Media Executive Jobs in USA with Visa Sponsorship
Media Executive roles in the U.S. qualify as specialty occupations under the H-1B visa, making them viable for employer-sponsored visas. Broadcasters, digital publishers, and streaming platforms are active sponsors. Your portfolio, production credits, and degree in communications or a related field are your strongest assets in the sponsorship process.
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Get Access To All JobsAt Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.
As a Staff Forward Deployed Engineer, Applied AI on our Cortex AI team, you will be a hands-on technical leader and trusted partner to our most strategic customers. You will own the end-to-end delivery of enterprise AI programs, leading a team of 2–4 engineers while staying deeply technical yourself. You will set the technical direction for your customer engagements, mentor your team, and serve as the senior technical voice at the intersection of product, engineering, and customer success.
Note: This is a customer facing role & require frequent travelling within USA mostly
IN THIS ROLE AT SNOWFLAKE, YOU WILL:
Lead Customer Programs: Own the full lifecycle of complex, multi-engineer AI engagements – from scoping and architecture through deployment, monitoring, and handoff. Be accountable for delivery quality and customer outcomes for the projects you lead.
Own AI Quality: Define what "good" means for each engagement. Translate ambiguous customer goals into measurable quality metrics, evaluation frameworks, and golden datasets – then run systematic eval loops to hill-climb on agent quality, catch regressions before customers do, and continuously raise the bar on accuracy, faithfulness, and safety. Set the standard for how the team measures and improves AI systems in production.
Grow and Mentor Engineers: Provide day-to-day technical leadership and mentorship to a team of 2–6 Applied AI Engineers. Review designs and code, unblock teammates, and actively develop their skills and careers.
Deliver with Velocity: Remain a hands-on contributor – designing, iterating, and shipping high-quality ML pipelines and agentic AI solutions alongside your team. Translate ambiguous business objectives into robust, scalable, and performant solutions.
Productionize AI at Scale: Own the full implementation lifecycle for AI solutions, from prototype through deployment, monitoring, and optimization in secure, large-scale production environments. Build the safety guardrails, observability, and human-review workflows that keep AI applications reliable and trustworthy – and close the loop from production traces and user feedback back into your evals so quality compounds over time.
Be a Strategic Technical Advisor: Serve as a senior technical advisor to customer data science and engineering leadership. Set the standard for how Snowflake AI is deployed and articulate complex technical concepts to both technical and executive stakeholders.
Collaborate to Innovate: Work cross-functionally with Snowflake's Product and Engineering teams, bringing real-world patterns and feedback from the field to directly shape the future of Snowflake's AI platform.
Drive Compounding Outcomes: Identify recurring deployment patterns and turn them into reusable assets – reference architectures, evaluation harnesses, and product feedback that scale Snowflake's impact across customers.
Have the opportunity to travel: Spend at least 25% of your time onsite, working closely with Snowflake's most strategic customers.
WE'RE LOOKING FOR CANDIDATES WHO HAVE:
- Demonstrated experience leading technical projects or teams, including setting technical direction, reviewing others' work, and driving delivery to completion.
- Proven experience building and productionizing applications using LLMs, especially with technologies like RAG and agentic workflows.
- Hands-on experience defining quality metrics and evaluation frameworks for LLM or agent systems, and using evals to systematically improve quality over time.
- Excellent problem-solving and communication skills, with an ability to articulate complex technical concepts to both technical and executive stakeholders.
- Comfort with ambiguity and the ability to independently structure and execute on complex, open-ended problems.
- 7+ years of professional software engineering experience.
- Experience in a customer-facing technical role.
- Willingness to travel.
Preferred Qualifications
- Experience building eval sets from production traces and synthetic data, and running structured experimentation (A/B tests, ablations, offline evals) to compare prompts, models, or agent architectures.
- Familiarity with eval and observability tooling (e.g., Braintrust, LangSmith, Arize, Weave, Promptfoo) or experience building custom eval harnesses.
- Experience with failure-mode analysis on agent or RAG systems – categorizing errors (hallucination, retrieval miss, planning failure, tool misuse) and driving each down with targeted evals.
- Hands-on experience with the MLOps lifecycle, including model deployment, monitoring, and evaluation in a cloud environment (AWS, Azure, or GCP).
- Familiarity with core data science libraries and tools (e.g., pandas, numpy, Snowpark).
- Startup experience or experience in a high-growth, fast-paced environment.
Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee’s duty to keep customer information secure and confidential.
Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
How do you want to make your impact?
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com
The following represents the expected range of compensation for this role:
- The estimated base salary range for this role is $200,000 - $287,500.
- Additionally, this role is eligible to participate in Snowflake’s bonus and equity plan.
The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. This role is also eligible for a competitive benefits package that includes: medical, dental, vision, life, and disability insurance; 401(k) retirement plan; flexible spending & health savings account; at least 12 paid holidays; paid time off; parental leave; employee assistance program; and other company benefits.
To comply with pay transparency requirements and other statutes, you can notify us if you believe that a job posting is not compliant by completing this form.
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.
As a Staff Forward Deployed Engineer, Applied AI on our Cortex AI team, you will be a hands-on technical leader and trusted partner to our most strategic customers. You will own the end-to-end delivery of enterprise AI programs, leading a team of 2–4 engineers while staying deeply technical yourself. You will set the technical direction for your customer engagements, mentor your team, and serve as the senior technical voice at the intersection of product, engineering, and customer success.
Note: This is a customer facing role & require frequent travelling within USA mostly
IN THIS ROLE AT SNOWFLAKE, YOU WILL:
Lead Customer Programs: Own the full lifecycle of complex, multi-engineer AI engagements – from scoping and architecture through deployment, monitoring, and handoff. Be accountable for delivery quality and customer outcomes for the projects you lead.
Own AI Quality: Define what "good" means for each engagement. Translate ambiguous customer goals into measurable quality metrics, evaluation frameworks, and golden datasets – then run systematic eval loops to hill-climb on agent quality, catch regressions before customers do, and continuously raise the bar on accuracy, faithfulness, and safety. Set the standard for how the team measures and improves AI systems in production.
Grow and Mentor Engineers: Provide day-to-day technical leadership and mentorship to a team of 2–6 Applied AI Engineers. Review designs and code, unblock teammates, and actively develop their skills and careers.
Deliver with Velocity: Remain a hands-on contributor – designing, iterating, and shipping high-quality ML pipelines and agentic AI solutions alongside your team. Translate ambiguous business objectives into robust, scalable, and performant solutions.
Productionize AI at Scale: Own the full implementation lifecycle for AI solutions, from prototype through deployment, monitoring, and optimization in secure, large-scale production environments. Build the safety guardrails, observability, and human-review workflows that keep AI applications reliable and trustworthy – and close the loop from production traces and user feedback back into your evals so quality compounds over time.
Be a Strategic Technical Advisor: Serve as a senior technical advisor to customer data science and engineering leadership. Set the standard for how Snowflake AI is deployed and articulate complex technical concepts to both technical and executive stakeholders.
Collaborate to Innovate: Work cross-functionally with Snowflake's Product and Engineering teams, bringing real-world patterns and feedback from the field to directly shape the future of Snowflake's AI platform.
Drive Compounding Outcomes: Identify recurring deployment patterns and turn them into reusable assets – reference architectures, evaluation harnesses, and product feedback that scale Snowflake's impact across customers.
Have the opportunity to travel: Spend at least 25% of your time onsite, working closely with Snowflake's most strategic customers.
WE'RE LOOKING FOR CANDIDATES WHO HAVE:
- Demonstrated experience leading technical projects or teams, including setting technical direction, reviewing others' work, and driving delivery to completion.
- Proven experience building and productionizing applications using LLMs, especially with technologies like RAG and agentic workflows.
- Hands-on experience defining quality metrics and evaluation frameworks for LLM or agent systems, and using evals to systematically improve quality over time.
- Excellent problem-solving and communication skills, with an ability to articulate complex technical concepts to both technical and executive stakeholders.
- Comfort with ambiguity and the ability to independently structure and execute on complex, open-ended problems.
- 7+ years of professional software engineering experience.
- Experience in a customer-facing technical role.
- Willingness to travel.
Preferred Qualifications
- Experience building eval sets from production traces and synthetic data, and running structured experimentation (A/B tests, ablations, offline evals) to compare prompts, models, or agent architectures.
- Familiarity with eval and observability tooling (e.g., Braintrust, LangSmith, Arize, Weave, Promptfoo) or experience building custom eval harnesses.
- Experience with failure-mode analysis on agent or RAG systems – categorizing errors (hallucination, retrieval miss, planning failure, tool misuse) and driving each down with targeted evals.
