Databricks Senior Solutions Architect _ GenAI focus at Hiflylabs

Budapest, Central Hungary, Hungary -

Full Time

Start Date

Immediate

Expiry Date

09 Jun, 26

Salary

0.0

Posted On

11 Mar, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Databricks, Generative AI, Data Engineering, Spark, Python, Scala, RAG Pipelines, Agents, Text-to-SQL, MLOps, LLMOps, CI/CD, LangChain, DSPy, HuggingFace, MLflow

Industry

IT Services and IT Consulting

Description

Company Description Hiflylabs is a Budapest-based company. We have 250+ employees at this moment and we are constantly thriving. Our application development team and business intelligence experts work to provide effective solutions to business problems. Our professional team has proved its expertise through 10 years of experience, participating in multiple Business Intelligence projects - both Hungarian and international - in various industries, such as the financial, telecommunication and energy sectors. We deliver a wide portfolio of innovative business solutions that include Data Warehouses, Business Intelligence, Data Analytics. In the last few years we have acquired a high level of competence in Application Development. Hiflylabs is committed to innovation, and encourages the realization of innovative initiatives in the form of independent startups. Get an insight on how we work and check out our Website, LinkedIn page and YouTube channel! Job Description About the Job/What will you do? As a Senior Solution Architect with GenAI focus, you are the dedicated technical engine for our most strategic Fortune 500 partners. You will bridge the gap between "cool AI demos" and production-grade GenAI systems. This is a hands-on role for a heavy-hitting Data Engineer who lives at the intersection of Big Data and Generative AI. Main Tasks Architect & Build: Lead the end-to-end implementation of data pipelines and GenAI applications (RAG, Agents, Text-to-SQL) on Databricks. Operationalize (MLOps/LLMops): Design and maintain the "plumbing" - CI/CD, model serving, monitoring, and evaluation frameworks to ensure AI stays reliable in production. Optimize Performance: Tune complex Spark jobs and LLM inference patterns for maximum efficiency and minimum latency. Strategic Advisory: Act as the long-term technical partner for clients, translating business hurdles into scalable code and architecture. Qualifications Requirements The Data Engineering Core Spark Mastery: Deep, hands-on experience with Apache Spark (Python/Scala) and the Databricks Lakehouse architecture. Performance Engineering: You don't just write code; you tune queries, debug complex distributed systems, and optimize for scale. Certification: Databricks Certified Data Engineer Professional (or equivalent proven experience). GenAI & LLM Implementation Applied GenAI: Proven experience building RAG pipelines, agentic workflows, and tool-calling LLMs using LangChain, DSPy, or HuggingFace. Model Lifecycle: Deep understanding of prompt engineering, fine-tuning strategies, and model evaluation metrics. The "Ops" Specialist MLOps & LLMops: Hands-on experience with MLflow, model serving, and automating the deployment/monitoring of AI applications. Engineering Best Practices: Strong grip on CI/CD, unit testing for AI, and infrastructure-as-code. Additional Information Why us? Diverse projects - In each assignment, there is always something new, either on the technical or the business side, that helps you grow. Empowerment - Trust is a cornerstone of our culture. We'll hold your hand if you need it, but give you space if you’d like to push your limits. Don't lose sight of the goal, the rest is up to you. Flexible ways of working – We love our location on Bartók Béla RoadStreet which is not only an office but also a community space. However, we respect our people to do their work when and how they work best. Balanced life - We love what we do and aim to work together with others who do their work with love. At the same time, we highly value fresh minds, for which we think a healthy work/life balance is essential! Forget about pointless meetings and unnecessary administration. Mentoring from your first day – Continuous support is not just a set of fancy words we throw around here; your mentor follows you throughout your career path. Learning & Development opportunities - If you want to keep learning and improving, we are on to a great track! We look forward to helping you unlock your potential. Supportive corporate culture - In addition to our professional success, we are proud of the social cohesion that is based on comradery, mutual support, and respect and is constantly nurtured in the company. Tag: DATABRICKS

Responsibilities

The role involves leading the end-to-end implementation of data pipelines and Generative AI applications like RAG, Agents, and Text-to-SQL on Databricks. Responsibilities also include operationalizing these systems through MLOps/LLMOps, optimizing performance of Spark jobs and LLM inference, and acting as a long-term technical advisor for clients.