Salary for Executive-level / Director Solutions Engineer in United States during 2024

Salary details

The average executive-level / director Solutions Engineer salary lies between USD 190,000 and USD 297,000 in the United States. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.

Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Nov. 10, 2024

Top 20 Job Tags for Executive-level / Director Solutions Engineer roles

The three most common job tag items assiciated with executive-level / director Solutions Engineer job listings are Engineering, Python and Machine Learning. Below you find a list of the 20 most occuring job tags in 2024 and the number of open jobs that where associated with them during that period:

Engineering | 5 jobs Python | 4 jobs Machine Learning | 4 jobs AWS | 4 jobs Architecture | 3 jobs Agile | 3 jobs Pipelines | 3 jobs Databricks | 3 jobs Computer Science | 3 jobs Data governance | 3 jobs Data Warehousing | 2 jobs ETL | 2 jobs Big Data | 2 jobs Spark | 2 jobs Redshift | 2 jobs Research | 2 jobs Distributed Systems | 2 jobs Business Intelligence | 2 jobs Azure | 2 jobs Feature engineering | 2 jobs

Top 20 Job Perks/Benefits for Executive-level / Director Solutions Engineer roles

The three most common job benefits and perks assiciated with executive-level / director Solutions Engineer job listings are Career development, Health care and Startup environment. Below you find a list of the 20 most occuring job perks or benefits in 2024 and the number of open jobs that where offering them during that period:

Career development | 5 jobs Health care | 4 jobs Startup environment | 3 jobs Competitive pay | 3 jobs Equity / stock options | 2 jobs Salary bonus | 2 jobs 401(k) matching | 1 jobs Parental leave | 1 jobs Wellness | 1 jobs Gear | 1 jobs Transparency | 1 jobs Team events | 1 jobs Relocation support | 1 jobs Medical leave | 1 jobs Insurance | 1 jobs Unlimited paid time off | 1 jobs

Salary Composition

In the United States, the salary composition for an Executive-level or Director Solutions Engineer in AI/ML/Data Science typically includes a mix of base salary, bonuses, and additional remuneration such as stock options or equity. The base salary often constitutes the largest portion, ranging from 60% to 80% of the total compensation package. Bonuses, which can be performance-based or tied to company-wide goals, usually account for 10% to 20%. Additional remuneration, such as stock options, equity, or other benefits, can make up the remaining 10% to 20%. The exact composition can vary significantly depending on the region, industry, and company size. For instance, tech companies in Silicon Valley might offer more in stock options, while companies in other regions might focus more on cash bonuses.

Increasing Salary

To increase your salary further from this position, consider the following strategies:

• Expand Your Skill Set: Continuously update your technical and managerial skills. Specializing in emerging technologies or methodologies can make you more valuable.
• Seek Leadership Roles: Aim for roles with greater responsibility, such as VP of Engineering or Chief Technology Officer, which typically offer higher compensation.
• Network Strategically: Build a strong professional network to learn about new opportunities and gain insights into industry trends.
• Negotiate Effectively: When offered a new position or during performance reviews, negotiate for higher pay, better bonuses, or more equity.
• Pursue Further Education: An advanced degree or executive education can sometimes justify a higher salary.

Educational Requirements

Most Executive-level or Director Solutions Engineer positions require at least a bachelor's degree in a relevant field such as Computer Science, Data Science, Engineering, or Mathematics. However, a master's degree or even a Ph.D. is often preferred, especially in larger companies or more competitive industries. An MBA can also be beneficial, particularly for roles that require significant business acumen and leadership skills.

Helpful Certifications

While not always mandatory, certain certifications can enhance your qualifications and demonstrate your expertise. Some valuable certifications include:

• Certified Data Scientist (CDS)
• AWS Certified Machine Learning – Specialty
• Google Professional Machine Learning Engineer
• Microsoft Certified: Azure AI Engineer Associate
• Certified Analytics Professional (CAP)

These certifications can help validate your skills and knowledge in specific areas of AI/ML and data science.

Required Experience

Typically, this role requires extensive experience, often 10+ years, in relevant fields such as software engineering, data science, or machine learning. Experience in leadership or managerial roles is crucial, as the position involves overseeing teams and projects. A proven track record of successful project delivery and strategic decision-making is also important.

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