- Hands-on experience with the MLOps lifecycle, including model deployment, monitoring, and evaluation in a cloud environment (AWS, Azure, or GCP).
- Familiarity with core data science libraries and tools (e.g., pandas, numpy, Snowpark).
- Startup experience or experience in a high-growth, fast-paced environment.
Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee’s duty to keep customer information secure and confidential.
Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
How do you want to make your impact?
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com
The following represents the expected range of compensation for this role:
- The estimated base salary range for this role is $200,000 - $287,500.
- Additionally, this role is eligible to participate in Snowflake’s bonus and equity plan.
The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. This role is also eligible for a competitive benefits package that includes: medical, dental, vision, life, and disability insurance; 401(k) retirement plan; flexible spending & health savings account; at least 12 paid holidays; paid time off; parental leave; employee assistance program; and other company benefits.
To comply with pay transparency requirements and other statutes, you can notify us if you believe that a job posting is not compliant by completing this form.
See all 101+ Media Executive Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Media Executive roles.
Get Access To All JobsTips for Finding Media Executive Jobs
Frame your credits as specialty work
Compile a portfolio that ties each production credit or editorial role to a specific degree requirement. USCIS assesses specialty occupation by whether the role normally requires a bachelor's in a directly related field, so your documentation needs to reflect that connection clearly.
Target employers with active LCA history
Use Migrate Mate to find media companies with verified LCA filing history for executive-level roles. Broadcasters and streaming platforms that have sponsored before are far more likely to repeat the process than employers new to it.
Check prevailing wage tiers before negotiating
Run your target title and location through the OFLC Wage Search before salary talks begin. Media Executive roles span Level I through Level IV wages depending on supervisory scope, and your offer must meet or exceed the certified wage tier your LCA specifies.
Distinguish editorial from management duties
Job descriptions for Media Executive roles often blend creative and managerial tasks. Clarify with your prospective employer whether the LCA will be filed under a media or communications specialty occupation code, since USCIS scrutinizes hybrid roles more closely than single-discipline positions.
Get your degree equivalency documented early
If your media degree is from a non-U.S. institution or is a three-year program, obtain a credential evaluation before your employer files. USCIS accepts foreign degrees but requires a formal equivalency assessment from a recognized evaluator, and delays here can push back your LCA certification.
Align your start date with LCA certification timing
DOL certifies LCAs within seven working days under normal conditions, but your employer can't file the I-129 petition with USCIS until certification is complete. Build that window into your offer timeline so your start date doesn't precede your authorized work status.
Frequently Asked Questions
Does a Media Executive role qualify as a specialty occupation for the H-1B?
Yes, provided the employer can demonstrate the position normally requires at least a bachelor's degree in a directly related field such as communications, journalism, media studies, or broadcasting. Roles with significant editorial, strategic, or production oversight typically satisfy this standard. USCIS evaluates the job duties rather than the title, so the offer letter and supporting documentation need to establish that degree-level expertise is genuinely required.
Which visa types are most common for sponsored Media Executive positions?
H-1B is the most widely used path for Media Executive roles at U.S. employers. Australian nationals can apply for the E-3 visa, which has no lottery and a separate annual cap. Canadian and Mexican nationals may qualify under TN visa if the role maps to a recognized USMCA profession. For senior roles with an international assignment component, L-1 visa is sometimes used by multinational media companies transferring executives between offices.
How do I find media companies that actively sponsor visas for executive roles?
Migrate Mate lists employers with verified sponsorship history for media and communications positions, so you can focus your applications on companies that have already committed to the LCA and I-129 process. This saves significant time compared to approaching employers who may be unfamiliar with sponsorship requirements for executive-level hires.
Will my non-U.S. media experience count toward the specialty occupation requirement?
Foreign work experience counts, but USCIS looks at whether the experience aligns with the degree requirement for the specific role. If you don't hold a directly related degree, three years of qualifying professional experience can substitute for one year of education under the specialty occupation framework. A detailed experience letter from each prior employer, outlining duties and your level of responsibility, is essential documentation for this argument.
What happens to my H-1B status if my media employer is acquired or restructures?
If your employer is acquired and you continue in a substantially similar role under a successor entity that assumes the LCA obligations, your existing H-1B may remain valid without a new filing. However, if the job duties, location, or wage level change materially, your employer must file an amended petition with USCIS before those changes take effect. Confirm with your employer whether an amendment is required before any organizational change is finalized.
What is the prevailing wage requirement for sponsored Media Executive 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.