AI Solution Architect Jobs
AI Solution Architect jobs are open across technology, financial services, healthcare, and manufacturing, from mid-level to principal and distinguished engineer, with specializations in generative AI, cloud-native AI platforms, and enterprise MLOps. Find a role that fits from the openings below and apply directly.
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Work you'll do/Responsibilities
- Shape enterprise architecture strategies for complex technology programs, aligning solutions with client blueprints and long-term objectives.
- Design secure, scalable data platforms and AI-driven analytical solutions for capital markets and financial services organizations.
- Translate complex business challenges into innovative technology solutions that deliver measurable business outcomes.
- Develop technology roadmaps by evaluating emerging technologies, platforms, infrastructure, and AI capabilities.
- Architect advanced data pipelines and ETL solutions using Python and PySpark across relational, warehouse, and cloud-native environments.
- Design and manage distributed data processing solutions using Hadoop, Cloudera, distributed file systems, and NoSQL databases.
- Apply AI-assisted development tools, CI/CD practices, and container orchestration to improve quality and accelerate delivery.
- Serve as a senior technical advisor, mentoring development teams and governing architecture and engineering best practices across transformation programs.
The Team
Join our AI & Engineering team in transforming technology platforms, driving innovation, and helping make a significant impact on our clients' success. You'll work alongside talented professionals reimagining and re-engineering operations and processes that are critical to businesses. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation.
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.
Qualifications
Required
- 6+ years of experience in IT architecture, systems design, or a related technical discipline, with experience delivering enterprise-scale data and/or AI solutions in complex environments.
- 6+ years of experience with distributed data platforms in the Hadoop ecosystem, preferably Cloudera, including HDFS, Hive, Pig, Sqoop, and MongoDB.
- Experience delivering AI and data architecture solutions within Financial Services, particularly Capital Markets, Fraud Detection, Risk Analytics, or Regulatory Reporting.
- Strong proficiency in Python and PySpark, including Pandas, NumPy, and Pydantic, as well as modern data architectures such as Lakehouse, Medallion, Kafka, Flink, Data Mesh, and OLAP/OLTP modeling.
- Hands-on experience designing enterprise Generative AI solutions, including RAG pipelines, LLM integration, prompt engineering, multi-agent workflows, and vector databases such as Pinecone, FAISS, or Azure AI Search.
- Experience with CI/CD, Git, Docker, and Kubernetes, along with the organizational skills to manage multiple workstreams, take ownership of complex challenges, and deliver under tight deadlines
- Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
- Limited immigration sponsorship may be available
- Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve. This may include overnight travel.
Preferred
- Master's degree in Computer Science, Data Science, Software Engineering, Mathematics, or a related quantitative discipline, and/or equivalent professional experience delivering enterprise AI and data solutions.
- Commercial & Strategic Vision: Familiarity with competitor technology products and services, with a deep understanding of how architectural specialisms contribute to commercial outcomes and Return on Investment (ROI).
- Cloud Platform & Infrastructure: Hands-on experience designing and deploying solutions on major cloud platforms (AWS, Azure, or GCP), including cloud-native data services (Databricks, Snowflake) and applying infrastructure engineering principles alongside software architecture.
- Project & Program Management: Experience managing and delivering complex, multi-workstream technology programs, including stakeholder management, resource planning, and milestone governance.
- Industry Certifications: Relevant certifications such as AWS Certified Data Analytics, Google Professional Data Engineer, Databricks Certified Associate, or equivalent cloud and data architecture qualifications.
AI Solution Architect Jobs by Experience Level
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Find AI Solution Architect JobsAI Solution Architect Job Market
Who's Hiring



Top Industries Hiring
- Technology & Software
- Fintech
- Insurance
- Manufacturing
- Staffing & Recruiting
What Employers Look For
The qualifications that appear most often in AI solution architect jobs.
