Wizdaa

• Build, optimize, and scale data pipelines and infrastructure using Python, TypeScript, Apache Airflow, PySpark, AWS Glue, and Snowflake • Design, operationalize, and monitor ingest and transformation workflows: DAGs, alerting, retries, SLAs, lineage, and cost controls • Collaborate with platform and AI/ML teams to automate ingestion, validation, and real-time compute workflows; work toward a feature store • Integrate pipeline health and metrics into engineering dashboards for full visibility and observability • Model data and implement efficient, scalable transformations in Snowflake and PostgreSQL • Build reusable frameworks and connectors to standardize internal data publishing and consumption

• Build, optimize, and scale data pipelines and infrastructure using Python, TypeScript, Apache Airflow, PySpark, AWS Glue, and Snowflake • Design, operationalize, and monitor ingest and transformation workflows: DAGs, alerting, retries, SLAs, lineage, and cost controls • Collaborate with platform and AI/ML teams to automate ingestion, validation, and real-time compute workflows; work toward a feature store • Integrate pipeline health and metrics into engineering dashboards for full visibility and observability • Model data and implement efficient, scalable transformations in Snowflake and PostgreSQL • Build reusable frameworks and connectors to standardize internal data publishing and consumption

Role Description We're looking for a Senior Platform Engineer / SRE who can lead complex infrastructure work, drive IaC and GitOps architecture, and set the standard for how we automate and operate systems at scale. You'll tackle hard problems — multi-tenant isolation, self-service infrastructure, reliability engineering — and have the scope to solve them properly. This is not a ticket-processing role. Seniors here identify problems before they're asked, make architectural calls, mentor engineers, and raise the ceiling on what the platform can do. What You'll Work On - Lead IaC architecture — Terraform module design, state management, multi-account patterns, and setting the standards the rest of the team builds against - Drive GitOps at scale — ArgoCD configuration, progressive delivery patterns, promotion workflows, and deployment reliability across multiple environments and tenants - Architect and operate multi-tenant Kubernetes infrastructure on AWS EKS — tenant isolation, workload placement, cluster topology, and long-term scalability strategy - Build self-service infrastructure automation — provisioning pipelines, configuration management, and platform capabilities that engineering teams can consume without manual intervention - Lead the use of agentic coding tools for infrastructure work — scaffolding new environments, generating and reviewing IaC, accelerating automation, and establishing patterns for the team - Own reliability — SLO definitions, error budgets, incident response quality, and the feedback loop that turns incidents into platform improvements - Set observability standards — trace coverage, alert quality, on-call ergonomics, and runbook culture - Partner with security on zero-trust architecture, secrets management at scale, and infrastructure hardening - Contribute to technical roadmap and help the team prioritize the right work - Mentor mid-level engineers — code review, design feedback, on-call shadowing Qualifications - 6+ years in platform engineering, SRE, or infrastructure — with meaningful time operating production systems at scale - Deep IaC expertise — you design Terraform architectures, not just write modules; you've managed complex state and multi-account configurations in production - Strong GitOps background — you understand declarative infrastructure management at depth and have opinions on how to do it well - Deep Kubernetes knowledge — you've operated clusters in production, dealt with real failure modes, and understand the system at the control plane level - Strong AWS background — networking, compute, IAM, storage, multi-account design - Experience with multi-tenant infrastructure — isolation patterns, noisy neighbor mitigation, and tenant lifecycle management - Automation-first thinking at a senior level — you design systems that eliminate entire categories of manual work, not just individual tasks - Active user of agentic coding tools — you know how to direct them effectively, review their output critically, and use them to multiply your output - Reliability engineering track record — SLOs defined and measured, post-mortems run, measurable improvements driven - Strong communicator — you can make architectural decisions legible to engineers and leadership alike Nice to Have - Experience with Karpenter and node lifecycle management in production - Background in FinOps — cost attribution, reserved capacity planning, workload right-sizing - Familiarity with data infrastructure — object storage, CDC pipelines, or lakehouse patterns - Experience supporting AI/ML inference workloads or GPU-based compute in production - Prior experience scaling platform infrastructure at a startup moving toward enterprise-grade requirements What You Won't Find Here A platform team that maintains the status quo. We're actively building — new scale requirements, new architectural domains, new automation capabilities. Senior engineers here shape how the platform evolves, and the tools available to do it are better than they've ever been. Type: Full-Time, remote Work hours aligned with EST or PST

