Customer Success Engineering Jobs in USA with Visa Sponsorship
Customer Success Engineering roles sit at the intersection of technical expertise and client relationships, making them strong candidates for H-1B visa and E-3 visa sponsorship. Most employers require a bachelor's degree in computer science, engineering, or a related field, and the specialty occupation standard is well-established for this title. For detailed occupation requirements, see the O*NET profile.
See All Customer Success Engineering JobsOverview
Showing 5 of 1,047+ Customer Success Engineering jobs
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
See all 1,047+ Customer Success Engineering Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Customer Success Engineering roles.
Get Access To All JobsINTRODUCTION
DataRobot delivers AI that maximizes impact and minimizes business risk. Our platform and applications integrate into core business processes so teams can develop, deliver, and govern AI at scale. DataRobot empowers practitioners to deliver predictive and generative AI, and enables leaders to secure their AI assets. Organizations worldwide rely on DataRobot for AI that makes sense for their business — today and in the future.
As the Director of Customer Success Engineering, you will be a pivotal leadership figure reporting directly to the VP of Customer Success Engineering. You will operationalize the global customer success engineering strategy by leading a regional or segmented team of highly skilled Customer Success Engineers (CSEs).
Your team is responsible for working hand-in-hand with customer AI Engineers and developers to maximize the value of DataRobot’s Agentic platform. You will ensure your CSEs are delivering measurable business outcomes, driving high application consumption, and securing long-term customer retention. This is a highly collaborative role requiring deep technical acumen in Generative/Predictive AI, proven people leadership, and a customer-obsessed mindset. You will partner cross-functionally with Account Management, Professional Services, Product, and Engineering to ensure a seamless customer experience that drives retention and growth.
ROLE AND RESPONSIBILITIES
What You Will Achieve (30-60-90 Days)
- Day 30: Understand the DataRobot platform, shadow ongoing CSE customer engagements, learn our internal processes, and build relationships with your direct reports and cross-functional peers (Engineering, Product, Account Management).
- Day 60: Take full operational ownership of your team's book of business. Begin identifying opportunities to optimize CSE capacity, improve Time-to-Value (TTV) for new deployments, and standardize success planning.
- Day 90: Co-develop and execute strategic adoption plans for top-tier enterprise accounts. Establish a clear feedback loop with Product/Engineering to champion customer needs, and begin driving measurable improvements in team KPIs (health scores, platform consumption).
Key Responsibilities
Team Leadership & Development
- Manage, mentor, and scale a high-performing team of Customer Success Engineers (CSEs).
- Translate the overarching technical success strategy set by the VP of Customer Success Engineering into actionable team-level objectives.
- Build a culture of accountability, continuous learning, and innovation.
- Develop career progression pathways, conduct performance reviews, and recruit top-tier technical talent to keep pace with company growth.
Customer Outcomes & Value Realization
- Serve as the senior technical sponsor and executive escalation point for strategic enterprise accounts.
- Ensure the successful execution of adoption plans, empowering customers to leverage DataRobot’s GenAI and predictive capabilities fully.
- Own regional/segment performance metrics, specifically customer health scores, and platform consumption rates.
- Proactively identify account risks and commercial expansion opportunities (upsell/cross-sell), guiding your CSEs to intervene and drive value realization alongside Account Management.
Operational Excellence & Tooling
- Drive day-to-day operational rigor across the team, ensuring adherence to success planning standards, CRM hygiene, and engagement methodologies.
- Leverage CS platforms and CRM tools (e.g., Salesforce) to optimize team utilization, capacity planning, and productivity metrics.
- Partner with the VP of Customer Success Engineering to evaluate telemetry data and analytics, continuously improving the customer journey.
Cross-Functional Collaboration
- Work closely with Account Management and Sales leadership to seamlessly align pre-sales expectations with post-sales technical delivery.
- Act as a vital conduit between the field and the Product/Engineering teams, utilizing tools like Jira or Productboard to aggregate and translate customer feedback into roadmap influence.
