2 publicaciones de empleo destacadas de data quality engineer en desde casa (¡Están contratando!)

Principal AI Engineer (Platform team)
Improvado —Desde casa
- Tiempo completo
1d
Senior AI-assisted DevOps Engineer
Improvado —Desde casa
- Tiempo completo
1d

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Principal AI Engineer (Platform team)
Improvado —Desde casa
Mentor and level up engineers on AI-assisted development practices — help them ship faster without introducing hidden risk. 20 PTO days + US holidays.
1d
Senior AI-assisted DevOps Engineer
Improvado —Desde casa
Detail-oriented and pedantic, with sharp attention to detail in high-volume, high-stakes systems — accountable and genuinely invested in the quality of your…
1d

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Principal AI Engineer (Platform team)

Improvado -
Desde casa

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Detalles del empleo

Tiempo completo
Hace 1 día

Descripción completa del empleo

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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