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The client is an innovative technology company focused on AI-engineered software products. They operate within a disciplined, metrics-driven engineering environment that prioritizes predictable delivery, strong technical governance, and high execution quality. Their ecosystem utilizes modern AI-augmented delivery models,such as agentic coding workflows to drive product success and scale software solutions reliably.
We are looking for a Bazel Engineer (Senior) to join a core Bazel team delivering a mix of consultancy, migration work, and open-source contributions. Team members work on short- to medium-length projects around Bazel, with the potential to become founding members of longer-lived teams over time.
This is a senior-level, highly autonomous role within an elite engineering squad of 10 Bazel experts working across various short and mid-term projects.
We are looking for a Sys Admin + Python Infrastructure Engineer to lead key infrastructure delivery centered on graph database environments (Neo4j/GraphDB). The role combines high-level systems engineering and infrastructure automation with proactive security hardening and system architecture optimization.
This is an advanced/senior-level, highly autonomous role. The engineer will collaborate independently with technical stakeholders, drive solutions end-to-end, and own delivery outcomes. No specific reporting line or time zone overlap requirement was specified beyond advanced English proficiency for technical communication.
Our client is a European software engineering and consulting company specializing in developer tooling. The team builds advanced tooling for developers as end-users, with a focus on IntelliJ plugins, IDEs, coding agents, and frameworks for local AI inference. The technical environment is Kotlin/Java-centric, with an engineering culture built around ownership, pragmatism, and transparency.
The team is aiming to harden the overall security posture across a multi-entity group structure and build robust operational capabilities to detect, respond to, and recover from security events. The Security Engineer will be responsible for supporting security operations within a modern security stack, streamlining integration capabilities across newly acquired entities, managing endpoint and identity protection, and optimizing SIEM/SOAR platforms.
As an ML Engineer, you will focus on enabling the rapid exploration, productionization, and deployment of machine learning models and optimization algorithms. The goal is to deliver end-to-end ML lifecycles and robust APIs that solve complex pricing class problems across multiple business domains within a hybrid-cloud ecosystem.
The main objective of this role is to productionize and scale an ML-driven data quality system across the organization. The team aims to build and optimize anomaly-detection and clustering pipelines, leveraging both classic machine learning and LLM reasoning to flag, explain, and resolve root-cause data issues. You will be responsible for creating and maintaining validator models that turn detected anomalies into higher-quality future data.
This position is responsible for designing, building, and maintaining the AI systems: the LangGraph agents, retrieval-augmented generation (RAG), multi-provider LLM orchestration, and prompt/evaluation machinery that turn customer conversations and uploaded documents into grounded, auditable cost estimates. Good leadership skills and the ability to work in US time zones as required are both prerequisites.
Our client is a growing software engineering group fostering a culture rooted in strong engineering practices, ownership, and transparency. The organization operates at the intersection of technology, implementation, and client collaboration, working across the full software development lifecycle (SDLC) with clients and engineering teams alike.
Our client is a European software engineering and consulting company building and enhancing IDEs and core plugins within a major IDE platform ecosystem, powering widely used developer tools (e.g., PyCharm-style, GoLand-style, PHPStorm-style, RubyMine-style tooling). The work involves implementing advanced language/technology support (e.g., PHP, Ruby, Scala, Bazel, Kotlin) through deep integration with their respective ecosystems, with the goal of delivering stable, high-quality tools used by developers worldwide.