Senior Platform Engineer

Zocks is an AI platform transforming how financial advisors work. Starting in the US financial services market, we're building technology that supports advisors across their entire workflow - from sales and meeting preparation to note-taking, follow-ups, scheduling, email, document intelligence, reporting, and integrations with the systems they use every day.

Our goal is to take repetitive, manual work out of the advisor-client relationship and turn conversations, documents, and data into actions automatically. As our platform expands across more workflows, customers, and use cases, we're solving increasingly complex challenges around AI, real-time systems, data, security, integrations, and scale.

Zocks is headquartered in San Francisco, while our entire R&D organization - Engineering, Product, Design, Data, and Infrastructure - is based in Budapest. This means our Budapest teams don't just execute on a product built elsewhere: they're directly responsible for shaping the product, technology, and how we build them as we grow.

More than 5,000 firms, including 6 of the 9 Barron’s Top Mega RIAs and 2 of the top 3 life insurance carriers, rely on Zocks, the #1 rated AI Assistant for Financial Services on G2.

Key challenges you will work on every day:

Design and evolve our cloud platform with scalability, reliability, security, and multi-region operation in mind
Own and improve Kubernetes environments, including cluster architecture, networking, workloads, scaling, reliability, and operational patterns
Improve the developer experience from local development through CI/CD to production
Design and optimize network topology for connectivity, latency, throughput, and resilience
Build and evolve observability that provides meaningful insights for engineering and operations rather than simply generating alerts
Support and improve infrastructure around stateful and distributed systems
Work closely with software engineers on infrastructure and architecture decisions instead of treating infrastructure as a separate operational layer
Explore and adopt AI-powered engineering tools where they can meaningfully improve platform engineering and operational workflows
Participate in a shared fair on-call rotation, with a focus on sustainable operations, low alert noise, automation, and continuous reliability improvements

Most of this applies to you:

Strong hands-on experience designing and operating production cloud infrastructure; AWS experience is preferred, but strong fundamentals from another major cloud environment can transfer well
Deep understanding of Kubernetes - not only deploying and operating workloads, but understanding the underlying concepts and mindset on running cloud-native applications
Strong Linux fundamentals
Strong understanding of networking, including private/public networking, DNS, load balancing, VPNs, firewalls, and cloud networking concepts
Experience designing and maintaining infrastructure as code, preferably with Terraform
Experience building and evolving software delivery platforms and CI/CD pipelines from pull request to production
Solid scripting or software engineering skills, preferably in Python or Go
Experience designing observability and monitoring for complex production systems
Understanding of distributed systems and the trade-offs involved in building highly available and resilient services
Hands-on experience using AI-powered development or infrastructure tooling as part of your everyday engineering workflow - maintaining and developing skills, plugins
Ability to reason about infrastructure beyond a specific cloud provider — storage, compute, networking, containers, databases, and distributed workloads rather than relying primarily on vendor-specific tooling

Nice to have:

Database administration experience, particularly with MySQL
Experience with durable execution/workflow technologies such as Temporal or similar systems
Experience with data-intensive platforms or previous exposure to data engineering
Experience operating multi-region infrastructure
Experience building internal developer platforms, self-service infrastructure, or platform abstractions used by multiple engineering teams

Requirements:

5+ years of relevant experience in Platform Engineering, Cloud Engineering, SRE, DevOps, or a closely related field
Strong English and Hungarian communication skills
Experience working in complex production environments and collaborating closely with software engineering teams
Comfortable taking ownership of ambiguous infrastructure problems and designing solutions rather than only implementing predefined ones
Experience working in a fast-moving product or startup environment is a strong advantage