Role Description Für unseren Kunden mit Sitz in München, einem führenden Hersteller von SMT Bestückautomaten, suchen wir im Rahmen der Arbeitnehmerüberlassung einen AI/Machine Learning Engineer (.NET & Python) (w/m/d), der die Weiterentwicklung von C#/.NET-Tools übernimmt, Python-basierte ML-Modelle entwickelt und robuste Integrationen sowie CI/CD-Pipelines für hochwertige Analysen und präzise Workflows gestaltet. - Weiterentwicklung des C#/.NET-Tools (Architektur, Features, Zuverlässigkeit, Performance) - Pflege und Erweiterung der Integrationen mit Azure DevOps/TFS (Work Items, Anhänge, Metadaten) - Pflege der Model-Context-Protocol-(MCP)-Schnittstellen zu den zugrunde liegenden Modulen - Entwicklung, Training, Evaluation und Auslieferung Python-basierter ML-Modelle (Sentence Embeddings, classification/ranking, multimodal) - Design robuster .NET–Python-Interoperabilität (API-Grenzen, Versionierung, Modell-Paketierung) - Aufbau und Pflege von CI/CD-Pipelines - Verbesserung von Datenqualität, Workflows und Evaluationsmetriken zur Steigerung der Zuweisungsgenauigkeit und Analysequalität. Qualifications - Abgeschlossenes Bachelor-Studium im Bereich Informatik, Ingenieurswesen oder vergleichbar - Praktische Erfahrung in der Entwicklung von C#- und modernen .NET-Anwendungen (ASP.NET, Razor, HTML) - Praktische Erfahrung im Bereich Applied Machine Learning (Design, Implementierung und Anwendung von ML-Ansätzen für reale Use Cases) - Praktische Erfahrung mit Python sowie modernen KI/ML-Frameworks (z. B. PyTorch, Hugging Face) - Erfahrung in Prompt- und Context-Engineering - (Optional Kenntnisse in Performance-Profiling und Maßnahmen zur Erhöhung der Zuverlässigkeit (z. B. Logging, Metriken) - Technologies: C#/.NET, inklusive Bibliotheken / Python, inklusive KI/ML-Bibliotheken - Fundiertes Verständnis von ML-Ansätzen, einschließlich Neuronaler Netze, Transformer/ViT, LLMs, Datenvorverarbeitung und Feature Engineering. - Fließende Englischkenntnisse, sowohl mündlich als auch schriftlich Benefits - Urlaubs- und Weihnachtsgeld - Unbefristeter Arbeitsvertrag - 30 Tage Urlaub - JobRad - Mentale Gesundheit - Lebenszeitkonto Contact Krisztina Szebényi-Schenker Tel.: +49 7034 65615013

Our Mission & Values: At Drata, we help companies earn and keep the trust of their users, customers, partners, and prospects. We’re the proof layer that shows great companies deserve the trust they aim to build. We live our values every day. Built on Trust means consistency is everything. Act with Integrity by always doing the right thing. Being Customer-Obsessed keeps the people we serve at the center of our work. Competitive Fire drives us to push ourselves harder than anyone else. Diversity brings unique perspectives that lead to better solutions. Automation First ensures we save time and money by making efficiency a priority. Our Culture & Work Style 🚀 At Drata, we’re not just building software - we’re building a mindset. Everything we do springs from: - Be a Driver (Owner‑Operator Mentality): Own your work. Improve relentlessly. Deliver results. - Move at Drata Speed (Precision & Velocity): Fast decisions. Quick learning. Immediate impact. - Stay Mission-Driven (Customer‑Obsessed): Challenge assumptions. Deliver value. Stay hungry. While we’re ideally looking for someone who can join us in a hybrid capacity from our San Francisco office, we know great talent isn’t limited by zip code. We’ll consider remote candidates across the U.S. who are a strong match for the role. If you thrive when you’re empowered, energized, and working with smart, mission-driven people where you’ll feel at home here. Why Join The Drata Team? The best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide, united by a culture that values trust, speed, and continuous growth. - See the Speed: Watch our CEO, Adam Markowitz, discuss the hyper-growth journey, from $0 to $100M ARR in just four years - Hear the Voice of the Team: Explore our "Life at Drata" page for employee testimonials on our collaborative and the growth opportunities available. - Experience the Impact: See why we are consistently recognized on Fortune's Best Workplaces lists. - Connect with Us on Socials: LinkedIn - follow us for company updates, employee stories, and career news. Job Summary: Drata is advancing the frontier of compliance automation by integrating intelligent AI capabilities into its platform. We are seeking a Senior AI Engineer to help design, build, and scale robust, high-impact AI systems that improve operational efficiency, enhance decision-making, and support trust-critical enterprise workflows. This role focuses on solving complex, real-world problems with agentic AI, LLMs, and intelligent reasoning systems, including automating questionnaire answering and other compliance-related workflows. You will work on creating generalizable AI solutions that can be applied across multiple products and domains, collaborating with cross-functional teams to bring cutting-edge research into production-ready systems. As a Senior AI Engineer, you will own the end-to-end design, implementation, and evolution of AI-driven systems embedded directly into Drata’s core platform. Your work will focus on building generalizable, reusable AI capabilities rather than one-off features, enabling multiple product surfaces and workflows across compliance and security. What you'll do: Build Agentic & Intelligent AI Systems - Design and implement LLM-powered systems capable of multi-step reasoning, evidence grounding, and decision support in high-trust domains. - Develop agentic workflows that combine retrieval, tool use, structured