Solution Architect, Data Science and AI
Role details
Job location
Tech stack
Job description
The Solution Architect - Data Science & AI is a senior, client-facing technical leader responsible for designing and governing machine learning, advanced analytics, and generative AI solutions on Microsoft Azure and Databricks. This role demands deep expertise in data science, ML engineering, MLOps, and Gen AI - with enough architectural breadth across infrastructure, networking, and application development to participate credibly in cross-domain solution conversations. The ideal candidate is equally comfortable whiteboarding a model serving architecture during a presales pursuit as they are reviewing PySpark code, evaluating RAG retrieval quality, or designing an MLflow experiment tracking strategy.
This role spans the full engagement lifecycle, from presales architecture and deal shaping through delivery design assurance, ensuring that data science and AI solution intent is preserved from pursuit through implementation. The Solution Architect serves as a trusted technical authority to clients and internal teams alike, operating independently to lead workshops, shape solutions, and contribute to data strategy engagements alongside practice leadership.
Key Responsibilities
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Architect end-to-end machine learning and data science solutions on Azure and Databricks, from feature engineering through model serving and monitoring.
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Design and govern MLOps pipelines using Databricks MLflow, Model Serving, and related tooling to enable repeatable, production-grade model deployment.
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Architect generative AI solutions including Retrieval-Augmented Generation, agentic workflows, fine-tuning, document intelligence, embeddings, evaluation frameworks, and computer vision.
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Contribute to modern data estate architectures using Microsoft Fabric and/or Azure Databricks, including lakehouse patterns and medallion architecture, to support ML and analytics workloads.
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Contribute to client data strategy engagements including maturity assessments, analytics roadmaps, and governance frameworks in partnership with practice leadership.
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Independently lead client-facing presales engagements, discovery workshops, and architecture reviews as the primary technical authority on data science and AI pursuits.
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Develop level-of-effort estimates, architecture deliverables, and technical contributions to Statements of Work for client pursuits.
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Provide delivery design assurance and architectural governance across active data science and AI engagements, including code reviews of Python, PySpark, and ML model implementations.
Requirements
- 8+ years in data science, ML engineering, or AI
Travel up to 50%, * 8+ years in data science, ML engineering, or AI-focused solution architecture roles.
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Strong experience presenting to clients and architectural governance skills is mandatory.
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Prior experience working in a large consulting firm with strong preference to Microsoft Partner firms is mandatory.
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Knowledge of the Microsoft ecosystem is mandatory.
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Deep expertise in machine learning lifecycle - feature engineering, model training, evaluation, deployment, and monitoring.
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Strong hands-on proficiency in Python and PySpark, with the ability to conduct code reviews and contribute to delivery when needed.
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Strong expertise in Databricks, including MLflow, Model Serving, Unity Catalog, and Delta Lake.
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Demonstrated experience designing and deploying generative AI solutions - RAG architectures, agentic patterns, fine-tuning, embeddings, document intelligence, evaluation frameworks, or computer vision.
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Experience with Microsoft Fabric for analytics and data engineering workloads.
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Familiarity with Azure AI services including Azure OpenAI Service, Azure AI Search, and Azure Machine Learning.
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Proven client-facing consulting experience with the ability to independently lead presales and delivery engagements.
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Strong presentation and architectural governance skills.
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Demonstrated understanding of generative AI-assisted development tools and workflows, including GitHub Copilot, Claude Code, or spec-driven development practices, with the ability to apply these tools to accelerate architecture design, code generation, and delivery execution.
Preferred Qualifications
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Ph.D. or Master's degree in Mathematics, Statistics, Computer Science, or a related quantitative discipline.
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Experience in regulated industries.
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Familiarity with infrastructure and networking concepts - enough to collaborate effectively with platform architects on landing zones, networking, and security.
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Experience with data governance frameworks, data mesh or data product patterns.
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Azure migration and modernization experience for analytics and ML workloads.
Certifications (Preferred)
- Databricks Certified Machine Learning Professional or Associate.
Benefits & conditions
Base Salary Pay Range*: $170,000 - $200,000 USD/$155,000 - $215,000 CAD
*The current applicable Base Salary Pay Range for this role is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills relevant to the role, internal equity, alignment with market data, or other law., In addition to Base Salary, the successful candidate may be eligible to participate in the following plans / programs, upon satisfying all hiring requirements:
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Bonus Plan
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Medical, Dental and Vision Coverage
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Life Insurance and Disability Programs
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Retirement Savings with Company Match
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Paid Time Off
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Flexible Work Arrangements including Remote Work