• Lead IaC architecture • Drive GitOps at scale • Architect and operate multi-tenant Kubernetes infrastructure on AWS EKS • Build self-service infrastructure automation • Lead the use of agentic coding tools for infrastructure work • Own reliability • Set observability standards • Partner with security on zero-trust architecture • Contribute to technical roadmap • Mentor mid-level engineers

• Lead IaC architecture • Drive GitOps at scale • Architect and operate multi-tenant Kubernetes infrastructure on AWS EKS • Build self-service infrastructure automation • Own reliability • Set observability standards • Partner with security on zero-trust architecture • Mentor mid-level engineers

Role Description Lead development of internal Kubernetes platform enabling scalable application deployment through GitOps. Engineer solutions for deployment complexity, database migrations, multi-environment management, and developer productivity. Drive DevOps practices including CI/CD automation, infrastructure operations, system reliability, and cross-team collaboration to accelerate software delivery. Responsibilities - Platform Engineering: - Build/maintain Helm charts - Engineer ArgoCD workflows - Develop deployment automation - Build database migration frameworks - Operate GitOps pipelines - Infrastructure: - Operate multi-cluster Kubernetes environments - Engineer observability solutions - Build ingress/service mesh/networking - Implement security policies - Manage cloud infrastructure - Operations: - Lead incident response - Engineer monitoring/alerting systems - Operate troubleshooting processes - Mentor operational practices - Drive reliability improvements - AWS/Cloud: - Engineer AWS infrastructure with Terraform - Operate Kubernetes/RDS/VPC/IAM - Optimize costs/performance - Build Infrastructure as Code patterns - Manage multi-account environments Qualifications - 5+ years DevOps/Platform/SRE/Cloud Engineering - Expert Kubernetes/containers - Advanced Helm templating - GitOps engineering (ArgoCD/Flux) - Expert AWS services - Advanced Terraform - Expert Linux operations - CI/CD engineering - Advanced monitoring systems - Database operations - Advanced automation (Bash/Python/Go) - Network engineering - Incident leadership - System troubleshooting Preferred - Platform engineering experience - PostgreSQL operations - Service mesh implementation - Database automation - Mobile deployment systems - Security engineering - Team mentoring - Large-scale system operations Certifications - CKA/CKAD - AWS Solutions Architect/DevOps Engineer - Terraform Associate

• Lead-level backend ownership • Make architecture decisions independently • Design systems with long-term scalability • Turn ambiguous product needs into production-ready backend solutions • Design and own backend services in NestJS and TypeScript • Build and maintain GraphQL APIs in a microservices environment • Own database design and optimization in Postgres • Define technical direction and enforce quality standards

• Lead frontend architectural direction • Define scalable technical patterns • Build shared foundations that increase quality, maintainability, and development velocity across the codebase • Shape the frontend as a system by raising the standard of architecture, shared infrastructure, engineering discipline, and long-term scalability • Use AI to accelerate execution, improve throughput, and enhance delivery while preserving sound technical judgment and high engineering standards

• Leads frontend architectural direction • Defines scalable technical patterns • Builds shared foundations that increase quality, maintainability, and development velocity across the codebase • Shapes frontend as a system by raising the standard of architecture, shared infrastructure, engineering discipline, and long-term scalability • Works in an AI-first environment, using AI to accelerate execution, improve throughput, and enhance delivery while preserving sound technical judgment and high engineering standards

• Lead-level backend ownership • Make architecture decisions independently, with a focus on scalability, maintainability, and reliability • Build and maintain GraphQL APIs across a microservices environment • Own database design, optimization, and reliability in Postgres • Define technical direction, not just implementation details • Set and enforce quality standards across both AI-generated and manually written code • Translate ambiguous product needs into clear technical solutions • Contribute to system design, infrastructure decisions, testing strategy, and developer productivity • Operate in an AI-first workflow without compromising engineering standards