reasoning, and human oversight. - Create interactive AI experiences that allow users to engage naturally with complex compliance and risk data. Automated Reasoning Over Regulations & Evidence - Build AI systems that reason over structured and unstructured data to support regulatory interpretation, control alignment, and evidence validation. - Ensure AI outputs are traceable, explainable, and auditable, meeting the expectations of enterprise customers and auditors. Production-Grade AI Architecture - Architect and deploy scalable LLM + retrieval + agent systems in production environments. - Optimize for latency, cost, reliability, and evaluation in real-world enterprise workloads. - Partner with platform, security, product teams, and other application development teams with diverse skill sets to operationalize AI safely and effectively. Responsible & Trustworthy AI - Embed human-in-the-loop workflows, confidence thresholds, and safety guardrails into AI systems. - Ensure privacy-preserving data handling, robust failure modes, and transparent behavior aligned with Drata’s trust principles. What you'll bring: - Experience: 7+ years of hands-on software engineering experience; 2+ years specifically in ML/AI engineering. - Programming Languages: Proficiency in Python; TypeScript experience is a plus, especially for production AI system integrations. - Retrieval & Vector Stores: Familiarity with vector databases (Pinecone, Chroma, FAISS, etc.) and RAG system design. - LLM & AI Systems: Proven experience building and shipping LLM-based applications in production, including embeddings, RAG, agent frameworks, prompt engineering, and evaluation. - Production Expertise: Track record of taking AI systems from concept to production, designing scalable, maintainable solutions. - Problem Solving: Ability to decompose complex tasks into agentic workflows and reason over high-stakes, structured, and unstructured data. - Collaboration: Experience working cross-functionally with product, compliance, security, engineering teams, and partnering with other application development teams with diverse skill sets. Bonus Qualifications: - Experience in compliance, security, risk, or audit domains. - Familiarity with Snowflake-based analytics, knowledge graphs, or enterprise data platforms. - Experience partnering with non-technical stakeholders such as compliance or GRC teams. This role defines how AI is responsibly embedded into a trust-critical enterprise platform. Your work will: - Establish foundational agentic AI capabilities that power multiple present and future product experiences. - Enable customers to derive accurate, explainable insights from complex compliance and security data. - Set the technical and ethical standard for applying modern AI in regulated, high-stakes environments. How we support you: At Drata, our people are our strongest advantage—and we prove it with support that exceeds industry standards. Our total rewards package is designed to power your well-being, accelerate your growth, and keep your work-life balance thriving. Explore how we invest in your Life at Drata. - Shared Success: We provide stock equity to ensure that as the company grows, you share directly in that success. Equity gives every employee a sense of ownership and the opportunity to celebrate our wins together—because your contributions don’t just support our progress; they help drive our collective success. - Health & Wellness: Up to 100% employer-paid premiums for medical, dental, and vision coverage for employees and their dependents, along with comprehensive wellness benefits and healthcare concierge services designed to support your needs beyond traditional insurance. - Financial Well-being: A comprehensive suite of financial benefits, including a 401(k) plan, company-paid life and disability insurance, tax-advantaged spending accounts, and a range of discounted voluntary offerings to help you customize and strengthen your overall financial position. - Family Support: We want to support you in life's most important moments, so we offer a paid Parental Leave policy, after six months of employment. Employees also receive access to Kindbody fertility and family-building benefits and dedicated leave specialists who help guide you through the entire process. - Growth & Development: Generous annual stipends for both professional and personal development, empowering you to invest in your continued growth. You’ll also have access to a wide range of internal learning opportunities, ensuring you can build new skills, deepen your expertise, and advance your career with confidence. - Time Off & Flexibility: We believe that to do your best work, you should get the time you need for rest, rejuvenation and recovery. Drata offers a flexible vacation policy, paid holidays, and other perks to recharge. This role will receive a competitive base salary, benefits, and/or stock, typically in the form of Restricted Stock Units (RSUs). The applicable salary range for each US-based role is based on where the employee works and is aligned to one of 3 tiers based on the cost of labor for that geographic area. The expected ranges for this role are set forth below, subject to change. Tier 1: $192,000 - $259,800 Tier 2: $172,800 - $233,800 Tier 3: $153,600 - $207,800 You can view which tier applies to where you plan to work here. A variety of factors are considered when determining someone’s leveling and compensation–including a candidate’s professional background and experience. These ranges may be modified in the future and final offer amounts may vary from the amounts listed above.

