Senior Customer Integration Engineer

Our Customer Integration team has taken every major retailer we've signed through production — and as we add more customers, we’re looking for a senior engineer to lead high-quality deployments, own onboarding and integrations end-to-end, and help define how this function grows.

What We're Looking For

• Ownership. When a customer has a problem, you don't wait for it to get assigned.You’ll pick it up, see it through end-to-end,, and close the loop.
• 4+ years of hybrid experience . You’ve written real production code and worked directly with external stakeholders. That could be integration or solutions engineering, a consultancy role with direct client work, freelancing on real production systems, or a technical role at a startup where you wore multiple hats. What matters is that you've shipped code and been accountable to someone outside the engineering org.
• Strong Python. Pandas and NumPy are second nature. You default to an API-first mindset — designing clean contracts, composable interfaces, and avoiding one-off scripts that don’t scale..
• Systems thinking. You can hold a complex distributed system in your head, decompose a messy customer problem into its parts, and come back with a solution — often one nobody else saw because they were closest to it.
• Solid SQL and data work. Diagnostic queries, tracing data inconsistencies, building ETL and transformation pipelines, following data across systems. You reach for SQL before you reach for a ticket.
• Working knowledge of distributed systems. Kafka, async pipelines, caching layers. You don't need to design them. You need to understand how they behave and figure out why data stopped flowing through them.
• Clear technical communication. You can explain a root cause to a non-technical customer or stakeholder without jargon, and explain a customer's actual problem to an engineer without losing the detail.

Nice to Have

• GCP, Kubernetes, or Helm experience (reading configs and logs, not managing infrastructure)

Focal Systems is the industry leader in retail AI solutions. We are a Silicon Valley based startup that has more than doubled in size every year since inception. We are a Deep Learning first company. Our mission is to automate and optimize brick and mortar retail using deep learning computer vision. Focal Systems has been deployed at scale with the top retailers in the world. We are looking for smart, creative and passionate people who want to help build a great and enduring company and deploy Deep Learning to the world!

We have a strong team of engineers located in Poland.

What We Offer

We care deeply about the health, happiness, and wellbeing of all of our employees. We offer:

• Your work is visible to customers and leadership. Make a real impact, get real credit for what you do.
• Competitive salary and equity.
• A small but dedicated team where decisions are fast and ownership is genuine.
• Flexible remote work with a growing team in Poland and the UK.
• Opportunity to travel to customer sites across the UK and Europe - but only if you’re willing to!

**Our pay bands are driven by market benchmarks in the target geography for hiring. Our posted ranges typically include multiple job levels. A candidate's level is determined by their performance throughout our talent acquisition process including technical screens, behavior interviews, presentations, work samples, and references. We will communicate transparently with the candidate at final stages regarding how we have leveled them, and what salary range that places them into. Placement within range is equally determined by education, general experience in your profession, specific experience in our domain, and your performance in the talent acquisition process. It is rare to receive an offer at the top of the range for a role.

,[Work with a real distributed AI system at scale — when a retailer's report is wrong, a pipeline is silently dropping events, task counts diverged somewhere between Kafka, Redis, MySQL, and MongoDB, you'll own the challenged end-to-end, not hand it off after one layer., Bring new customers live — map their data formats to ours and validate pipelines held up at 10 stores before scaling up to 100 and then a 1000., Manage live production configuration for dozens of active deployments — granular store configurations, feature flags and so on — where a single mistake can impact shelf monitoring across thousands of stores and be presented in a retailer's morning report., Build tooling that removes the manual work — identify the patterns and build the systems that make the next deployment faster than the last one., Work directly with customers when something goes wrong — explain what happened, own the fix, and close the loop.] Requirements: Python, Flask, Git, Degree, Data engineering, MySQL, MongoDB, SQL, ETL, CSV, JSON, XML, Data modeling, Kafka, Redis, BigQuery, Snowflake, dbt Tools: Jira, Confluence, GitHub, GIT, Agile, Scrum. Additionally: Training budget, Small teams, International projects, Flat structure, Startup atmosphere, No dress code, In-house hack days.