid Time Off
- US Exempt Employees: flexible time off (unlimited, with manager approval, 11 paid national holidays (not applicable to employees in Phoenix, AZ, Puerto Rico or Rayzebio employees)
- Phoenix, AZ, Puerto Rico and Rayzebio Exempt, Non-Exempt, Hourly Employees: 160 hours annual paid vacation for new hires with manager approval, 11 national holidays, and 3 optional holidays
Based on eligibility*, additional time off for employees may include unlimited paid sick time, up to 2 paid volunteer days per year, summer hours flexibility, leaves of absence for medical, personal, parental, caregiver, bereavement, and military needs and an annual Global Shutdown between Christmas and New Years Day.
All global employees full and part-time who are actively employed at and paid directly by BMS at the end of the calendar year are eligible to take advantage of the Global Shutdown.
Eligibility Disclosure: The summer hours program is for United States (U.S.) office-based employees due to the unique nature of their work. Summer hours are generally not available for field sales and manufacturing operations and may also be limited for the capability centers. Employees in remote-by-design or lab-based roles may be eligible for summer hours, depending on the nature of their work, and should discuss eligibility with their manager. Employees covered under a collective bargaining agreement should consult that document to determine if they are eligible. Contractors, leased workers and other service providers are not eligible to participate in the program.
Uniquely Interesting Work, Life-changing Careers
With a single vision as inspiring as “Transforming patients’ lives through science™”, every BMS employee plays an integral role in work that goes far beyond ordinary. Each of us is empowered to apply our individual talents and unique perspectives in a supportive culture, promoting global participation in clinical trials, while our shared values of passion, innovation, urgency, accountability, inclusion and integrity bring out the highest potential of each of our colleagues.
On-site Protocol
BMS has an occupancy structure that determines where an employee is required to conduct their work. This structure includes site-essential, site-by-design, field-based and remote-by-design jobs. The occupancy type that you are assigned is determined by the nature and responsibilities of your role:
Site-essential roles require 100% of shifts onsite at your assigned facility. Site-by-design roles may be eligible for a hybrid work model with at least 50% onsite at your assigned facility. For these roles, onsite presence is considered an essential job function and is critical to collaboration, innovation, productivity, and a positive Company culture. For field-based and remote-by-design roles the ability to physically travel to visit customers, patients or business partners and to attend meetings on behalf of BMS as directed is an essential job function.
Supporting People with Disabilities
BMS is dedicated to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace accommodations/adjustments and ongoing support in their roles. Applicants can request a reasonable workplace accommodation/adjustment prior to accepting a job offer. If you require reasonable accommodations/adjustments in completing this application, or in any part of the recruitment process, direct your inquiries to adastaffingsupport@bms.com. Visit careers.bms.com/eeo-accessibility to access our complete Equal Employment Opportunity statement.
Candidate Rights
BMS will consider for employment qualified applicants with arrest and conviction records, pursuant to applicable laws in your area.
If you live in or expect to work from Los Angeles County if hired for this position, please visit this page for important additional information.
Data Protection
We will never request payments, financial information, or social security numbers during our application or recruitment process. Learn more about protecting yourself.
Any data processed in connection with role applications will be treated in accordance with applicable data privacy policies and regulations.
If you believe that the job posting is missing information required by local law or incorrect in any way, please contact BMS at TAEnablement@bms.com. Please provide the Job Title and Requisition number so we can review. Communications related to your application should not be sent to this email and you will not receive a response. Inquiries related to the status of your application should be directed to Chat with Ripley.
R1604590 : AI & Data Engineer, Data Discovery Services
Working with Us
Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible.
Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives.
Position Summary:
Join the Data Discovery Services team within Enterprise Data Platforms, where we deliver and maintain the data foundation platforms that power discovery, search, and data accessibility across the Bristol Myers Squibb enterprise. We run multiple search and discovery services used across the company - and we're building the next generation of AI-powered discovery on top of them. Our work makes enterprise data findable, accessible, and actionable for teams across the organization. At the core of this is a semantic knowledge layer - metadata, taxonomies, and relationships that describe what data means and how it connects - curated as a data inventory that helps AI work reliably across the enterprise. This is a high-impact team where engineering, search, and applied AI come together to solve real problems at scale.
