Sr. AI-First Backend & Data Engineer (AI)

TL;DR

Sr. AI-First Backend & Data Engineer (AI): Design, build, and ship AI-integrated data systems and backend services that embed AI/ML capabilities into production decision-making layers. Focus on scalable data/ML pipelines, safe daily shipping with feature flags and rollback architecture, and end-to-end ownership across deployment, monitoring, cost, and business impact.

Location: Herzliya, IL

Company

hirify.global builds an AI-native predictive analytics platform that embeds ML and AI-driven insights into production GTM workflows.

What you will do

• Design, build, and own scalable data and ML pipelines, backend services, and AI-powered capabilities used in production runtime.
• Decompose complex work into safely mergeable increments and ship daily using feature flags, canary releases, and rollback architecture.
• Use AI-assisted development tooling (e.g., code generation and architecture prototyping) as a core workflow multiplier.
• Own outcomes end-to-end: deployment, operational monitoring, observability, cost efficiency, and business impact measurement.
• Make pragmatic architectural decisions balancing reliability, cost, and delivery speed; document decisions in lightweight ADRs.
• Collaborate with product, design, infrastructure, and GTM teams to translate customer and business needs into technical solutions.

Requirements

• 5+ years building and shipping production-grade backend and data systems in distributed cloud environments (AWS and/or GCP).
• Hands-on AI/ML integration in production workflows where AI/LLM/agent components are part of the production runtime.
• Active use of AI-assisted development tooling (e.g., Copilot, Cursor or equivalent) to increase engineering throughput.
• Strong backend expertise in Java (Spring Boot), Python, and/or Go, plus experience with relational and non-relational databases, data modeling, and query optimization.
• Expertise in automated testing, CI/CD, and observability.
• High-velocity, high-ownership mindset with a track record of delivering small incremental changes and maintaining strong delivery flow.

Nice to have

• Experience shipping ML-Ops powered systems in production (model serving, monitoring, retraining pipelines).
• Experience with distributed data technologies (e.g., Parquet, Athena, or similar query engines).
• Experience making and documenting architectural decisions autonomously (ADRs or equivalent).

Culture & Benefits

• Builder-first, high-ownership environment with a focus on shipping daily and iterating constantly.
• AI-native approach where AI components are treated as first-class runtime dependencies.
• Startup setting with exposure to diverse technologies and clients and real impact on product direction.
• Equal opportunity employer with commitment to accessibility and reasonable accommodations during the recruitment process.

Hiring process

• Interviews and evaluation of production engineering experience, AI/ML integration, and architectural decision-making.
• Discussion of how daily shipping, testing/CI/CD, and observability are applied in real systems.