The Role
Lead a hands-on platform engineering function spanning full-stack product development, real-time Kafka and ClickHouse data/ML pipelines, cloud infrastructure, DevOps, security, and reliability. Own React, Node.js, and MongoDB applications; Terraform, Kubernetes, AWS/GCP, Docker, and GitHub Actions; production observability and incident response; and SOC 2 readiness. Establish AI-assisted engineering workflows using tools such as Claude Code and Cursor while replacing vendor-built infrastructure with durable internal automation.
Summary Generated by Built In
Lead Platform Engineer, AI-Native — Full-Stack + Data/ML Pipelines + DevOps
Company: Revenue Roll Inc. / Tie
Location: Fully remote, US-based
Compensation: $135,000 USD/year
Employment Type: Full-time, W-2
Benefits: Health, vision, and dental insurance + equity options
Reports to: CTO / Co-Founder
Tie 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.
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, US-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.
- This is the bar. If any one of these is a "no," the role isn't a fit:
- 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've debugged production systems under pressure.
- I use AI coding tools every day and can walk through my workflow.
- I want startup equity upside enough to take broad ownership.
- Data & 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. You own the path from commit to production, and the cost and reliability of what runs there.
- 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.
- Map 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.
- Replace vendor-dependent infrastructure with durable, internally-owned Terraform/Kubernetes automation.
- 7+ 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.
- Real cloud infrastructure depth: 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.
- Proven experience operating production systems with logs, metrics, traces, alerts, and incident response under pressure.
- 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 environment with high ownership, incomplete documentation, and shifting priorities.
- ML/feature pipelines, model serving, or data-quality tooling at scale
- Snowplow/SnowcatCloud, BigQuery, dbt, Neo4j, RisingWave, Airbyte
- OpenTelemetry, Sumo Logic, Grafana, Prometheus
- Auth0, 1Password CLI, SOC 2, GitGuardian, TruffleHog, security automation
- 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
A senior IC who can lead without a team beneath them. Full-stack enough to ship product, pipeline-literate enough to own the data the business depends on, infrastructure-literate enough to own production. AI-native but not reckless. Comfortable replacing vendor dependency with internal leverage. Fast, opinionated, pragmatic, and able to debug across frontend, backend, data pipeline, cloud, and deployment layers.
- Because the role is multifaceted, the loop is tailored to each candidate rather than a fixed gauntlet: a CTO screen, a technical deep dive, a short AI-assisted practical (work through part of a repo with AI, propose a change, add tests, explain the risks), and a domain session matched to your strengths — a Kafka/ClickHouse pipeline design for data-heavy candidates, a React/Node build for product-heavy ones — plus an infra/incident scenario, and a final founder working session.
Compensation: $135,000 USD/year (full-time, W-2)
Equity: Meaningful early-stage equity, commensurate with seniority and ownership scope (standard 4-year vest, 1-year cliff)
Benefits: Health, vision, and dental insurance
Revenue Roll Inc. (DBA Tie) is an equal opportunity employer.
Skills Required
- 7+ years of software engineering experience, including production ownership
- Hands-on production ownership of data and streaming pipelines using Kafka and ClickHouse or directly comparable technologies
- Operational experience with pipeline throughput, retention, schema evolution, backfills, and reliability
- Strong full-stack experience with TypeScript or JavaScript, React, Node.js, Express and/or NestJS, and MongoDB
- Hands-on ownership of AWS and/or GCP infrastructure, Terraform, Kubernetes, Docker, CI/CD, secrets management, and deployment automation
- Experience operating production systems with logs, metrics, traces, alerts, and incident response under pressure
- Demonstrable experience using AI coding tools to increase engineering output
- Strong architectural judgment and ability to design systems, simplify them, and explain tradeoffs
- Comfort working in a lean startup with incomplete documentation and shifting priorities
- Experience with ML or feature pipelines, model serving, or data-quality tooling at scale
- Experience with Snowplow or SnowcatCloud, BigQuery, dbt, Neo4j, RisingWave, or Airbyte
- Experience with OpenTelemetry, Sumo Logic, Grafana, or Prometheus
- Experience with Auth0, 1Password CLI, SOC 2, GitGuardian, TruffleHog, or security automation
- Experience modernizing contractor- or vendor-built systems into internally owned infrastructure
- Prior founding engineer, staff engineer, DevOps lead, or architect experience
- Experience with martech, adtech, e-commerce, customer data platforms, identity graphs, billing, or fintech workflows
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The Company
What We Do
Tie is an AI-powered shopper-intelligence platform for ecommerce brands. It helps marketing teams identify anonymous website visitors, connect shopper identities across devices and channels, enrich profiles with demographic and intent data, and predict purchase and engagement likelihood. Tie also optimizes email inbox placement and sends actionable audiences into existing marketing systems, helping brands personalize outreach, improve customer acquisition and retention, and earn more from web traffic.
