Role Description Are you passionate about leveraging AI to transform global industries? Do you have a proven track record of working with LLMs and building agentic solutions? Join Elixirr Digital as an AI Engineer, where you will drive innovation and help shape the future of intelligent systems for clients across industries like banking, insurance, healthcare, telecommunications, consumer goods, and more. What will you be doing as an AI Engineer at Elixirr Digital? - Design and Implement Solutions: Architect, design, and develop advanced AI systems with a focus on LLMs and agentic solutions that transform enterprise workflows. - Collaborate: Collaborate with cross-functional experts to deliver AI-driven innovations and mentor junior engineers. - Drive Innovation: Work on a mix of internal R&D projects and enterprise-level solutions, building and optimizing tools for both internal and client use. - Deploy at Scale: Develop and maintain production-ready AI solutions, ensuring scalability, performance, and reliability. - End-to-End Lifecycle: Own and contribute to the entire AI development lifecycle—from research and prototyping to deployment and monitoring. - Deliver Tangible Outcomes: Help global enterprises achieve measurable impact through solutions like underwriting agents, airport assistants, pharmacy workflow optimizers, and customer due diligence systems. Qualifications - Hands-on experience working with LLMs, with demonstrated expertise in building and deploying agentic solutions using frameworks such as LangChain, AutoGen, Crew, or Swarm. - Solid background in programming and past experience in machine learning, with a deep understanding of at least one area such as deep learning, reinforcement learning, fine-tuning, or model development. - Ability to design and lead AI solutions while also contributing directly to development. Excellent problem-solving, analytical, and critical thinking skills, with a proficiency in applying mathematical principles to analyze, model, and solve complex problems. - Passion for transforming businesses and delivering measurable results through AI. - Experience working in cross-functional teams, balancing R&D and production-level work. - Stay ahead of AI trends, continuously innovate by building and refining tools for internal and client use, and actively apply cutting-edge research to improve processes and develop scalable, impactful solutions. Requirements - Proven track record of leading AI projects from concept to deployment. - Strong understanding of the AI development lifecycle, with deep expertise in at least one part of the process. - Examples of deployed AI systems demonstrating agentic capabilities. Benefits - Individually tailored benefits package - Performance bonus - Employee Stock Options Grant - Employee Share Purchase Plan (ESPP) - Competitive compensation - Flexible working hours and remote work - Multi-sport card - Full medical checkup - Learning and development budget - Growth and development opportunities - Referral bonus - Anniversary bonus

• Design scalable AI architectures for customer use cases in line with enterprise and security standards • Lead implementation of AI software components such as model serving, orchestration, retrieval, and integrations • Run time-bound proofs of value to demonstrate business outcomes quickly and clearly • Help migrate AI workloads between cloud, on-premises, and hybrid environments on Dell infrastructure, optimizing performance, reliability, and security • Take shared responsibility for production readiness and early production stability, including monitoring, performance optimization, and issue triage • Work closely with AI Data Specialists to define and consume AI-ready data pipelines that support performance and reliability • Collaborate with AI Strategists and Enterprise Architects to align technical scope with business outcomes and target-state architectures • Provide documentation, runbooks, and knowledge transfer to customer teams, and contribute to Dell AI Factory reference architectures and playbooks • Mentor other technical team members on AI architecture patterns, Dell AI infrastructure capabilities, and responsible AI practices

• Design and implement LLM-powered applications, including RAG pipelines, AI agents, chatbots, and generative AI integrations. • Manage AP/AR, invoice processing, collections, and payment runs. • Build, optimize, train, fine-tune, and evaluate machine learning and data science pipelines. • Process payroll in accordance with AU legislation. • Architect, deploy, and maintain AI infrastructure, including containerized environments, CI/CD pipelines for ML, monitoring, and scalable production systems. • Prepare financial and management reports (BS, P&L, Cash Flow). • Integrate with commercial LLM APIs (e.g., OpenAI, Anthropic) and open-source models. • Support AU accounting compliance; BAS/IAS prep is a plus. • Engage with business users and stakeholders to interpret requirements, scope AI use cases, and translate ambiguous needs into clear technical specifications. • Collaborate with product, engineering, and non-technical teams to align AI solutions with business objectives and user workflows. • Establish best practices for prompt engineering, model evaluation, and responsible AI development. • Document system architectures, runbooks, and handover materials to support long-term maintainability.