As an AI / Data Engineer, you'll be a hands-on Python developer building the pipelines and integrations that make enterprise data more discoverable. Your primary focus is data engineering - pipelines, metadata enrichment, transformations, and platform integrations. You'll also contribute to search and AI-powered retrieval as you grow into the role. Working alongside data engineers, search engineers, and data scientists, this is a hands-on engineering role - you'll write code, build pipelines, ship features, and own what you deliver.
Why Join Us?
- Work with a modern stack - Databricks, Amazon Web Services (AWS), OpenSearch, vector search, semantic knowledge layers, graph databases, and AI agents.
- Build real AI-powered discovery capabilities, not proofs of concept.
- Grow your skills across data engineering, search, and applied AI on the same team.
- Use AI-assisted development tools (Claude, Copilot) in your daily workflow.
- Contribute to open-source projects and shared accelerators.
- Clear path to grow into senior engineering, search specialization, or AI engineering roles.
- Make enterprise data findable and accessible for teams working to improve patient outcomes.
Job Responsibilities:
As an AI / Data Engineer, you'll be a hands-on Python developer building the pipelines and integrations that make enterprise data more discoverable. Your primary focus is data engineering — pipelines, metadata enrichment, transformations, and platform integrations.
You'll also contribute to search and AI-powered retrieval as you grow into the role. Working alongside data engineers, search engineers, and data scientists, this is a hands-on engineering role — you'll write code, build pipelines, ship features, and own what you deliver.
- Build and maintain Python pipelines that pull metadata from enterprise data catalogs, enrich it with taxonomy tags and ownership information, and publish it to the discovery platform.
- Tune and optimize search indexes - adjust analyzers, boost fields, and test queries - to ensure results match what users need.
- Build a semantic knowledge layer - chunking documents, generating vector embeddings, and enriching them with semantic knowledge metadata - to grow a data inventory that supports retrieval-augmented generation (RAG) and helps AI systems and large language models (LLMs) find and use the right context.
- Maintain integrations that sync ontology and taxonomy changes into the discovery platform, so classifications stay current.
- Investigate and resolve data pipeline issues across Databricks and AWS Glue, trace root causes through metadata enrichment flows, and add data quality checks to prevent recurrence.
- Build API endpoints and Model Context Protocol (MCP) servers that expose search and metadata capabilities to applications and AI agents.
- Design metadata pipelines that map cross-domain dataset relationships and add them to the cross-domain join catalog with confidence scores.
- Analyze search patterns, capture user feedback, and improve the discovery experience so the system learns and improves over time.
Qualifications & Experience:
Required
- Bachelor’s degree in computer science, Data Science, Information Science, Engineering, or a related field. Master's degree preferred.
- Demonstrated proficiency in data engineering, software engineering, or a related technical discipline, with a track record of delivering production data pipelines.
- Proficient Python skills - this is your primary language day-to-day.
- Proficiency in Structured Query Language (SQL).
- Experience with Databricks and AWS Glue for data pipelines and transformations.
- Solid data engineering fundamentals: extract-transform-load (ETL/ELT) patterns, data modeling, data quality, and pipeline orchestration.
- Familiarity with AWS cloud services (S3, Lambda, API Gateway, Glue).
- Experience with OpenSearch or Elasticsearch.
- Understanding of metadata management and data cataloging concepts.
- Effective problem-solving skills and willingness to learn.
- Good communication skills and ability to work collaboratively in a team.
Preferred Qualifications:
- Experience with semantic knowledge layers, RAG patterns, vector search technologies, and building AI-ready data inventories.
- Familiarity with semantic search, embeddings, chunking strategies, relevance tuning, and semantic knowledge metadata (entity relationships, taxonomies, context enrichment).
- Exposure to AI agent patterns, MCP, or large language model orchestration frameworks.
- Experience with ontology or taxonomy technologies (such as Turtle, Resource Description Framework, Web Ontology Language, or SPARQL query language) or management platforms.
- Familiarity with graph databases or knowledge graph technologies.
- Experience with metadata enrichment, data lineage, or data quality frameworks.
- Exposure to Azure OpenAI, Google Vertex AI, or Amazon Bedrock.
