Lead Software Platform Engineer

Job summary

TetraScience is seeking a Lead Platform Engineer to architect and evolve shared Platform Core services, designed to absorb 100x growth in data volume and users. This role involves owning cross-cutting primitives like authorization, metadata, governance, and high-throughput event processing, acting as a technical design authority across product and engineering. The ideal candidate will have experience building authorization and governance systems as products and thrive on turning ambitious scalability goals into concrete technical strategy.

Benefits

Qualifications

• 10+ years of hands-on software engineering experience, with a proven track record of designing, building, and scaling distributed, cloud-native backend services and platforms in production.
• Demonstrated experience as a technical leader or architect, making key decisions on system design, scalability, performance, and cost optimization.
• Strong proficiency in API-first design, including REST, GraphQL, and OpenAPI specifications for scalable, secure, versioned, and extensible APIs.
• Strong proficiency in TypeScript and Python, with a focus on building highly performant backend services.
• Expertise in AWS cloud services and architecture, including deep experience with core services (e.g., EC2, Lambda, ECS/EKS, IAM, S3) and advanced data and messaging tools (e.g., SQS, Kinesis, Kafka, EventBridge).
• Expert knowledge of infrastructure-as-code frameworks such as CloudFormation and CDK, CI/CD pipelines, and strong opinions on production deployment strategy.
• Solid understanding of observability best practices, including monitoring, alerting, and distributed tracing for SLI/SLO/SLA design.
• Ability to articulate ideas clearly, present findings persuasively, and build rapport with clients and team members.
• Strong collaboration skills and ability to partner effectively with cross-functional teams.

Responsibilities

• Architect and evolve cloud-native platform and services to support high-throughput, low-latency data processing patterns and customer-facing features, meeting scalability requirements.
• Design scalable, distributed systems for authentication, authorization, data lifecycle management, metadata management, operational intelligence, and real-time event processing.
• Evolve authorization service towards modern identity standards and customer-configurable, fine-grained access models, including authorization for non-human identities.
• Build systems to capture and enforce structured metadata at ingest and serve through clean service contracts, collaborating across platform metadata and semantic/ontology layers.
• Build governance primitives for regulated environments, including compliance-grade audit trails, dataset-level access controls, and approval/eSignature workflows.
• Collaborate with engineering and product teams to deliver infrastructure supporting new services, customer-facing applications, and high-volume data processing workloads.
• Build and maintain infrastructure-as-code (e.g., CloudFormation, AWS CDK) to automate, standardize, and secure deployments for online upgrades and on-demand infrastructure allocation.
• Enhance observability and monitoring to ensure reliability, cost efficiency, and rapid incident response.
• Champion best practices in distributed systems design, scalability, and performance optimization, sharing architectural insights through design reviews and technical documentation.

Skills

Languages

Relocation