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

Salary details

The average senior-level / expert Solution Architect salary lies between USD 138,200 and USD 217,200 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. 17, 2024

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

The three most common job tag items assiciated with senior-level / expert Solution Architect job listings are Architecture, Machine Learning 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:

Architecture | 328 jobs Machine Learning | 290 jobs Python | 283 jobs Engineering | 280 jobs Azure | 244 jobs AWS | 228 jobs Computer Science | 226 jobs Security | 199 jobs SQL | 150 jobs GCP | 134 jobs Consulting | 123 jobs Agile | 114 jobs Java | 111 jobs APIs | 108 jobs Generative AI | 105 jobs Pipelines | 103 jobs Big Data | 101 jobs LLMs | 94 jobs Research | 93 jobs DevOps | 87 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert Solution Architect job listings are Career development, Health care and Flex hours. 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 | 294 jobs Health care | 163 jobs Flex hours | 114 jobs Medical leave | 78 jobs Team events | 77 jobs Competitive pay | 74 jobs Equity / stock options | 63 jobs Startup environment | 58 jobs Salary bonus | 42 jobs Parental leave | 39 jobs Insurance | 37 jobs Conferences | 35 jobs Wellness | 31 jobs Flex vacation | 30 jobs 401(k) matching | 21 jobs Transparency | 13 jobs Home office stipend | 13 jobs Unlimited paid time off | 8 jobs Flexible spending account | 7 jobs Travel | 6 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Solution Architect in AI/ML/Data Science typically includes a combination of a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the majority of the total compensation package, ranging from 60% to 80%. Bonuses can vary significantly depending on the company’s performance and individual achievements, usually accounting for 10% to 20% of the total compensation. Additional remuneration, such as stock options, can be a significant part of the package in larger tech firms or startups, sometimes making up 10% to 20% of the total compensation. The exact composition can vary based on the region, with tech hubs like Silicon Valley offering higher equity components, and industry, with finance and healthcare often providing higher bonuses. Company size also plays a role, with larger companies typically offering more structured bonus and equity packages.

Increasing Salary

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 to employers.
• Leadership Roles: Transition into leadership roles such as Chief AI Officer or Head of Data Science, which often come with higher compensation.
• Consulting: Consider moving into consulting, where you can leverage your expertise across multiple projects and potentially earn more through consulting fees.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML to remain competitive and justify salary increases.
• Networking: Build a strong professional network to learn about higher-paying opportunities and negotiate better offers.

Educational Requirements

Most Senior-level or Expert Solution 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 research. Advanced degrees can provide a deeper understanding of machine learning algorithms, data structures, and statistical methods, which are crucial for this role.

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, Azure, Google Cloud): These certifications validate your ability to design and deploy scalable systems on cloud platforms.
• Certified Data Scientist (DASCA, SAS, or other platforms): These certifications can demonstrate your proficiency in data science methodologies and tools.
• Machine Learning Certifications (Coursera, edX, or Udacity): These can provide a structured learning path and validate your skills in machine learning.

Required Experience

Typically, a Senior-level or Expert Solution 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 working with cross-functional stakeholders is also highly valued. Additionally, experience in a specific industry, such as finance, healthcare, or technology, can be beneficial.

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