- Collaborate with Enablement teams to ensure your technical staff is thoroughly trained on the latest DataRobot features, AI agents, and market trends.
KNOWLEDGE, SKILLS, AND ABILITIES
- Strong foundational knowledge of artificial intelligence, including predictive AI, Generative AI, LLMs, AI Agents, and modern SaaS delivery architectures (AWS, GCP, Azure).
- Familiarity with data science concepts, programming languages (Python, R), and enterprise AI integration patterns.
- Demonstrated ability to coach highly technical individual contributors (data scientists, CSEs, ML engineers) into trusted strategic business advisors.
- Ability to translate highly complex technical concepts into ROI-driven business narratives for C-suite stakeholders.
- Data-driven decision-maker with a strong grasp of customer success operations and financial KPIs.
MINIMUM QUALIFICATIONS
- 10+ years of experience in post-sales technical, solution engineering, or professional services roles within the B2B enterprise SaaS, Cloud, or AI/Data space.
- 3–5+ years of direct people management experience, successfully leading technical customer-facing teams.
- Proven track record of owning and achieving product adoption, retention, and commercial expansion targets.
- Bachelor’s degree in a technical, business, or related field (Master’s degree or equivalent experience preferred).
The talent and dedication of our employees are at the core of DataRobot’s journey to be an iconic company. We strive to attract and retain the best talent by providing competitive pay and benefits with our employees’ well-being at the core. Here’s what your benefits package may include depending on your location and local legal requirements: Medical, Dental & Vision Insurance, Flexible Time Off Program, Paid Holidays, Paid Parental Leave, Global Employee Assistance Program (EAP) and more!
DataRobot Operating Principles:
- Wow Our Customers
- Set High Standards
- Be Better Than Yesterday
- Be Rigorous
- Assume Positive Intent
- Have the Tough Conversations
- Be Better Together
- Debate, Decide, Commit
- Deliver Results
- Overcommunicate
Research shows that many women only apply to jobs when they meet 100% of the qualifications while many men apply to jobs when they meet 60%. At DataRobot we encourage ALL candidates, especially women, people of color, LGBTQ+ identifying people, differently abled, and other people from marginalized groups to apply to our jobs, even if you do not check every box. We’d love to have a conversation with you and see if you might be a great fit.
DataRobot is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. DataRobot is committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. Please see the United States Department of Labor’s EEO poster and EEO poster supplement for additional information.
All applicant data submitted is handled in accordance with our Applicant Privacy Policy.
INTRODUCTION
DataRobot delivers AI that maximizes impact and minimizes business risk. Our platform and applications integrate into core business processes so teams can develop, deliver, and govern AI at scale. DataRobot empowers practitioners to deliver predictive and generative AI, and enables leaders to secure their AI assets. Organizations worldwide rely on DataRobot for AI that makes sense for their business — today and in the future.
As the Director of Customer Success Engineering, you will be a pivotal leadership figure reporting directly to the VP of Customer Success Engineering. You will operationalize the global customer success engineering strategy by leading a regional or segmented team of highly skilled Customer Success Engineers (CSEs).
Your team is responsible for working hand-in-hand with customer AI Engineers and developers to maximize the value of DataRobot’s Agentic platform. You will ensure your CSEs are delivering measurable business outcomes, driving high application consumption, and securing long-term customer retention. This is a highly collaborative role requiring deep technical acumen in Generative/Predictive AI, proven people leadership, and a customer-obsessed mindset. You will partner cross-functionally with Account Management, Professional Services, Product, and Engineering to ensure a seamless customer experience that drives retention and growth.
ROLE AND RESPONSIBILITIES
What You Will Achieve (30-60-90 Days)
- Day 30: Understand the DataRobot platform, shadow ongoing CSE customer engagements, learn our internal processes, and build relationships with your direct reports and cross-functional peers (Engineering, Product, Account Management).
- Day 60: Take full operational ownership of your team's book of business. Begin identifying opportunities to optimize CSE capacity, improve Time-to-Value (TTV) for new deployments, and standardize success planning.
