AI Architect
Magna Legal Services
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇺🇸 United States
Visit company websiteSalary
💰 $175,000 - $200,000 per year
Job Level
SeniorLead
Tech Stack
AWSAzureCloudGoogle Cloud Platform
About the role
- Define and own Magna’s AI systems architecture, including model selection, data infrastructure, orchestration, and deployment pipelines
- Lead the design of scalable, secure, compliant AI solutions across the organization
- Establish development standards, MLOps best practices, and governance frameworks for responsible AI
- Architect, prototype, and deliver AI/ML applications — including summarization tools, document processing systems, scheduling automation, and proprietary medical/legal analysis products
- Oversee model fine-tuning, prompt engineering, data pipelines, evaluation frameworks, and performance monitoring
- Review and guide technical work across the AI engineering team
- Collaborate with executives, sales leaders, operations, and product teams to identify high-value AI opportunities
- Translate business challenges into technical solutions with clear ROI and measurable outcomes
- Communicate complex AI concepts in clear, accessible terms to non-technical stakeholders
- Drive cross-departmental adoption of AI systems through training, change management, and solution evangelism
- Manage, mentor, and grow an AI engineering team, providing career development, technical guidance, and performance oversight
- Promote a culture of experimentation, accountability, and continuous learning
- Collaborate with engineering, product, and data teams to ensure coordinated delivery
- Lead end-to-end lifecycle of AI products, from ideation and scoping through deployment and iteration
- Ensure solutions meet enterprise standards for security, data integrity, and privacy (HIPAA, PHI, PII, etc., as applicable)
- Measure business impact, track adoption, and ensure systems perform reliably at production scale
Requirements
- 8+ years of professional experience in AI/ML engineering, data science, or software architecture roles
- Proven track record designing, deploying, and maintaining AI products in real-world production environments
- Strong hands-on experience with modern AI stacks (LLMs, vector databases, embedding systems, orchestration frameworks, MLOps)
- Deep knowledge of cloud platforms (AWS, Azure, or GCP) and containerized environments
- Experience leading engineering teams or technical programs
- Ability to work closely with executives to shape strategy and communicate technical concepts clearly
- Strong understanding of data governance, compliance, and security in regulated or sensitive data environments
Benefits
- Competitive compensation
- Benefits
- Growth opportunities
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
AI systems architecturemodel selectiondata infrastructureMLOpsAI/ML applicationsmodel fine-tuningprompt engineeringdata pipelinesevaluation frameworksperformance monitoring
Soft skills
leadershipcommunicationcollaborationmentoringchange managementproblem-solvingstrategic thinkingaccountabilitycontinuous learningtraining