Role Description Design, build, and operate a sovereign AI toolchain used in isolated or tightly controlled environments, including model serving, retrieval, orchestration, observability, and secure platform operations for enterprise AI engineering workloads. This role centers on open-source or open-weight LLM stacks, air-gapped or isolated deployment models, Kubernetes-based platform engineering, GPU-enabled environments, and auditable AI operations suitable for sovereignty-sensitive programs. Key responsibilities - Design and run Kubernetes environments optimized for AI inference, retrieval, experimentation, and agent execution in secure or isolated settings. - Deploy and operate open-source or open-weight model stacks, model gateways, vector databases, and supporting platform components. - Build reproducible platform automation using Infrastructure as Code and GitOps approaches for stable, auditable delivery. - Manage local registries, package mirrors, secrets, access controls, storage, networking, and observability in environments with limited or no public cloud dependency. - Optimize GPU, compute, and storage usage for reliable AI workloads while maintaining security and data sovereignty requirements. Examples of market tools, models, and platform components expected: - Inference and local serving stacks such as vLLM, Ollama, llama.cpp, or OpenAI-compatible self-hosted endpoints. - Open-source or open-weight models appropriate for sovereign deployment, for example coding-capable and general-purpose families hosted internally through approved serving layers. - Platform tooling such as Kubernetes, Helm, Terraform, Ansible, ArgoCD, private registries, Qdrant or similar vector stores, and Open WebUI or comparable internal interfaces. - Developer-facing integration options such as VS Code-compatible extensions, Continue-style local model connectors, or editor integrations pointed at internal APIs instead of external SaaS endpoints. - Hardware awareness covering GPU-backed nodes, CPU-only fallback options, storage performance, network isolation, and on-prem or dedicated infrastructure patterns. Qualifications - 5+ years in platform engineering, DevOps, SRE, or MLOps, with strong Kubernetes and Linux expertise. - Proven experience with AI infrastructure, model serving, private or on-prem deployments, and production operations for LLM-based workloads. - Strong hands-on skills in Python plus automation tooling such as Terraform, Ansible, Helm, and GitOps workflows. - Good understanding of networking, storage, access control, monitoring, and operational hardening in high-security environments. - Comfortable working in sovereignty-driven environments where auditability, isolation, and controlled data handling are mandatory. Additional Information - You will be working in the European Union to meet our customers' data security and privacy requirements. - Please be informed that our remote working possibility is only available within Hungary due to European taxation regulation. Company Description As Hungary’s most attractive employer in 2025 (according to Randstad’s representative survey), Deutsche Telekom IT Solutions is a subsidiary of the Deutsche Telekom Group. The company provides a wide portfolio of IT and telecommunications services with more than 5300 employees. We have hundreds of large customers, corporations in Germany and in other European countries. DT-ITS received the Best in Educational Cooperation award from HIPA in 2019, acknowledged as the Most Ethical Multinational Company in 2019. The company continuously develops its four sites in Budapest, Debrecen, Pécs and Szeged and is looking for skilled IT professionals to join its team.

Title: Lead Instructor: MLOps / AI Platform Engineering Location: United States Job Description: U.S. Remote, Business UnitGeneral Assembly DepartmentInstruction (Full Time) Since 2011, General Assembly has transformed tens of thousands of careers through pioneering, experiential education in today’s most in-demand skills. As featured in The Economist, Wired, and The New York Times, GA offers training in web development, data, design, business, and more, both online and at campuses around the world. Our global professional community boasts 60,000 full- and part-time alumni — and counting. In addition to fostering career growth for individuals, GA helps employers cultivate top tech talent and spur innovation by transforming their teams through strategic learning. More than 21,000 employees at elite companies worldwide have honed their digital fluency with our upskilling and reskilling initiatives. GA has also been recognized as one of Deloitte’s Technology Fast 500, and Fast Company has dubbed us leaders in World-Changing Ideas as well as the #1 Most Innovative Company in Education. GA is at the leading edge of creating practical solutions to one of the most pressing challenges of our time - the future of work. As recognized by The World Economic Forum, BCG, the OECD and more, these are big challenges to which only a few companies are offering real solutions. In this role, you'll be speaking every day to corporate leaders who rely on GA to help them apply these solutions to their workforce of the future. Job Title: Lead Instructor: MLOps / AI Platform Engineering Company: General Assembly Client: Confidential – Customer Success Reskilling Location: Remote (Must work West Coast / Pacific Time hours) Duration: 2 Weeks (Starting Mid-June) Commitment: Roughly 30 hours per week Compensation: $11,500 - $15,500 (Estimated lump sum payment for one 60-hour program) About the Engagement General Assembly is delivering a specialized reskilling program designed to transition Customer Success and Account Management professionals into MLOps and AI Platform Engineering roles. As the Lead Instructor, you will be the face of lessons. You aren't just checking the math; you are bridge-building. You will lead experienced customer-facing professionals through the complexities of taking AI systems from pilot to production, ensuring they leave the 2-week intensive with a functional understanding of MLOps governance and deployment. What You’ll Do - Lead Live Instruction: Deliver high-energy, synchronous remote lectures and "prompt-along" sessions covering ML pipelines, model deployment, and monitoring. - Simplify the Complex: Translate high-level MLOps concepts (CI/CD for ML, governance frameworks) into digestible insights for learners who are experienced professionals but not career engineers. - Facilitate Hands-on Labs: Guide students through self-paced exercises and live troubleshooting within the Azure AI Foundry and ML environments. - Mentor & Office Hours: Provide real-time feedback during dedicated lab hours, helping students navigate technical roadblocks in Python and Azure infrastructure. - Drive Learning Outcomes: Ensure students can successfully articulate and execute model lifecycle management strategies by the end of the cohort. What You Bring - The Experience: 7+ years in software or data engineering, with at least 3+ years specifically in MLOps or ML platform roles in a production environment. - The "Teacher" Gene: Proven experience in technical instruction, bootcamp delivery, or corporate training. You should be comfortable "reading the room" in a virtual setting. - Azure Fluency: Deep, hands-on expertise with Azure ML and AI Foundry. You should be able to navigate these platforms in your sleep. - Technical Foundation: Proficiency in Python, Data Engineering fundamentals, and applying DevOps/CI/CD principles specifically to ML workloads. - The Credentials: AZ-900, AI-900, and DP-100 are required; AI-102 is preferred. - The Pedigree: Experience as an AI Platform or Azure ML engineer at a major tech firm (Microsoft, Google, etc.) is a massive plus. Note on Schedule: This is a high-intensity, 2-week engagement. Candidates must be fully available for 30 hours per week during the mid-June window and be prepared to operate on Pacific Time (PT) schedules to align with the learner cohort. Unless otherwise noted, remote positions can be performed from the following approved General Assembly operating countries. United States of America (states of operation may vary), Canada (provinces of operation may vary), United Kingdom, Australia, and Singapore.

