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We are growing and are looking for a Senior Data Platform Engineer
who value personal and career growth, team-work, and winning!
What your day will look like:
Design, plan, and build all aspects of the platforms data, machine learning (ML) pipelines, and infrastructure.
Build and optimize an AWS-based Data Lake using best practices in cloud architecture, data partitioning, metadata management, and security to support enterprise-scale data operations.
Collaborate with engineers, data analysts, data scientists, and other stakeholders to understand data needs.
Solve challenging data integration problems, utilizing optimal ETL/ELT patterns, frameworks, query techniques, and sourcing from structured and unstructured data sources.
Lead end-to-end data projects from infrastructure design to production monitoring.

We are building cutting-edge data solutions, primarily on BigQuery, Databricks and Snowflake and for large scale customers.
Our solutions introduce next level automations and aim for low-code/no-code platforms that allows our customers to deliver fast while we hide all the engineering complexity behind.
If you are not afraid of any engineering task, likes to build cool stuff and enjoy when customers use your craft you belong with us.

we are seeking an innovative and experienced Senior Software Developer to join our team. This team is pioneering a new wave of application security solutions focused on identifying risks in AI-powered software. If you're passionate about software security, skilled in backend engineering, and intrigued by the intersection of AI/LLMs and security, we want you on our team.
The product scans application source code to detect embedded AI/ML models, libraries and framework, understand their behavior, and surface potential security risks; from data leakage to prompt injection vulnerabilities. This is a high-impact role that blends backend engineering with cutting-edge AI applications, helping organizations secure the next generation of software.
You're invited to meet the R&D team here!
**Work in a hybrid model: Two days from the office, three days from home**
Responsibilities:
Design and implement backend systems that scan source code, identify AI/ML components, and evaluate associated security risks.
Build intelligent detection logic to recognize large language models (LLMs), machine learning models, and custom pipelines in codebases.
Collaborate with security researchers, data scientists, and product managers to integrate AI risk models into our core platform.
Develop scalable and maintainable services in Java and Go.
Translate research prototypes into production-grade features, with attention to performance, resilience, and accuracy.
Conduct code reviews, maintain high development standards, and mentor team members.

We are seeking a highly motivated and skilled Release Engineer to join our AIOps group.

In this role, you'll play a critical part in bridging the gap between development and operations, ensuring the seamless qualification, deployment, and monitoring of our AI algorithms and infrastructure, and be responsible for the end-to-end operationalization of our core technology.

A day in the life and how youll make an impact:
Manage the end-to-end release process of machine learning algorithms and infrastructure components, from qualification through deployment.
Validate and test new algorithm releases to ensure they meet performance, stability, and compliance standards.
Create and execute deployment plans across various environments (staging, production), ensuring minimal risk and downtime.
Collaborate closely with AI researchers, MLOps, and software engineers to understand release requirements, share feedback, and resolve pre-release issues.
Identify and drive automation opportunities within the release pipeline to improve efficiency, reliability, and traceability.
Oversee updates to infrastructure components, ensuring compatibility and performance across systems.
Monitor deployments, proactively identify issues related to model behavior or infrastructure anomalies, and drive resolution with relevant teams.
Maintain clear and accurate release documentation, including version history, deployment notes, and incident reports.