Lead Platform Engineer, AI-Native — Full-Stack + Data/ML Pipelines + DevOpsCompany: Fully remote, Canada-based Engagement Type: B2B contractor About TieTie builds high-scale data infrastructure for digital commerce: identity resolution, customer intelligence, marketing analytics, and the activation systems that turn anonymous traffic into revenue for 200+ brands. Our platform spans customer-facing SaaS, real-time data and ML pipelines, multi-cloud infrastructure, and automation-heavy internal tooling. We're a Series A company heading into a Series B, and our engineering org is deliberately small, deeply automated, and ships like a team three times its size.

About the Role
We're hiring one Lead Platform Engineer to operate as a hybrid force multiplier across product engineering, data/ML pipelines, infrastructure, and AI-assisted development. This single hire consolidates work currently spread across contractors and vendors into one high-agency, Canada-based engineering owner. You should be senior enough to own production end to end, fluent enough in data and streaming systems to own the pipelines that the business runs on, pragmatic enough to ship application code, and AI-native enough to dramatically increase throughput using tools like Claude Code, Cursor, and agentic workflows. This is a hands-on technical leadership role, not a management role. You Can Credibly Say Yes to All FiveThis is the bar. I can ship React/Node/Mongo product features and build the data/ML pipelines (Kafka, ClickHouse) myself. I can own Terraform/Kubernetes/GCP/AWS/CI-CD without leaning on a vendor. I use AI coding tools every day and can walk through my workflow. What You'll OwnData & ML Pipelines (core) Own the systems the business runs on: real-time event ingestion and streaming through Kafka,



analytical and feature data in ClickHouse, and the transformation and ML workflows on top. You'll design, operate, debug, and scale these pipelines — partitioning, retention, schema evolution, backfills, and the reliability of data moving end to end. Platform Engineering Build, refactor, and scale core product surfaces — React frontends, Node/Express/Nest-style services, and MongoDB-backed APIs — plus the integrations, onboarding, billing, and customer-facing analytics that sit on top. Infrastructure & DevOps Take ownership of CI/CD (GitHub Actions), Terraform, Kubernetes, AWS/GCP infrastructure, secrets management, deployment reliability, and environment automation. AI-Native Engineering Use AI aggressively and responsibly to accelerate delivery — scaffolds, tests, migrations, code review, observability queries, runbooks, Terraform modules, and data-debugging workflows — while applying senior engineering judgment, security discipline, and production rigor. Security, Compliance & Reliability Own practical SOC 2 readiness, audit-friendly CI/CD, secrets rotation, IAM hygiene, observability (OpenTelemetry, Sumo Logic), and incident response.

What You'll Do
in the First 90 DaysMap the current platform, repos, environments, pipelines, cloud resources, and deployment paths. Take over day-to-day ownership of the data/ML pipelines (Kafka, ClickHouse) and high-priority full-stack tickets. Harden CI/CD for critical services:



tests, build validation, deployment controls, and rollback procedures. Establish an AI-assisted engineering workflow the rest of the team can use — repeatable prompts, review workflows, test generation, and infra/debugging agents. Improve production and pipeline observability across services, containers, and data flows. Required Background7+ years of software engineering experience, including production ownership. Hands-on ownership of data/streaming pipelines — Kafka and ClickHouse (or directly comparable) in production, including the operational side (throughput, retention, schema, backfills, reliability). Strong full-stack experience with TypeScript/JavaScript, React, Node.
Js, Express and/or NestJS, and MongoDB. AWS and/or GCP, Terraform, Kubernetes, Docker, CI/CD (GitHub Actions), secrets management, deployment automation — owned as your responsibility, not handed to a separate ops team. Demonstrably AI-native: real work where AI tooling multiplied what you shipped, and a workflow you can walk through. Strong architectural judgment — can design systems, simplify them, and explain tradeoffs. Comfort in a lean startup setting with high ownership, incomplete documentation, and shifting priorities. ML/feature pipelines, model serving, or data-quality tooling at scale Experience modernizing contractor
- or vendor-built systems into durable internal infrastructure Prior founding engineer, staff engineer, DevOps lead, or architect experience Martech, adtech, e-commerce, customer data platforms, identity graphs, billing, or fintech workflows What "Great" Looks LikeA senior IC who can lead without a team beneath them. Full-stack enough to ship product, pipeline-literate enou

📌 Lead Platform Engineer, Ai-Native (Winnipeg)
🏢 Revenue Roll
📍 Winnipeg