HiPeople is the AI Hiring Platform that takes care of screening, interviews, assessments, and references. So recruiting teams can focus on what matters most. People. We work with some of the world's leading brands, including the NFL, Zapier, Celonis, and DAZN. and are backed by leading investors and operators such as: Moonfire founder Mattias Ljungman, Capnamic, Cherry, André Christ (LeanIX, an SAP company), Mirko Novakovic (Founder Instana/Dash0), Micha Hernandez (Fiberplane), and others. We’re hiring an Applied AI Engineer to build the backbone of how we ensure quality, reliability, and trust in our AI systems as we scale toward $10M ARR and beyond. You’ll work directly with founders and play a central role in making sure our AI products are robust, measurable, and enteprise-production-ready. This role is for people who care deeply about quality, enjoy working on hard system problems, and want to build AI that actually works in the real world. We are an extremely lean team and plan to reach $10M ARR with fewer than 20 people. Every hire materially changes the company. This role has direct exposure to founders and real responsibility from day one. What you’ll do Own evaluation systems and quality standards - Build and maintain evaluation pipelines for core AI workflows across screening, interviews, assessments, and references - Define metrics, benchmarks, and acceptance criteria for AI outputs - Track performance over time (quality trends, drift, regressions) and make results visible across the team Drive continuous improvement of AI performance - Identify issues across prompts, workflows, and data pipelines using both quantitative analysis and deep dives into real cases - Design and implement improvements across: - prompting strategies - model selection, configuration, and fine-tuning - input data quality and preprocessing - orchestration and workflow design - Push new systems from “working” (80%) to reliable and high-quality (95%+) Ensure reliability, monitoring, and stability - Build and improve monitoring for AI systems (e.g. dashboards, alerts, tracing) - Detect and prevent failure modes, breakdown risks, and performance degradation - Monitor usage, rate limits, and capacity to ensure stable operation at scale Drive testing, CI, and safe shipping practices - Integrate AI and prompt testing into CI (e.g. regression tests, golden datasets, staging environments) - Define standards and tooling so product and engineering teams can safely ship without introducing regressions - Act as a quality gate for AI-related changes Own AI system audits and compliance support - Prepare and support internal and external audits (e.g. SOC 2 and beyond) - Provide evidence, documentation, and artifacts for AI system behavior and controls - Translate audit findings into concrete improvements in systems and processes Productionize AI workflows (not just prototype them) - Build and productionize AI workflows that meet defined quality and reliability standards - Support product and engineering teams in integrating AI cleanly into product logic and user experience - Ensure new AI capabilities are robust, measurable, and maintainable before release What we are looking for - 100% alignment with our Ops Principles (if you feel this isn’t you, do not apply) - Excitement for building in Go - Experience working with AI/ML systems, LLMs, or data-intensive applications - High ownership mindset and attention to detail - Strong interest in quality, reliability, and system performance, not just building features - Ability to debug complex systems across prompts, models, and data pipelines - Clear communication and documentation skills - Comfort improving systems and processes, not just using them - Experience with evaluation methods, metrics, or experimentation is a strong plus - Familiarity with monitoring, CI/CD, and production systems is a plus Background Strong candidates often come from: - AI/ML engineering or applied AI roles - Backend or systems engineering roles with exposure to AI/ML - Data science roles with strong engineering and production experience - Other paths that demonstrate building and improving real-world systems with rigor Logistics This role is remote or on-site in our Berlin office. We do not offer any Visa support for Germany at this time. Benefits - Direct ownership of one of the most critical parts of the company: AI quality and reliability - Work closely with founders on core product and technical decisions - Competitive salary and meaningful stock options - Educational stipend to support ongoing learning and development - The best team to work with (true story!) Process - Step 1: AI Application Screen (immediate) - Step 2: AI Recruiter Interview (right after successful AI Application Screen) - Step 3: AI Skills-Assessment (right after successful AI Recruiter Interview) - Step 4: Interview with Co-founder - Step 5: Interview with the team (incl. Live Case Study) - Step 6: References + Offer - Duration: 1 week, end-to-end 🌈 We proudly believe in the power of diversity and inclusion. Diversity of thought fuels our success which can only be achieved with a diverse team. We welcome people from any race, orientation, gender, religion, age, ethnicity, differently-abled, neurodiverse or identity, we value all uniqueness.