- Experience with Docker, Elastic Container Service (ECS), or CloudFormation.
- Prior exposure to pharma or life sciences.
If you come across a role that intrigues you but doesn’t perfectly line up with your resume, we encourage you to apply anyway. You could be one step away from work that will transform your life and career.
Compensation Overview:
Princeton - NJ - US: $87,810 - $106,399
The starting compensation range(s) for this role are listed above for a full-time employee (FTE) basis. Additional incentive cash and stock opportunities (based on eligibility) may be available. The starting pay rate takes into account characteristics of the job, such as required skills, where the job is performed, the employee’s work schedule, job-related knowledge, and experience. Final, individual compensation will be decided based on demonstrated experience.
Eligibility for specific benefits listed on our careers site may vary based on the job and location.
Benefit offerings are subject to the terms and conditions of the applicable plans in effect at the time and may require enrollment. Our benefits include:
- Health Coverage: Medical, pharmacy, dental, and vision care.
- Wellbeing Support: Programs such as BMS Well-Being Account, BMS Living Life Better, and Employee Assistance Programs (EAP).
- Financial Well-being and Protection: 401(k) plan, short- and long-term disability, life insurance, accident insurance, supplemental health insurance, business travel protection, personal liability protection, identity theft benefit, legal support, and survivor support.
Work-life benefits include:
Paid Time Off
- US Exempt Employees: flexible time off (unlimited, with manager approval, 11 paid national holidays (not applicable to employees in Phoenix, AZ, Puerto Rico or Rayzebio employees)
- Phoenix, AZ, Puerto Rico and Rayzebio Exempt, Non-Exempt, Hourly Employees: 160 hours annual paid vacation for new hires with manager approval, 11 national holidays, and 3 optional holidays
Based on eligibility*, additional time off for employees may include unlimited paid sick time, up to 2 paid volunteer days per year, summer hours flexibility, leaves of absence for medical, personal, parental, caregiver, bereavement, and military needs and an annual Global Shutdown between Christmas and New Years Day.
All global employees full and part-time who are actively employed at and paid directly by BMS at the end of the calendar year are eligible to take advantage of the Global Shutdown.
Eligibility Disclosure: The summer hours program is for United States (U.S.) office-based employees due to the unique nature of their work. Summer hours are generally not available for field sales and manufacturing operations and may also be limited for the capability centers. Employees in remote-by-design or lab-based roles may be eligible for summer hours, depending on the nature of their work, and should discuss eligibility with their manager. Employees covered under a collective bargaining agreement should consult that document to determine if they are eligible. Contractors, leased workers and other service providers are not eligible to participate in the program.
Uniquely Interesting Work, Life-changing Careers
With a single vision as inspiring as “Transforming patients’ lives through science™”, every BMS employee plays an integral role in work that goes far beyond ordinary. Each of us is empowered to apply our individual talents and unique perspectives in a supportive culture, promoting global participation in clinical trials, while our shared values of passion, innovation, urgency, accountability, inclusion and integrity bring out the highest potential of each of our colleagues.
On-site Protocol
BMS has an occupancy structure that determines where an employee is required to conduct their work. This structure includes site-essential, site-by-design, field-based and remote-by-design jobs. The occupancy type that you are assigned is determined by the nature and responsibilities of your role:
Site-essential roles require 100% of shifts onsite at your assigned facility. Site-by-design roles may be eligible for a hybrid work model with at least 50% onsite at your assigned facility. For these roles, onsite presence is considered an essential job function and is critical to collaboration, innovation, productivity, and a positive Company culture. For field-based and remote-by-design roles the ability to physically travel to visit customers, patients or business partners and to attend meetings on behalf of BMS as directed is an essential job function.
Supporting People with Disabilities
BMS is dedicated to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace accommodations/adjustments and ongoing support in their roles. Applicants can request a reasonable workplace accommodation/adjustment prior to accepting a job offer. If you require reasonable accommodations/adjustments in completing this application, or in any part of the recruitment process, direct your inquiries to adastaffingsupport@bms.com. Visit careers.bms.com/eeo-accessibility to access our complete Equal Employment Opportunity statement.
Candidate Rights
BMS will consider for employment qualified applicants with arrest and conviction records, pursuant to applicable laws in your area.
