Staff Engineer – AI Platform & Engineering Strategy | Jobs in US

Key Responsibilities

• Lead engineering strategy and technical roadmap execution.
• Drive platform modernization and large-scale system migration.
• Build scalable, secure, and highly available software architecture.
• Implement AI-powered development workflows across the SDLC.
• Design and maintain CI/CD pipelines, monitoring, and deployment processes.
• Lead data migration, architecture redesign, and platform integrations.
• Establish engineering standards, code quality, testing, and documentation.
• Own privacy, security, governance, and compliance initiatives.
• Collaborate with Product Leadership to transform business goals into engineering deliverables.
• Mentor engineers and foster a high-performance engineering culture.
• Manage engineering vendors, contractors, and internal development teams.
• Ensure AI-powered products meet safety, privacy, and quality standards.

Required Skills

• Full Stack Development
• Backend Development
• AI Engineering
• Large Language Models (LLMs)
• Airtable
• System Architecture
• Cloud Infrastructure
• CI/CD
• Software Design
• API Development
• Database Design
• DevOps Practices
• Security Best Practices
• Technical Leadership
• Agile Methodologies
• AI Experience
• Experience working with Machine Learning systems and AI-powered applications.
• Hands-on experience building AI-first production systems.
• Experience implementing AI-assisted software development workflows.
• Knowledge of Generative AI development tools.
• Experience integrating AI into engineering processes.
• Familiarity with AI evaluation, monitoring, and testing.
• Understanding of AI governance, safety, and privacy.
• Managerial Experience
• Lead and mentor engineering teams.
• Manage full-time engineers, contractors, and vendors.
• Define engineering processes and delivery standards.
• Collaborate with executive leadership on technical strategy.
• Drive cross-functional execution across Product, Engineering, and Operations.
• Build a culture of accountability, ownership, and innovation.
• Operational Experience
• Platform modernization and migration.
• Engineering operations and release management.
• Monitoring, logging, and incident response.
• Security implementation and governance.
• Performance optimization.
• Infrastructure scalability.
• Data governance and lifecycle management.
• Risk management and engineering reporting.
• National-scale application architecture.

Education & Certifications

• Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related discipline.
• 5–7 years of software engineering experience.
• Proven experience delivering AI-enabled software products.
• Startup or high-growth technology experience preferred.
• EdTech experience is an added advantage.
• AWS Certified Solutions Architect
• Google Professional Cloud Architect
• Microsoft Azure Solutions Architect
• Certified Kubernetes Administrator (CKA)
• AI/ML or Cloud Engineering Certifications (Preferred)