job specification

OPEN TO ALL CANDIDATES ACROSS LATIN AMERICA

Title: Senior Backend Engineer (Golang) – Data Infrastructure & Recommendations

Company: Fulcrum SaaS

Location: Remote – Latin America (strong overlap with Americas time zones required)

Type: Full-time

Level:  Senior / Staff

Compensation:  USD 70,000–100,000 per year, depending on experience and location

About Fulcrum SaaS

Fulcrum SaaS is a conversion rate optimization (CRO) platform that powers product recommendations for ecommerce brands. Our infrastructure processes high-volume behavioral events, feeds real-time recommendation algorithms, and serves personalized experiences at scale. We operate in a multi-tenant SaaS environment where data correctness, low latency, and system reliability are non-negotiable.

Our stack includes Go, Bigtable, BigQuery, Pub/Sub, and a dual-store architecture (operational + analytical) that we designed from scratch.

The Role

We are looking for a senior backend engineer who has built and operated production data systems under real load—not prototypes, not internal tools. This is a core infrastructure role at the intersection of our operational and analytical data layers.

You will own the systems that move behavioral event data from ingestion through transformation into our recommendation engine. You will design for correctness, build for observability, and make architectural tradeoffs with the pragmatism that only comes from production scars.

You will be an early engineering hire with real influence over our technical direction.

What You’ll Do

• Design and operate high-throughput event ingestion pipelines capable of processing millions of events per day with low-latency serving requirements.
• Own the dual-store architecture that separates our operational (real-time) and analytical (batch) data layers, including streaming vs. batch pipeline design and failure recovery.
• Build and maintain data movement infrastructure between stores (Bigtable/BigQuery or comparable), ensuring consistency, at-least-once delivery, and graceful degradation.
• Instrument production systems: define SLOs, implement distributed tracing, and build alerting that distinguishes signal from noise.
• Partner with the recommendation team to evolve our scoring, waterfall, and ranking infrastructure.
• Drive architectural decisions on data modeling, schema evolution, and multi-tenant isolation.
• Participate in an on-call rotation and own incidents end-to-end—from detection through root cause analysis to postmortem.

What We’re Looking For (Must-Haves)

• 5–10+ years of hands-on backend engineering in production environments (more is better).
• Track record of building and operating high-performance, high-throughput, low-latency systems at scale—not just prototypes.
• Deep working knowledge of Go’s concurrency model (goroutines, channels, context, sync primitives)—beyond syntax familiarity.
• Experience with columnar or wide-column stores: Bigtable/BigQuery strongly preferred; Cassandra, DynamoDB, Redshift, or Snowflake are comparable.
• Hands-on experience moving data between operational and analytical stores—you have solved streaming vs. batch tradeoffs, handled delivery guarantees, and recovered from pipeline failures.
• Experience with production observability: metrics, tracing, alerting, dashboards—you know what good instrumentation looks like.
• Multi-tenant SaaS experience—you understand isolation, scaling, and noisy-neighbor challenges when serving multiple customers on shared infrastructure.
• Batch pipeline design experience—you know when batch is the right tool and how to make it reliable.
• Dual-store architecture experience—you have operated systems where the operational and analytical data layers are intentionally separate.
• Comfortable working daily in English with a US-based team (meetings, async communication, code reviews, and technical documentation).

Strong Nice-to-Haves

• Identity resolution and cross-device stitching (probabilistic or deterministic).
• A/B testing infrastructure built for statistical rigor—not just feature flags, but impression tracking, experiment analysis, and statistical significance frameworks.
• Recommendation systems experience: scoring heuristics, waterfall algorithms, collaborative filtering, or hybrid approaches.
• Ecommerce domain knowledge: attribution models, conversion tracking, order/cart data models, session stitching.

What We Offer

• Compensation in the range of USD 70,000–100,000 per year, depending on experience and location, benchmarked to senior remote engineering roles in LATAM.
• Remote-first culture with async-friendly practices.
• Direct access to leadership; your architectural opinions will be heard and implemented.
• A team that treats production reliability as a first-class engineering concern.

How to Apply

Please apply through LinkedIn with your CV (English) and a brief note highlighting:

• Your experience with Go in production.
• The most demanding data/throughput system you have owned.
• Your country of residence and preferred start date.

You can also include links to GitHub, technical blogs, or talks if available.