• Harden and maintain container images for compliance-driven distribution channels. • Build and mature Terraform modules and Helm charts used to deploy Coder in customer environments. • Own reference architectures, keeping them accurate as the platform evolves and enterprise deployment patterns shift. • Improve the upgrade experience for our users, making it more seamless, predictable, and reliable. • Contribute to architecture decisions and collaborate with teams across engineering. • Mentor other engineers, sharing what you know and raising the quality of the team’s work. • Hold a high bar for code quality, security, and performance in everything you ship.

Role Description We are seeking a highly skilled Senior SOC Platform Engineer with strong expertise in CrowdStrike Falcon Next-Generation SIEM, Falcon Fusion SOAR, Falcon EDR, Python automation, threat hunting, and detection engineering. This role is responsible for engineering, optimizing, and scaling SOC platform capabilities that enable advanced threat detection, incident response, security analytics, and SOC transformation initiatives. The successful candidate will act as a technical lead for security platform engineering, supporting customer onboarding, SIEM/SOAR content development, automation initiatives, threat intelligence integration, and SOC maturity programs. Microsoft Sentinel experience is required as a secondary platform. - Design, deploy, manage, and optimize CrowdStrike Falcon Next-Gen SIEM environments. - Configure detections, correlation rules, dashboards, reports, and alerting logic. - Engineer Falcon Fusion SOAR workflows for automated incident response. - Manage Falcon EDR policies, detections, investigations, and response actions. - Develop Python-based automation for SOC operations and threat-hunting activities. - Integrate third-party security telemetry and threat intelligence feeds. - Build MITRE ATT&CK aligned detection content. - Conduct proactive threat hunting using Falcon, Defender, and Notebook-based analytics. - Support Microsoft Sentinel analytics, playbooks, data connectors, and KQL content development. - Maintain platform documentation, SOPs, runbooks, and architecture standards. Qualifications - 5–10+ years of experience in Security Operations, SIEM, SOAR, EDR, or Security Engineering. - Hands-on experience with CrowdStrike Falcon Next-Gen SIEM. - Experience with Falcon Fusion SOAR and Falcon EDR. - Strong knowledge of threat detection, incident response, and threat hunting. - Proficiency in Python, REST APIs, PowerShell, and automation frameworks. - Working knowledge of Microsoft Sentinel, KQL, Azure Logic Apps, and Microsoft Defender. - Experience with cloud platforms including Azure, AWS, and GCP. - Strong communication and stakeholder management skills. Requirements - Lead engineering efforts for Falcon SIEM, SOAR, and EDR platforms. - Develop and tune detection use cases and correlation logic. - Create reusable automation and onboarding frameworks. - Support SOC operations through enrichment and orchestration. - Ensure telemetry quality, data normalization, and coverage optimization. - Participate in threat hunting and purple-team exercises. - Mentor analysts and platform engineers. - Support client onboarding and SOC transformation programs. - Drive continuous improvement and operational excellence. Preferred Skills - Splunk Enterprise Security - Microsoft Security Copilot - ServiceNow Security Operations - Palo Alto Cortex XSOAR - Infrastructure as Code (Terraform, ARM, Bicep) - CI/CD and DevSecOps concepts Preferred Certifications - CrowdStrike Certified Falcon Administrator (CCFA) - CrowdStrike Certified Falcon Responder (CCFR) - CrowdStrike Certified Falcon Hunter (CCFH) - Microsoft SC-200 - Microsoft AZ-500 - CISSP - CISM - GCIH Experience Level Senior Individual Contributor / Lead SOC Platform Engineer