Senior Software Engineer Job at Cloudera (Budapest)

Senior Software Engineer

Cloudera

Location:
Hungary , Budapest ▼
Szeged

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

At Cloudera, we empower people to transform complex data into clear and actionable insights. With as much data under management as the hyperscalers, we're the preferred data partner for the top companies in almost every industry. Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world’s largest enterprises. Ready to take cloud innovation to the next level? Join Cloudera’s Anywhere Cloud team and help deliver a true “build your own pipeline, bring your own engine” experience. Enabling data and AI workloads to run anywhere, without friction or vendor lock-in. We take the best of the public cloud- cost efficiency, scalability, elasticity, and agility and extend it to wherever data lives: public clouds, private data centers, and even the edge. Powered by Kubernetes, our hybrid architecture separates compute and storage, giving customers maximum flexibility and optimized infrastructure usage. As a Senior Software Engineer, you will lead the architecture and delivery of AI-powered workflows that are integral to our product. You will define the technical strategy, set quality and reliability standards, and deliver end-to-end systems that transform ambiguous customer needs into robust, measurable, and privacy-safe AI experiences.

Job Responsibility:

Own the architecture: Design, evolve, and document the end-to-end AI workflow stack (prompting, retrieval, tools/function-calling, agents, orchestration, evaluation, observability, and safety) with clear interfaces, SLAs, and versioning
Ship production systems: Build reliable, low-latency services that integrate foundation models (hosted and self-hosted), and traditional micro services
Own end-to-end delivery of features from the user-facing aspect (UI) to the backend services
Implement robust testing frameworks, including unit, regression, and end-to-end tests, to guarantee deterministic and predictable behavior from our AI-powered data platform. Establish safety guardrails and human-in-the-loop processes to maintain accuracy and ensure the production of ethical, responsible, and non-toxic outputs
Optimize for cost & performance: Instrument, analyze, and optimize unit economics (token usage, caching, batching, distillation) and performance (p95 latency, throughput, autoscaling)
Drive data excellence: Shape data contracts, feedback loops, labeling strategies, and feature stores to continuously improve model and workflow quality
Mentor and multiply: Provide technical leadership across teams, unblock complex projects, raise code/design standards, and mentor junior engineers
Partner across functions: Translate product intent into technical plans, influence roadmaps with data-driven insights, and communicate trade-offs to executives and stakeholders

Requirements:

4+ years of software engineering experience building large-scale distributed systems
Expertise in at least one primary language: Rust, Go, or Java
Cloud-native architectures (containers, service mesh, queues, eventing, micro services, Kubernetes)
Platform thinking: Experience designing reusable AI workflow primitives, SDKs, or internal platforms used by multiple product teams
Familiarity with the AI/ML ecosystem: You understand the fundamentals of LLMs, vector databases, RAG, and prompt engineering
Security & privacy mindset: Familiarity with data governance, PII handling, tenant isolation, and compliance considerations

Nice to have:

Ability to drive UI frontend decisions and development using React or any other frontend frameworks
Basic understanding of Big Data Technologies (Spark, Ray)
Model ops: Experience with model lifecycle management, feature/embedding stores, prompt/version management, and offline/online eval systems
Search & data infra: Experience with vector databases (e.g., Pinecone, Weaviate, pgvector), retrieval strategies, and indexing pipelines
Observability: Built robust tracing/metrics/logging for AI systems
familiarity with quality dashboards and prompt diff tooling
Proven experience in integrating AI/ML models into user interfaces
Familiarity with tools such as MLflow, LangChain, or Hugging Face

What we offer:

Generous PTO Policy
Support work life balance with Unplugged Days
Flexible WFH Policy
Mental & Physical Wellness programs
Phone and Internet Reimbursement program
Access to Continued Career Development
Comprehensive Benefits and Competitive Packages
Paid Volunteer Time
Employee Resource Groups

Additional Information:

Job Posted:
January 24, 2026

Employment Type:

Fulltime

Work Type:

Hybrid work

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