Data & AI/ML Architect

Join Aya Healthcare, winner of multiple Top Workplace awards!

We are seeking a highly skilled Data and AI/ML Architect to design and implement scalable data platforms and intelligent systems that power analytics, automation, and decision-making across the organization. This role bridges data engineering, cloud architecture, and machine learning, defining best practices for data management, model deployment, and AI-driven business solutions. The ideal candidate thrives in an Agile environment, fostering collaboration, adaptability, and continuous delivery of high-value data and AI capabilities.

Who We Are:

We’re a $8+ billion, rapidly growing workforce solutions provider in the healthcare industry. We deliver tech-enabled services that help healthcare organizations meet and manage their contingent labor needs. We build and manage tech-enabled marketplaces for national and local healthcare talent and deliver contingent labor management solutions through our proprietary software platform.

At Aya, we’re obsessed with creating exceptional experiences for our clients, clinicians, and employees. In fact, we put employee satisfaction above all else. Our team members are responsible for incomparable customer experience and we know that happy employees are critical to maintaining happy clients. We foster an entrepreneurial, high-energy, low-bureaucracy culture and value innovative thinking and creative problem solving. We embrace diversity in thought and backgrounds unified by a commitment to high achievement. When you join Aya, you’ll be surrounded by teammates who care about you as an individual and leaders who will help you grow both personally and professionally.

Responsibilities:

Architecture & Strategy

• Design end-to-end data and AI architectures across cloud and hybrid environments (e.g., Azure, AWS, GCP).

• Define data and model lifecycle management frameworks that support ingestion, transformation, storage, and consumption at scale.

• Establish and enforce governance, security, and compliance standards for AI and data usage.

• Partner with stakeholders in Agile planning sessions, sprint reviews, and backlog prioritization to translate business goals into technical architectures and roadmaps.

Data Engineering & Infrastructure

• Develop robust, modular data pipelines using tools such as Databricks, Spark, Airflow, or Synapse.

• Implement Agile-friendly CI/CD frameworks for data and ML workloads to support incremental delivery and continuous improvement.

• Optimize systems for real-time analytics, batch processing, and ML training pipelines.

• Lead the adoption of data lakehouse and semantic layer architectures to unify structured and unstructured data sources.

AI/ML Systems Design

• Architect scalable solutions for machine learning, generative AI, and predictive analytics, from experimentation to production deployment.

• Integrate MLOps and Agile DevOps practices for model lifecycle management, leveraging tools like MLflow, Kubeflow, Vertex AI, or Azure ML.

• Oversee model governance, explainability, and performance monitoring frameworks.

• Collaborate with cross-functional teams in Agile sprints to experiment, validate, and iterate on AI prototypes.

Leadership & Collaboration

• Champion Agile and DevOps methodologies, promoting iterative development, continuous learning, and feedback-driven improvement.

• Mentor engineers, data scientists, and analysts in modern AI and data architecture practices.

• Collaborate closely with product owners, Scrum Masters, and stakeholders to align AI initiatives with business value creation.

• Stay ahead of emerging trends in data platforms, AI frameworks, and responsible AI governance.

Required Qualifications:

• Bachelor’s or master’s degree in computer science, Data Engineering, or related field.

• 8+ years of experience in data architecture, ML engineering, and cloud architecture.

• Deep experience with cloud data platforms (Azure Synapse, AWS Redshift, GCP BigQuery).

• Proficiency in Python, SQL, and modern data frameworks (Spark, Databricks, Snowflake, etc.).

• Strong understanding of Agile frameworks (Scrum, Kanban) and collaboration tools (Jira, Confluence, Azure DevOps).

• Solid grounding in MLOps, data pipelines, API design, and data security.

Preferred Experience

• Experience with GenAI/LLM-based applications (OpenAI, Anthropic, Azure OpenAI, etc.).

• Familiarity with vector databases, knowledge graphs, or AI orchestration frameworks.

• Certifications in cloud or data architecture (e.g., Azure Solutions Architect, AWS Data Analytics Specialty).

• Excellent communication and leadership skills, able to articulate technical concepts in cross-functional Agile settings.

What We Offer:

• Free premium medical, dental, life and vision insurance

• Generous 401(k) match

• Aya also offers other benefits to those that are eligible and where required by applicable law, including reimbursements and discretionary bonuses

• Aya provides paid sick leave in accordance with all applicable state, federal, and local laws. Aya’s general sick leave policy is that employees accrue one hour of paid sick leave for every 30 hours worked. However, to the extent any provisions of the statement above conflict with any applicable paid sick leave laws, the applicable paid sick leave laws are controlling

• Celebrations! We hit our goals and reward ourselves.

• Company-sponsored virtual events, happy hours and team-building activities are always on the horizon — plus, you get a special treat on your birthday!

• Unlimited DTO — we believe in time off!

• Virtual yoga, meditation or boot camp classes offered daily

Compensation: Aya reasonably anticipates the pay scale for this position to be an annual salary of $200,000 to $215,000.

The pay scale for this position may vary if applicant possesses experience outside of what Aya reasonably anticipates for this position. Bonuses are subject to the role and your manager’s discretion.

Aya is an Equal Opportunity Employer (EEO), including Disability / Vets, and welcomes all to apply. Please click here for our EEO policy