Salary for Senior-level / Expert Solutions Architect in United States during 2024

Salary details

The average senior-level / expert Solutions Architect salary lies between USD 140,000 and USD 247,300 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: Dec. 22, 2024

Top 20 Job Tags for Senior-level / Expert Solutions Architect roles

The three most common job tag items assiciated with senior-level / expert Solutions Architect job listings are Engineering, Architecture and Python. 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 | 553 jobs Architecture | 535 jobs Python | 512 jobs Machine Learning | 422 jobs Computer Science | 374 jobs AWS | 358 jobs Azure | 268 jobs Spark | 259 jobs GCP | 253 jobs Security | 234 jobs Java | 229 jobs Databricks | 227 jobs Generative AI | 212 jobs Big Data | 211 jobs Research | 197 jobs Excel | 190 jobs Scala | 180 jobs SQL | 179 jobs Consulting | 178 jobs MLFlow | 177 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Solutions Architect roles

The three most common job benefits and perks assiciated with senior-level / expert Solutions Architect job listings are Career development, Equity / stock options and Health care. 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 | 550 jobs Equity / stock options | 261 jobs Health care | 250 jobs Flex hours | 179 jobs Flex vacation | 159 jobs Salary bonus | 159 jobs Competitive pay | 143 jobs Insurance | 131 jobs Parental leave | 128 jobs Medical leave | 127 jobs Team events | 126 jobs Wellness | 111 jobs Startup environment | 109 jobs Conferences | 93 jobs 401(k) matching | 57 jobs Fitness / gym | 49 jobs Transparency | 41 jobs Home office stipend | 19 jobs Fertility benefits | 19 jobs Unlimited paid time off | 11 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Solutions Architect in AI/ML/Data Science typically includes a combination of base salary, bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the largest portion, ranging from 70% to 85% of the total compensation package. Bonuses, which can be performance-based or tied to company success, usually account for 10% to 20%. Additional remuneration, such as stock options, equity, or profit-sharing, can make up the remaining 5% to 10%. The exact composition can vary significantly depending on the region, industry, and company size. For instance, tech hubs like Silicon Valley or New York may offer higher base salaries and more substantial equity packages, while smaller companies might offer more competitive bonuses to attract top talent.

Next Steps for Salary Increase

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

• Specialization: Develop expertise in a niche area within AI/ML, such as natural language processing, computer vision, or reinforcement learning, which can make you more valuable.
• Leadership Roles: Transition into leadership roles such as Chief AI Officer or Head of Data Science, where strategic decision-making and team management are key responsibilities.
• Consulting: Offer your expertise as a consultant, which can command higher hourly rates and provide opportunities for additional income streams.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML, and consider pursuing advanced certifications or degrees.
• Networking: Build a strong professional network to learn about high-paying opportunities and negotiate better compensation packages.

Educational Requirements

Most Senior-level or Expert Solutions Architect positions in AI/ML/Data Science require at least a bachelor's degree in computer science, data science, engineering, or a related field. However, a master's degree or Ph.D. is often preferred, especially for roles that involve complex problem-solving and advanced research. These advanced degrees provide a deeper understanding of machine learning algorithms, data analysis, and statistical modeling, which are crucial for high-level positions.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate your expertise to potential employers. Some valuable certifications include:

• Certified Solutions Architect (AWS, Google Cloud, Azure): These certifications validate your ability to design and deploy scalable systems on cloud platforms.
• Certified Data Scientist (DASCA, SAS): These certifications focus on data science skills and methodologies.
• Machine Learning Certifications (Coursera, edX, Udacity): Courses and certifications from reputable online platforms can provide specialized knowledge in machine learning and AI.

Required Experience

Typically, a Senior-level or Expert Solutions Architect in AI/ML/Data Science is expected to have at least 8-10 years of experience in the field. This experience should include hands-on work with machine learning models, data analysis, and software development. Experience in leading projects, managing teams, and collaborating with cross-functional teams is also highly valued. Additionally, experience in specific industries, such as finance, healthcare, or technology, can be advantageous depending on the job requirements.

Related salaries

Want to contribute?