- Day 90: Co-develop and execute strategic adoption plans for top-tier enterprise accounts. Establish a clear feedback loop with Product/Engineering to champion customer needs, and begin driving measurable improvements in team KPIs (health scores, platform consumption).
Key Responsibilities
Team Leadership & Development
- Manage, mentor, and scale a high-performing team of Customer Success Engineers (CSEs).
- Translate the overarching technical success strategy set by the VP of Customer Success Engineering into actionable team-level objectives.
- Build a culture of accountability, continuous learning, and innovation.
- Develop career progression pathways, conduct performance reviews, and recruit top-tier technical talent to keep pace with company growth.
Customer Outcomes & Value Realization
- Serve as the senior technical sponsor and executive escalation point for strategic enterprise accounts.
- Ensure the successful execution of adoption plans, empowering customers to leverage DataRobot’s GenAI and predictive capabilities fully.
- Own regional/segment performance metrics, specifically customer health scores, and platform consumption rates.
- Proactively identify account risks and commercial expansion opportunities (upsell/cross-sell), guiding your CSEs to intervene and drive value realization alongside Account Management.
Operational Excellence & Tooling
- Drive day-to-day operational rigor across the team, ensuring adherence to success planning standards, CRM hygiene, and engagement methodologies.
- Leverage CS platforms and CRM tools (e.g., Salesforce) to optimize team utilization, capacity planning, and productivity metrics.
- Partner with the VP of Customer Success Engineering to evaluate telemetry data and analytics, continuously improving the customer journey.
Cross-Functional Collaboration
- Work closely with Account Management and Sales leadership to seamlessly align pre-sales expectations with post-sales technical delivery.
- Act as a vital conduit between the field and the Product/Engineering teams, utilizing tools like Jira or Productboard to aggregate and translate customer feedback into roadmap influence.
- Collaborate with Enablement teams to ensure your technical staff is thoroughly trained on the latest DataRobot features, AI agents, and market trends.
KNOWLEDGE, SKILLS, AND ABILITIES
- Strong foundational knowledge of artificial intelligence, including predictive AI, Generative AI, LLMs, AI Agents, and modern SaaS delivery architectures (AWS, GCP, Azure).
- Familiarity with data science concepts, programming languages (Python, R), and enterprise AI integration patterns.
- Demonstrated ability to coach highly technical individual contributors (data scientists, CSEs, ML engineers) into trusted strategic business advisors.
- Ability to translate highly complex technical concepts into ROI-driven business narratives for C-suite stakeholders.
- Data-driven decision-maker with a strong grasp of customer success operations and financial KPIs.
MINIMUM QUALIFICATIONS
- 10+ years of experience in post-sales technical, solution engineering, or professional services roles within the B2B enterprise SaaS, Cloud, or AI/Data space.
- 3–5+ years of direct people management experience, successfully leading technical customer-facing teams.
- Proven track record of owning and achieving product adoption, retention, and commercial expansion targets.
- Bachelor’s degree in a technical, business, or related field (Master’s degree or equivalent experience preferred).
The talent and dedication of our employees are at the core of DataRobot’s journey to be an iconic company. We strive to attract and retain the best talent by providing competitive pay and benefits with our employees’ well-being at the core. Here’s what your benefits package may include depending on your location and local legal requirements: Medical, Dental & Vision Insurance, Flexible Time Off Program, Paid Holidays, Paid Parental Leave, Global Employee Assistance Program (EAP) and more!
DataRobot Operating Principles:
- Wow Our Customers
- Set High Standards
- Be Better Than Yesterday
- Be Rigorous
- Assume Positive Intent
- Have the Tough Conversations
- Be Better Together
- Debate, Decide, Commit
- Deliver Results
- Overcommunicate
Research shows that many women only apply to jobs when they meet 100% of the qualifications while many men apply to jobs when they meet 60%. At DataRobot we encourage ALL candidates, especially women, people of color, LGBTQ+ identifying people, differently abled, and other people from marginalized groups to apply to our jobs, even if you do not check every box. We’d love to have a conversation with you and see if you might be a great fit.
