Senior Software Engineer (AI Fluent)

 

Role summary  

Ramat Hasharon, Herzliya. 

Hybrid  
Full-time  

We are looking for an engineer who can take ownership of a solution from understanding the business problem through production delivery and continuous improvement. 

AI-assisted development tools are a core part of how you work. You use them daily, critically, and effectively to improve the quality and speed of software delivery. 

You will report to a Domain Architect and work closely with senior engineering, product, and business leaders on AI initiatives and other high-impact challenges. 

You will contribute across the full lifecycle: problem definition, solution design, implementation, evaluation, deployment, monitoring, and production support. 

 

What you’ll do  

• Own the full loop - understand the problem, define the solution, architect it, ship it, monitor it. No one hands you a spec 

• Build with AI as your primary tool - Claude Code, Cursor, whatever gives the most leverage; do in a day what used to take a team a week 

• Co-design with stakeholders and the business - decision logic, risk thresholds, success metrics 

• Build the evaluation harness before you ship - if you can’t measure it, it’s not done 

• Own production from day one - monitoring, alerting, observability; you’re on call for what you build 

• Raise the bar - in design reviews, in code, and in how the team works 

 

Who you are  

Engineering  

• At least 7 years of experience as a backend engineer 
  
  
• Experience shipping production AI systems - running them in the real world and fixing what breaks, not just building them 

• Understanding of agentic architectures - orchestration, multi-step workflows, fallback and error logic 

• Strong eval instincts - you define metrics, build test sets, and don’t ship until you can measure 

• Full-stack range - comfortable across the prompt, RAG pipeline, orchestrator, and backend 

• Comfortable across any stack - you go where the right solution is 

• Honest communication - you flag problems early and give direct, candid feedback 

• You understand production concerns such as reliability, maintainability, security, observability, latency, and cost. 

AI fluency  

• Real fluency with AI coding tools - genuinely fast, not just "familiar with" 

• Think in workflows, not endpoints - agentic loops, skills, and orchestrated flows; CRUD with an LLM bolted on isn’t a system 

• Clear judgment about when to trust AI output and when to rewrite it 

• Goes beyond using AI - builds skills, workflows, and harnesses, not just prompts 

• You understand common AI-system risks such as hallucinations, prompt injection, data leakage, unreliable tool execution, and uncontrolled autonomy. 

Good to have  

• Fintech or regulated-environment experience - understanding why "probably fine" isn’t acceptable when money is moving 

 

What could set you apart  

• Builder’s itch. When you see a repetitive task or a problem the team has accepted as "too hard to fix," you come back with a working prototype. Watching people do manually what a system could do doesn’t sit right with you. 

• Grounded confidence. You move forward with incomplete information, make a call, own it. When you’re wrong, you update and move on - no drama, no ego. 

• Production instinct. When you design, you’re already thinking about 2am incidents, runaway inference costs, and edge cases that surface when real money is moving. "Probably fine" isn’t a risk posture. 

• Curious and adaptive. You explore new models and tools before anyone tells you to, run the experiment, and help create the best practices that don’t exist yet. 

 

Why join us 

• Real problems at scale - 25M+ customers in 190+ countries depend on these systems; the stakes are real 

• You help define the methodology - early-stage work at Payoneer; you won’t inherit a playbook, you’ll write it 

• Work directly with senior architects, engineers, product leaders, and business stakeholders. 

• Build solutions for challenging real-world problems where reliability, security, and measurable outcomes matter. 

 

#LI-LF1