AI/ML Architect
Location: Sparks, MD
Type: Full-Time, Exempt
Overview
We are seeking an experienced AI/ML Architect to lead the design, deployment, and scaling of enterprise AI, machine learning, and Generative AI solutions. This role will drive AI strategy, architect cloud-native AI platforms, and build production-ready solutions leveraging AWS services, Databricks, and modern AI frameworks.
The ideal candidate has a strong background in cloud architecture, machine learning, Generative AI, MLOps, and large-scale data platforms, with hands-on experience building enterprise-grade AI applications.
Key Responsibilities
AI & Cloud Architecture
- Design and implement scalable AI/ML and Generative AI solutions within AWS environments.
- Develop enterprise architecture standards for AI platforms, model deployment, and governance.
- Ensure high availability, security, performance, and scalability of AI systems.
Agentic AI Solutions
- Architect and deploy autonomous AI agents and multi-agent workflows.
- Build production-ready conversational AI and agent-based systems.
- Design integrations between AI services, enterprise tools, and business applications.
Data & Machine Learning Platforms
- Develop and optimize end-to-end data pipelines and machine learning workflows using Databricks.
- Implement scalable data processing solutions utilizing Spark, Delta Lake, and MLflow.
- Support model training, deployment, monitoring, and lifecycle management.
Generative AI & Analytics
- Integrate Generative AI capabilities into enterprise applications.
- Enable natural language interactions with enterprise data and reporting platforms.
- Develop intelligent solutions that automate insights, recommendations, and decision-making processes.
MLOps & Governance
- Establish MLOps standards, model governance, monitoring, and compliance frameworks.
- Implement model registries, traceability, telemetry, and deployment automation.
- Ensure AI solutions meet security, operational, and regulatory requirements.
Technical Leadership
- Serve as the technical lead for AI and machine learning initiatives.
- Mentor engineering teams and provide architecture guidance.
- Partner with product, engineering, and business stakeholders to deliver AI-driven solutions.
Required Qualifications
Experience
- 7+ years of experience in software engineering, cloud architecture, data engineering, or related technical disciplines.
- 3+ years of experience designing and implementing AI/ML and Generative AI solutions in cloud environments.
- Proven experience building enterprise-scale AI applications from concept through production deployment.
Technical Expertise
- Strong hands-on experience with AWS AI and machine learning services.
- Deep knowledge of Databricks, Spark SQL, Delta Lake, and MLflow.
- Experience building conversational AI systems and agent-based architectures.
- Strong Python development skills.
- Experience with Infrastructure as Code (IaC), preferably Terraform.
- Understanding of modern MLOps practices, model governance, and CI/CD pipelines.
Preferred Experience
- Experience with GenAI frameworks such as LangGraph, CrewAI, or similar agent orchestration tools.
- Experience integrating AI systems with enterprise platforms and business applications.
- Familiarity with cloud-native application architecture and containerized environments.
Required Certifications
- AWS Certified Solutions Architect – Associate
- AWS Certified AI Practitioner
Preferred Certifications
- AWS Certified Solutions Architect – Professional
- AWS Certified Generative AI Developer – Professional
- Databricks Machine Learning Professional or Data Engineer Professional
- AWS Certified Machine Learning – Specialty
Compensaiton
- Salary: $150,000 - $200,000
- Benefits: PTO, Paid Holidays, Medical, Dental, Vision, 401(k), Sick Leave (as required by law).