- 5 or more years of experience designing and deploying AI or ML solutions at enterprise scale
- Proficiency with cloud AI services on AWS, Azure, or Google Cloud Platform
- Experience with large language models, generative AI frameworks, or foundation model integration
- Strong background in data architecture, including pipelines, feature stores, and model serving infrastructure
- Ability to communicate technical architecture decisions to non-technical executive stakeholders
- Bachelor's or master's degree in computer science, engineering, or a closely related technical field
Tips for Your AI Solution Architect Job Search
Tailor your resume to architecture layers
Hiring managers for ai solution architect roles scan for evidence you've designed end-to-end AI systems, not just built models. Call out the integration layer, data pipeline decisions, and trade-offs you owned in each project, not just the tools you used.
Show cloud certification depth not breadth
Having AWS, Azure, and GCP badges looks unfocused to most hiring panels. Pick the platform your target employer runs and lead with the professional-level AI or ML specialty certification for that platform. It signals real deployment experience, not course completions.
Filter openings by stack before applying
Many ai solution architect postings list identical titles but mean very different roles: one is pre-sales, another is internal platform engineering. Read the requirements past the first paragraph to confirm the role centers on technical design, not client demos or sales support.
Apply early to roles that fit
Migrate Mate lists ai solution architect openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare a system design portfolio piece
Interviewers for ai solution architect positions routinely ask you to whiteboard a production AI system from scratch. Having one well-documented architecture you designed, including your reasoning on scalability, latency, and cost, gives you a concrete answer rather than a hypothetical.
Negotiate scope before negotiating title
Once you have an offer, clarify whether the role owns architecture decisions or advises them. An advisory role with an architect title limits your portfolio growth. Confirm who you report to, what decisions require sign-off, and whether you have budget authority before accepting.
AI Solution Architect Jobs: Frequently Asked Questions
Which companies are hiring the most ai solution architects?
The companies hiring the most ai solution architects right now include Booz Allen Hamilton, Koch, and Lenovo, with the largest share of openings in Texas, Virginia, and California, based on current listings on Migrate Mate as of September 2026. Demand is concentrated at large technology vendors, cloud platform providers, and enterprise consulting firms with active AI transformation practices.
How many ai solution architect jobs are remote?
About 67% of ai solution architect openings are fully remote or hybrid as of September 2026, making it one of the more distributed roles in enterprise technology hiring. Sub-areas that skew most remote include generative AI integration work, pre-sales architecture, and platform consulting, where client delivery happens over video rather than on-site.
How do you become an ai solution architect?
Start by building hands-on depth in one cloud platform's AI and ML services, then move into roles where you own system design rather than individual model development. Pursue a professional-level AI or ML certification, document two or three complete architectures you designed from requirements through production deployment, and practice explaining your technical trade-off decisions to non-technical audiences, since that communication skill is what separates architects from senior engineers in most hiring processes.
Can you get an ai solution architect job with little experience?
Getting hired directly into an ai solution architect role with no prior architecture experience is uncommon, but transitioning from a senior data engineer, ML engineer, or cloud solutions engineer position is a realistic path. Build a public portfolio of system design artifacts, contribute to open-source AI infrastructure projects, and target smaller companies or startups where the architect title covers a broader scope and the bar for prior experience is lower than at large enterprises.
What does the ai solution architect interview process look like?
The process typically runs across four to five stages: an initial recruiter screen, a hiring manager conversation focused on your architecture background and leadership style, a technical system design round where you design an AI solution live on a whiteboard or shared doc, a panel interview with engineering and product stakeholders, and a final leadership or executive conversation. Some employers add a take-home design case or ask you to present a past architecture to the panel.
Where can I find and apply to ai solution architect jobs?
You can find and apply to ai solution architect jobs on Migrate Mate, which lists current openings from companies across the United States. Search the listings to find roles that match your background and apply directly to each one that fits.
See All 63 AI Solution Architect Jobs
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