If you live in or expect to work from Los Angeles County if hired for this position, please visit this page for important additional information.
Data Protection
We will never request payments, financial information, or social security numbers during our application or recruitment process. Learn more about protecting yourself.
Any data processed in connection with role applications will be treated in accordance with applicable data privacy policies and regulations.
If you believe that the job posting is missing information required by local law or incorrect in any way, please contact BMS at TAEnablement@bms.com. Please provide the Job Title and Requisition number so we can review. Communications related to your application should not be sent to this email and you will not receive a response. Inquiries related to the status of your application should be directed to Chat with Ripley.
R1604590 : AI & Data Engineer, Data Discovery Services
See all 4,584+ AI Data Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI Data Engineer roles.
Get Access To All JobsTips for Finding Visa Sponsorship as an AI Data Engineer
Target companies with active LCA filings
Employers who have filed Labor Condition Applications for data engineering or machine learning roles in the past 12 months are already set up to sponsor. These companies have legal counsel, established workflows, and budgets allocated for visa costs.
Emphasize your ML pipeline and infrastructure work
USCIS approves AI Data Engineer petitions more cleanly when job duties are tied to a specific technical field. Highlight work on model training pipelines, feature stores, or distributed data systems, not general data tasks.
A computer science or data engineering degree strengthens your case
H-1B specialty occupation requires a degree in a directly related field. CS, software engineering, statistics, and applied mathematics are strong fits. A general business or unrelated degree may require additional documentation or a credentials evaluation.
Cap-exempt employers offer a faster path in
Universities, nonprofit research institutions, and government-affiliated organizations are exempt from the H-1B lottery. AI and data roles at these employers can be filed any time of year, with USCIS adjudicating without a cap slot.
O-1A is a realistic alternative if your profile is strong
AI Data Engineers with published research, open-source contributions with wide adoption, or recognition from the field may qualify for the O-1A extraordinary ability visa. It has no lottery and no annual cap, making it faster to obtain.
Use Migrate Mate to find roles already set up to sponsor
Not every job posting discloses visa sponsorship upfront. Migrate Mate filters for employers actively sponsoring AI and data engineering roles, so you apply to companies already prepared to file, not ones figuring it out for the first time.
Frequently Asked Questions
Does the AI Data Engineer role qualify for H-1B sponsorship?
Yes. AI Data Engineer is a specialty occupation under USCIS guidelines because it requires a bachelor's degree or higher in a specific technical field such as computer science, data engineering, or statistics. Employers regularly file H-1B visa petitions for this title, and USCIS approves them at high rates when the job duties and degree field align clearly.
What degree do I need for an employer to sponsor my H-1B as an AI Data Engineer?
A bachelor's degree in computer science, data science, statistics, applied mathematics, or a closely related field is the standard. A general business or humanities degree typically won't support the petition without supplemental evidence. If your degree is in a tangentially related field, employers may need to file additional documentation demonstrating the connection between your coursework and the role.
Can I get sponsored as an AI Data Engineer if I didn't win the H-1B lottery?
There are a few paths. Cap-exempt employers, including universities and qualifying nonprofits, can file H-1B petitions year-round without lottery exposure. Alternatively, the O-1A visa has no cap and no lottery, and is achievable for AI Data Engineers with strong publication records, recognized open-source projects, or other evidence of extraordinary ability in the field.
How common is visa sponsorship for AI Data Engineer roles specifically?
AI and machine learning data roles are among the most actively sponsored positions in the U.S. tech sector. DOL LCA disclosure data consistently shows high filing volumes for data engineering and ML infrastructure titles at large technology companies and well-funded startups. Browse Migrate Mate to see which employers are currently hiring AI Data Engineers with sponsorship.
Does hands-on AI experience matter more than a formal degree for sponsorship purposes?
For H-1B purposes, the formal degree requirement is a legal threshold, not just a preference. However, USCIS also allows three years of specialized experience to substitute for one year of a four-year degree, so candidates with significant hands-on AI pipeline work and some formal education can still qualify. Document your experience clearly in any petition supporting the specialty occupation argument.
What is the prevailing wage requirement for sponsored AI Data Engineer jobs?
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.