• Work closely with data science, ML/DevOps, and engineering teams to enhance AI infrastructure • Improve and enhance predictive models • Test hypotheses and present findings to management • Develop understanding of Sift’s data and provide analysis • Stay up to date with current ML and GenAI trends • Collaborate with Data Scientists, ML & Dev Ops, Engineers, and Product teams to integrate capabilities

Location: Remote (Global) Reports to: Head of Product Company: Supernal Type: EOR FTE or Contractor Rate: $50/hr About Supernal At Supernal, we help SMBs hire their first AI employee. Our AI teammates are built with intelligent, agentic workflows and deployed on our proprietary platform. We don't build tools — we deliver working, value-generating AI Employees. Our AI Platform Engineers, known internally as Masons, are the builders behind these systems. Now, we're looking for a Senior Mason to help lead this craft. The Role As a Senior AI Platform Engineer, you'll be on the frontlines of our most critical customer implementations, with a strong focus on conversational AI agents deployed in real business environments. You'll design, build, and deliver agentic systems that handle live users, multi-turn conversations, real-time constraints, and complex integrations. These are not demos or experiments — they are production systems that customers rely on. Beyond hands-on engineering, you will act as a technical owner for client delivery. You'll translate customer requirements and SOWs into working systems, own delivery timelines, manage technical tradeoffs, and ensure successful outcomes in production. This is a hands-on role. You're not just reviewing PRs or sitting in meetings — you're in the weeds, building systems, debugging failures, and showing others how it's done. Responsibilities - Build advanced AI agent workflows on n8n and Supernal's proprietary platform - Design, implement, and deploy conversational agents, including multi-turn flows, state management, and tool usage - Own end-to-end technical delivery for high-priority customer implementations, from architecture through production launch - Translate customer requirements and SOWs into clear technical designs, execution plans, and deliverables - Make and own architectural decisions across LLM orchestration, RAG design, API integrations, and workflow decomposition - Handle real-world voice system challenges including latency, interruptions, fallbacks, error handling, and failure recovery - Write automated tests — unit tests for isolated logic and end-to-end tests for full workflow and user journey validation - Apply solid error handling: distinguish retryable vs. fatal failures, surface meaningful error messages, and avoid silent failures - Actively debug complex production issues across agent logic, prompts, integrations, and external dependencies - Partner with delivery and product leadership to manage timelines, scope, and technical tradeoffs during implementation - Review technical work for quality, scalability, and maintainability, setting a high bar for engineering excellence - Define, document, and evolve best practices for building and delivering reliable AI Employees You Might Be a Fit If You... - Have 4+ years of experience as a software engineer, automation engineer, or systems builder shipping production systems - Have hands-on experience deploying voice agents using leading platforms (e.g., ElevenLabs, Retell, Nextiva), including telephony and streaming audio integration patterns - Understand multi-turn conversation design: state management, context windows, interruption handling, and graceful recovery - Have tackled real-time constraints in production: latency budgets, streaming audio, fallback paths, and API chaos - Write automated tests as a matter of course — unit tests, integration tests, and end-to-end workflow validation — and treat testing as part of shipping, not an afterthought - Apply solid engineering fundamentals: error handling, retry strategies, separation of concerns, and clean interfaces between components - Are comfortable owning delivery outcomes end-to-end — not just writing code — including timelines, reliability, and client success - Have deep experience with agentic architectures, workflow automation platforms (n8n, Zapier, Make), and APIs - Understand LLM orchestration, prompt engineering, function calling, and retrieval-augmented generation (RAG) - Can prototype fast and finish the job to production quality — with tests, error handling, monitoring, and runbooks - Are an elite debugger who can reason through edge cases, flaky agents, and real-world API failures - Communicate clearly and fluently in English — both in writing and verbally — especially when articulating technical decisions, tradeoffs, and implementation choices to technical and non-technical stakeholders alike - Can run meetings, drive decisions, write crisp updates, and ask the right questions early — without needing heavy process - Thrive in fast-paced, ambiguous startup environments and take ownership without being asked - Bring a low-ego, high-integrity approach to collaboration and leadership What Success Looks Like - Voice-first AI Employees are delivered on time, meet customer requirements, and perform reliably in production - Client implementations are predictable, well-architected, and resilient under real-world conditions - Complex conversational and voice workflows behave consistently and recover gracefully from failure - Code is well-tested, well-documented, and maintainable — not just functional - Technical decisions are communicated clearly and proactively to stakeholders, with tradeoffs explained and risks surfaced early - Engineering best practices reflect real production learnings and are widely adopted across the Mason team - Delivery artifacts — runbooks, SOPs, reusable components — raise the bar for the whole team