Tel Aviv, Israel · Onsite · Full-time

Seller Snap is a SaaS platform that helps Amazon sellers price smarter, protect their margins and grow through algorithmic repricing and data. Our algorithm makes pricing decisions for sellers around the clock, so reliability isn't optional. It's the product.

We're looking for a hands-on Head of R&D to lead all of engineering, including DevOps and FinOps. You'll report to the CEO.

This is a leadership role first. You'll set the operating rhythm, own reliability, and build a team where everyone knows what they're doing, why, and by when, and where people feel coached and engaged. It's also a deeply technical role. You'll still write production code, understand our infrastructure end to end, and be able to go deep on our pricing algorithm with the people who build it.

You'll also be the evangelist for AI-native engineering at Seller Snap: making AI a default part of how the team builds, while putting the systems and guardrails in place that keep it safe.

• Own production reliability, including observability, alerting, & incident management.
• Build R&D's daily, weekly and monthly operating rhythm, with clear ownership, sensible delegation and reporting that leadership can rely on.
• Lead multiple engineering teams, coaching and giving clear direction so people know what they're doing and when, and stay engaged.
• Shape the R&D organisation: structure, roles, ways of working, and the right mix of in-house and outsourced talent.
• Turn priorities into realistic plans with Product, deliver predictably, and work well across functions.
• Raise the bar on code review, testing, security testing and release practices.
• Lead adoption of AI-assisted development across R&D, finding the right balance between automation and human checks, with guardrails around what AI can and can't touch.
• Be the technical authority on architecture, infrastructure and data systems, and write code when it matters.
• Own cloud spend and keep infrastructure efficient as we scale.

• Experience owning an entire SaaS platform end to end, not a single product, feature or tool: architecture, infrastructure, data, and how it all runs in production.
• Demonstrated experience managing engineers and leading multiple engineering teams.
• A strong hands-on backend background, ideally in Python, building data-heavy production systems. You still enjoy writing code and can review anyone's PR with credibility.
• Deep, production-level AWS experience, with a strong grasp of cost and reliability trade-offs.
• Experience running Kubernetes in production and owning the infrastructure-as-code (CDK, Terraform or similar) and CI/CD pipelines behind it.
• Hands-on experience with most of EKS/ECS, Lambda, SQS/SNS, Kinesis, RDS, S3 and IAM.
• PostgreSQL at scale: performance tuning, sharding, and replication.
• Real experience running AI-assisted engineering in a team, not just using it yourself, with a clear view of where it helps and where it needs guardrails.
• Experience putting in place the processes that make teams accountable and predictable without slowing them down.
• Clear, direct communicator. Fluent English, written and spoken.

• Production experience with Go.
• Experience with a columnar or OLAP store such as ClickHouse, Redshift, BigQuery or Snowflake.