Senior Lead Software Engineer

Responsibilities

• Provide technical guidance to engineers, contractors, and vendors in alignment with business goals.
• Develop, review, debug, and improve secure, high-quality production code.
• Influence product design, application functionality, and technical operations.
• Architect and deploy secure, scalable cloud platforms optimized for AI/ML workloads.
• Translate AI team compute requirements into infrastructure requirements.
• Monitor, manage, and optimize cloud resources for performance and cost efficiency.
• Build CI/CD automation and infrastructure-as-code for ML deployment and operations.
• Drive adoption and governance of approved AI-assisted engineering practices across teams.
• Establish validation standards for secure coding, peer review, automated testing, and AI-generated outputs.
• Promote responsible, compliant use of AI-assisted development tools and coach senior engineers and leads on usage patterns and controls.

Requirements

• Formal training or certification in software engineering concepts and at least 5 years of applied experience.
• Hands-on experience with system design, application development, testing, and operational stability.
• Strong experience with Kubernetes and Docker, including cluster operations and production troubleshooting.
• Proficiency in at least one of Python, Go, Java, or C#.
• Ability to independently solve design and functionality problems with minimal oversight.
• Knowledge of IaaS, PaaS, SaaS, and public, private, and hybrid cloud deployment models.
• Understanding of machine learning concepts including transformer architecture, training, and inference.
• Experience with infrastructure-as-code and cloud component architecture.
• Experience leading enterprise-authorized AI-assisted software development tools and validating their correctness, performance, and security.
• Understanding of responsible AI practices, data sensitivity, secure input/output handling, resiliency, and security expectations.
• Preferred qualifications include NVIDIA GPU infrastructure, Prometheus, Grafana, MLflow, vLLM, Ray.io, Slurm, network architecture, database programming, data modeling, cloud data services, big data processing tools, and Linux.

Benefits

• Competitive total rewards package with role-, experience-, skill-, and location-based base salary determination.
• Eligible roles may receive commission-based pay or discretionary incentive compensation in cash or forfeitable equity.
• Comprehensive health care coverage and on-site health and wellness centers.
• Retirement savings plan, backup childcare, tuition reimbursement, mental health support, and financial coaching.
• Employment is contingent on review of criminal conviction history under Section 19 of the Federal Deposit Insurance Act.