{"id":4285870,"url":"https://alion.io/job/focal-systems-platform-engineer-backend-infrastructure","title":"Platform Engineer (Backend Infrastructure)","company":{"id":173841,"name":"Focal Systems","domain":"focal.systems","url":"https://alion.io/company/focal-systems","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":88,"open_postings":10,"ghost_share":0,"stale_share":0.5,"repost_share":0,"time_to_fill_p50_days":22,"computed_at":"2026-11-12T10:38:37Z"}},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Poland"],"countries":["PL"],"hiring_countries":["PL"],"hiring_countries_total":1,"salary":{"min":102000,"max":117500,"currency":"USD","period":"year","gross":null,"usd_annual":117500},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"FastAPI","optional":false},{"name":"GCP","optional":false},{"name":"Grafana","optional":false},{"name":"Helm","optional":false},{"name":"KEDA","optional":false},{"name":"Kubernetes","optional":false},{"name":"Mimir","optional":false},{"name":"MySQL","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"Redis","optional":false},{"name":"Sentry","optional":false},{"name":"Terraform","optional":false},{"name":"CircleCI","optional":true},{"name":"Computer Vision","optional":true},{"name":"Go","optional":true},{"name":"Ray","optional":true},{"name":"Snowflake","optional":true}],"status":"live","first_seen_at":"2026-11-13T21:12:41Z","employer_posted_date":"2026-11-13","last_verified_at":"2026-11-13T21:49:13Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Position: Infrastructure Engineer\nLocation: Poland/Europe - Remote\nType: This can be structured as a B2B contract or Employment Contract with full benefits\nPoland B2B Annual Rate: $102,000 - $117,500 depending on experience + stock options\nPortugal Salary Band: €60,000 - €72,000 depending on experience + stock options\nWho We Are\nFocal Systems is the industry leader in retail AI solutions. We are a Silicon Valley-based startup headquartered in San Francisco, with operations in Canada, the UK, multiple EU countries and a tech hub in Poland. 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 some of the top retailers in the world, processing hundreds of millions of images per day across tens of thousands of stores globally.\nWe were recently named Confluent's inaugural Data Streaming Startup of the Year, a recognition of how seriously we take the engineering challenges at the core of our business.\nWe seek smart, creative, and passionate people who want to help build a great and enduring company.\nWhat We're Looking For\nWe are looking for a Platform Engineer to own the platform that every image from every store passes through: ingestion, Kafka streaming, Python services, GPU model inference, databases, storage, and the GCP and Kubernetes layer underneath. The team is small, so there is no separate SRE, DBA or release team. When a pipeline slows down, you find out whether the cause is a Kafka consumer, a MySQL query, an autoscaler or a node pool, and you fix it, including in the application code. The role is cloud-only, with no on-prem or datacenter hardware, and CI/CD pipelines are a small part of it.\nThe core challenge is scale. We are processing hundreds of millions of images per day across tens of thousands of retail locations globally, and that number is growing fast. Load will grow by an order of magnitude, and your job is to make sure cost and operational effort do not grow with it.\nWhat You Will Do\nOwn the design, operation and cost of Focal's production platform on GCP: Kubernetes, Kafka, MySQL, MongoDB, Redis, object storage.\nDrive measurable reductions in COGS and latency, for example lowering GPU inference cost per store through machine types, batching, autoscaling or scheduling, and report the numbers.\nRead, debug and change Python (FastAPI, Kafka consumers) backend services. Platform problems are often fixed in application code, for example a MySQL query that ran fine at 1,000 stores and times out at 10,000.\nFix throughput bottlenecks such as consumer lag at store opening, whether the cause is partition count, consumer throughput, a downstream database or autoscaling reaction time.\nRework metrics, alerts and dashboards so the on-call engineer can tell which stores and regions are affected when an alert fires. Take part in incident response, postmortems and capacity planning.\nBuild tooling that gives engineers access to data across regions and storage systems in minutes instead of days.\nMaintain infrastructure-as-code (Terraform, Helm) and the deployment path to production, and work with the backend, deep learning and edge teams so the platform keeps up with new products and models.\nWhat You Need to Be Successful\nMust have\nPython as a software engineer, not only for scripting. You will contribute to backend code every week.\n5+ years building and operating production backend systems on a cloud platform. GCP preferred; deep AWS or Azure experience is fine.\nHands-on production experience operating at least one stateful system under load: Kafka or another streaming platform, MySQL/PostgreSQL, or MongoDB. We mean partitioning, replication, lag, slow queries and failover, not only provisioning.\nKubernetes in production, including scheduling, resource limits, autoscaling with KEDA, GPU node pools and debugging misbehaving pods.\nDebugging production incidents across layers (application, messaging, database, orchestration, network), with examples you can walk us through.\nObservability with Prometheus, Grafana, Grafana Mimir and Sentry, or equivalent: instrumenting code, writing useful alerts.\nTerraform or another infrastructure-as-code tool.\nNice to have\nMySQL query tuning; Kafka internals (consumer group rebalancing, partition strategy, throughput tuning), Confluent Cloud and Kafka Connect.\nGPU workloads or ML inference serving in production (Ray/KubeRay or similar), and cloud cost optimization with measured results.\nGo, Snowflake, Airflow, CircleCI, Helm, and blue/green or canary releases.\nAbout you\nYou take ownership of problems end to end and follow them into whichever layer they lead.\nYou make decisions from data (profiles, metrics, query plans, cost reports) and prioritize well in startup/scaleup environments.\nAdvanced written and spoken English.\nComfortable coordinating across time zones with a global team.\nComfortable with a shared on-call rotation.\nWhy Focal Systems\n\nStrong Values and Mission - We are a tightly-knit team with an ambitious mission and a strong set of core values, which define our approach to business and have successfully guided us since inception.\nExceptional Team - We are a team of hard-working, fun-loving professionals from some of the most eminent universities, research labs, and tech companies of our time. We pride ourselves on recruiting exceptional individuals to help us redefine the state-of-the-art.\nOutstanding Partners - We work with some of the largest retailers in the world and have a world-class roster of investors, advisors and partners to support & advise us in our endeavors.\nWhat we offer \n We care deeply about the health, happiness, and wellbeing of all of our employees. We offer:\nCompetitive Salary & Attractive Stock\nPaid Time Off \nTeam Retreats \nEducation grants\nNote: 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. 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