DataRobot is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. DataRobot is committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. Please see the United States Department of Labor’s EEO poster and EEO poster supplement for additional information.
All applicant data submitted is handled in accordance with our Applicant Privacy Policy.
See all 1,047+ Customer Success Engineering Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Customer Success Engineering roles.
Get Access To All JobsTips for Finding Customer Success Engineering Jobs
Lead with your technical depth
Customer Success Engineers who can demonstrate hands-on product expertise, API knowledge, or integration experience are far easier for employers to sponsor. Highlight specific technical skills in your resume before listing relationship management responsibilities.
Target companies with established sponsorship history
SaaS and enterprise software companies sponsor Customer Success Engineers regularly. Look for employers with dedicated immigration counsel, existing H-1B LCA filings, and international offices, as these signal a mature, repeatable sponsorship process rather than a one-off decision.
Clarify the technical scope of the role early
Specialty occupation approval depends on the role requiring a specific bachelor's degree. In interviews, emphasize technical duties such as solution architecture, API troubleshooting, or platform configuration rather than account management to strengthen the visa petition's foundation.
Align your degree field to the job description
USCIS scrutinizes Customer Success Engineering petitions when degree fields seem loosely connected. A degree in computer science, information systems, or engineering aligns cleanly. If your field is adjacent, gather documentation showing how your coursework directly supports the technical duties.
Understand the LCA prevailing wage tier
Your employer files a Labor Condition Application before your visa petition. The certified wage on the LCA must meet the prevailing wage for the role and location. Roles classified at Level I or II can attract additional USCIS scrutiny, so senior-level framing helps.
Use Migrate Mate to filter for sponsors
Not every Customer Success Engineering posting comes with sponsorship. Migrate Mate surfaces roles where employers have confirmed willingness to sponsor, saving you the time of applying to positions that will screen out visa candidates before the first interview.
Frequently Asked Questions
Does Customer Success Engineering qualify as a specialty occupation for H-1B sponsorship?
Generally yes, but the petition needs to clearly establish that the role requires a specific bachelor's degree rather than any degree. Customer Success Engineers whose day-to-day work involves technical implementation, API integration, or complex product troubleshooting tend to have stronger petitions than those whose duties lean toward account management or relationship coordination.
What degree do I need to get sponsored for a Customer Success Engineering role?
Most employers and USCIS adjudicators expect a bachelor's degree in computer science, software engineering, information systems, or a closely related technical field. Degrees in business or communications can create complications unless the job description is explicitly technical. If your degree is from outside the U.S., a credential evaluation confirming U.S. equivalency strengthens the petition significantly.
Are Customer Success Engineering roles harder to get sponsored for than pure software engineering roles?
Yes, somewhat. Pure software engineering roles have a long history of H-1B visa approvals and established adjudication precedent. Customer Success Engineering sits closer to a boundary between technical and client-facing work, which means adjudicators look more closely at job duties. The more the role description emphasizes architecture, integrations, and technical problem-solving, the cleaner the approval path.
How do I find Customer Success Engineering jobs that offer visa sponsorship?
Most general job searches don't filter by sponsorship willingness, which means you'll spend significant time applying to roles that screen out visa candidates. Migrate Mate is built specifically for this, surfacing Customer Success Engineering positions where employers have confirmed they'll sponsor. Filtering by sponsorship upfront avoids wasted applications and gets you to real opportunities faster.
Can I transfer my H-1B to a new Customer Success Engineering role if I change employers?
Yes. H-1B portability allows you to start working for a new employer as soon as they file a transfer petition, without waiting for approval, provided you've been in valid H-1B status for at least 180 days. The new employer still needs to file their own I-129 and LCA, and the role must independently qualify as a specialty occupation under the same technical criteria.
What is the prevailing wage requirement for sponsored Customer Success Engineering 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.