Software Development Engineer - Golang

🏢 Avalara · all Avalara jobs (6)
📍 Remote · Brazil
💰 R$319,300 - R$574,900 / year
📅 Posted 2026-09-03 · via RemoteIO
🏷 Golang,AI,Distributed Systems,Cloud-native,CI/CD
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What You'll Do
Avalara operates at global scale, processing millions of tax transactions across thousands of customers in an increasingly complex regulatory environment. To sustain that growth, we must continuously accelerate the reliability, intelligence, and delivery velocity of our core engineering systems — while raising the engineering bar across every team that builds and operates them. This role exists because the pace and complexity of what we need to build demands engineers who raise the bar: people who strengthen systems, elevate teams, and take full ownership of outcomes — not just tasks.
A Senior Software Engineer in this role owns high-impact work at the intersection of distributed systems reliability, AI-enabled product delivery, and engineering excellence across a global organization. This role elevates Avalara in three ways. For the team, you improve the performance of engineers around you through technical leadership, disciplined code review, mentoring, and a relentless commitment to quality — leaving every system, process, and team stronger than you found it. For the business, you accelerate delivery of reliable, scalable platform capabilities that support Avalara's global research infrastructure, eliminating production risk through proactive design and reducing toil through automation. For customers, you build and ship AI-enabled capabilities that improve automation, data accuracy, and measurable compliance outcomes.
Success in this role is measured by impact, not activity. Within 12 months, you will have delivered a meaningful system reliability improvement — measurable through reduced incident rates, improved SLA adherence, or lower mean time to recovery — and driven at least one AI-enabled product capability that reaches production and generates quantifiable business or customer value. You will have raised the technical capability of peers through mentoring and design leadership, driven at least one significant CI/CD or operational improvement, and established yourself as a trusted architectural voice whose decisions are grounded in data and sound tradeoff reasoning. At Avalara, we hire only Bar Raisers — individuals who improve talent density, execution quality, and business outcomes by their presence. This role is no exception. This position is also open to people with disabilities (PcD), in accordance with Law No. 8.213/91 (Esta vaga também é destinada a pessoas com deficiência (PcD), conforme Lei nº 8.213/91).
What Your Responsibilities Will Be
- Own the reliability, observability, and performance of scalable distributed systems within Avalara's global research platform — proactively reducing production incidents and strengthening system resilience through architectural discipline, not reactive fixes.
- Drive engineering velocity and quality by integrating AI to accelerate how work gets done — including code generation, test automation, system design, debugging, and documentation — with demonstrable, measurable impact on speed and output quality.
- Design and deliver AI-enabled product capabilities that improve automation, data processing efficiency, and customer outcomes, translating applied AI into business value with quantifiable results.
- Lead architectural and technical design decisions for complex distributed systems, balancing scalability, cost, reliability, and long-term maintainability — communicating tradeoffs clearly and driving alignment across teams.

Bar Raiser Expectations
This role is expected to be an AI Bar Raiser, integrating advanced AI capability to meaningfully improve how distributed systems are designed, built, and operated, while elevating the team's ability to use AI to drive measurable engineering and business outcomes. The successful candidate will:
- Embed AI into engineering workflows to accelerate speed and quality, including code generation, automated testing, debugging, and documentation.
- Drive measurable engineering impact using AI, such as reducing inciden

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