Sr Lead Software Engineer - AWS - Lead AI/ML Platform Engineer
Salary not listed • Jersey City, NJ, United States • Full-time
Posted 1mo ago
No salary is listed. Many US states require employers to post a pay range, so ask about pay early.
About the job
As a Senior Lead Software Engineer on the Firmwide AI/ML Deployment Platform team, you will be a key part of a globally distributed team responsible for architecting, building, and owning the infrastructure that enables model deployment at scale. You will have significant autonomy, driving technical direction, engaging directly with clients, and making critical architectural decisions. The team builds the control plane, APIs, monitoring, and deployment infrastructure that internal teams rely on, constantly evolving to meet new scale requirements and challenges. This role is ideal for someone who enjoys owning problems end-to-end, making difficult tradeoffs, and shipping systems that empower other engineers.
Responsibilities
- Drive architectural vision for platform components including control plane integration, multi-region deployment, and disaster recovery.
- Design and implement APIs for retraining, scheduling, endpoint deployment, and autoscaling.
- Build infrastructure for seamless integration across control plane and client accounts.
- Engage directly with clients to gather requirements, provide strategic solutions, and debug issues.
- Make independent architectural decisions and own technical tradeoffs with minimal oversight.
- Provide technical guidance and direction to business and technical teams, contractors, and vendors.
- Drive decisions influencing product design, application functionality, and technical operations.
- Drive adoption and governance of approved AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes.
- Apply knowledge of SDLC toolchain, including AI-assisted development and automation, to enhance automation value at scale.
- Establish measurable validation standards for AI-assisted engineering practices and promote reuse of proven patterns.
Requirements
- 5+ years of applied experience with formal training or certification on software engineering concepts.
- Industry experience as a platform engineer leading large-scale platform infrastructure delivery.
- Deep AWS expertise in networking (VPCs, DNS, cross-account connectivity, service mesh), scalability, multi-account architectures, and security.
- Strong hands-on proficiency in Golang or Python.
- Advanced Terraform and HCL skills, including module design, state management, and multi-region/multi-account delivery.
- Production experience with Kubernetes/EKS at scale.
- Hands-on experience with AWS SageMaker for model deployments and inference.
- Strong DevOps background with complex CI/CD pipelines, infrastructure automation, and deployment strategies.
- Self-directed with demonstrated ability to make architectural decisions and drive outcomes with minimal oversight.
- Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools.
- Ability to set team expectations for validating AI outputs for correctness, performance, and security.
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs/outputs, and adherence to resiliency/security expectations.
- Experience coaching senior engineers/leads on compliant AI usage patterns and controls.