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Salary
≈ $128k – $284k per year (Estimated)
Location
Remote (likely United States, Canada, EST hours)
Seniority
Principal · 7+ years exp

Confirmed on the employer's own hiring board on Nov 5, 2026. First seen by Alion on Sep 26, 2026.

Overview
Company
Impact
Profile match
Improvado is a marketing intelligence and revenue analytics technology enterprise specializing in automated data management and marketing pipeline orchestration. The company focuses on data extraction, ETL transformation, cross-channel attribution modeling, reporting automation, and AI-driven revenue insights by connecting over 1,000 marketing and sales data sources into unified analytics dashboards and data warehouses. Headquartered in San Francisco, California, it serves mid-market and enterprise marketing teams, digital advertising agencies, and corporate revenues teams across North America, Europe, and global markets.

We're a fast-growing Series A startup ($34M raised, $10.3M ARR, 75% gross margin) building the unified marketing intelligence platform for enterprises like Spotify, Asus, and Colgate. Our Platform Team owns the core data pipeline infrastructure powering 500+ integrations - and we're now rebuilding how that work gets done, with AI at the center.

We're looking for a Principal Engineer who can set the technical direction for AI-assisted engineering across the Platform Team - someone who doesn't just use AI tools, but defines how they're used responsibly at scale.

About the Role

You'll be the architectural voice on the Platform Team, shaping how we design, build, and evolve our core Python-based extraction and load infrastructure. More than that, you'll own the engineering practices shift: defining how agentic coding, AI-assisted development, and LLM tooling integrate into our delivery process without sacrificing reliability or maintainability. This is a hands-on role - you'll be writing code, reviewing architecture, and mentoring engineers, not just advising.

Responsibilities

  • Own platform architecture: design and evolve data extraction, load, and pipeline systems serving 500+ integrations at scale
    • Identify architectural bottlenecks and drive performance/reliability improvements at scale (Kubernetes, distributed systems, ClickHouse/PostgreSQL)
    • Lead modernization of legacy systems (LES, DSAS, ULS) into scalable, AI-native infrastructure
  • Design and implement agentic development frameworks for codebase maintenance and continuous improvement - owning the full loop from AI-assisted development to automated acceptance and rollout, with proper validation, testing, and architectural guardrails
    • Make and document key technical decisions; set the bar for code quality, system reliability, and performance
  • Mentor and level up engineers on AI-assisted development practices - help them ship faster without introducing hidden risk
  • Collaborate cross-functionally with product and AI teams on agentic framework rollout and new integration capabilities

Requirements

  • 7+ years of backend engineering (hands-on programming), with at least 2 years in a principal/architect-level role owning production systems
  • You've designed and scaled complex systems, not just maintained them
  • Hands-on experience with AI-assisted development (Claude Code, agentic coding) - you ship with it, know its limits and where they break, and have built agentic frameworks for code maintenance and rollout
  • Strong distributed systems background: Kubernetes, workflow orchestration (e.g. Temporal), message queues (e.g. RabbitMQ)
  • Experience building secure systems that are hard to break, hard to breach, and resilient
  • Experience with reliability practices at scale: observability, alerting, incident response
  • Solid SQL and query optimization across PostgreSQL and ClickHouse
  • Comfortable with ambiguity and high-velocity, fast-shifting priorities - we move like a startup, not a committee
  • Ability to work within EST timezone
  • Fluency in English

Nice to Have

  • Track record of defining engineering standards and driving adoption across a team
  • Experience migrating legacy pipeline systems
  • Background in data integration or ETL infrastructure

What We Offer

  • Remote-first environment
  • Direct impact on platform architecture - your decisions matter
  • Modern AI-native tech stack with real freedom to experiment
  • 20 PTO days + US holidays
  • Stock options
  • Professional development reimbursement
  • Optional relocation assistance to Latin America after trial period
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