Role Description We're not running an AI pilot. We're not building a chatbot. We're systematically rebuilding every repeatable workflow in the company — across Sales, Marketing, Finance, CS, HR, Legal, and Operations — on an AI-native foundation. We call this program AI Pioneer, and it is the defining internal initiative of the next 18 months at Emplifi. The Agentic Builder role is the engine of AI Pioneer. You'll be embedded directly into business teams, operating inside a federated model: - A small central hub provides governance and shared tooling (LLM gateway, eval harness, MCP server registry); you ship inside the business. - This is a hybrid role: part workflow engineer, part systems thinker, part domain translator. - Industry calls it Forward Deployed Engineer or AI Solutions Engineer. - This is not a consulting role. You don't recommend and move on; you build, you ship, and you own whether it works. What You'll Do Here - Discover & Design - Embed within business teams to map existing workflows, identify automation opportunities, and prioritise by impact and feasibility. - Translate business goals into concrete agentic workflow specifications — defining inputs, outputs, decision logic, and human-in-the-loop touchpoints. - Build & Deploy - Design and ship end-to-end AI workflows using no-code/low-code platforms (Make, or equivalent) and LLM-powered tools. - Engineer prompts as production assets — versioned, evaluated, regression-tested. - Integrate with APIs, CRMs, data warehouses, and internal tools — comfortable with JSON payloads, webhooks, and auth patterns without needing to write full backend code. - Use AI coding assistants (Claude, Gemini, ChatGPT, and Cursor) to produce, adapt, and debug scripts. - Embed & Enable - Act as the in-team AI expert for your assigned function — training colleagues, documenting workflows, and building institutional knowledge. - Collaborate with central engineering and the AI Pioneer Governance team when workflows require production infrastructure, security review, or data pipeline work. - Iterate & Scale - Maintain and improve shipped workflows based on usage feedback; establish monitoring, fallback logic, and human escalation paths. - Surface reusable patterns and components across functions, and contribute to the organisation's agentic playbook. Qualifications - Advanced prompt engineering — systematic, versioned, regression-tested. - Proficient with no-code/low-code automation tools at the complex end of the spectrum: multi-step workflows, conditionals, error handling, loops. - API literacy without hand-holding: read docs, handle OAuth/API keys, parse JSON, paginate, retry, respect rate limits. - Understands data shapes and how poorly formatted output breaks downstream steps. - Can read, lightly edit, and debug code (Python, JavaScript) produced by AI coding assistants. - Familiar with LLM concepts: context windows, temperature, tool use, structured outputs, RAG basics. - Eval and observability mindset: You instinctively reach for an eval harness before a workflow goes live. - Cost awareness: you can estimate token cost per run, spot a workflow that will bankrupt itself at scale, and choose model tier (Haiku/Sonnet/Opus or equivalent) deliberately. Requirements - Thinks in workflows, not tasks — naturally maps processes end-to-end before touching a tool. - Comfortable designing for failure: edge cases, fallback paths, and human escalation. - Can scope what should and shouldn't be automated — knows when a human decision is irreplaceable. - Can sit in a business team conversation and extract the automatable signal from the noise. - Understands enough about functional operations (finance cycles, campaign pipelines, hiring workflows, CS escalations) to build for how teams actually work, not how they say they work. - Can explain why something works (or doesn't) to people who don't code — without talking down to them or hiding behind jargon. - Recognize when a workflow touches personal data, financial data, customer data, or regulated content and route to central governance before shipping, not after. - Understand basic threat surface: prompt injection, data exfiltration via tool calls, over-permissioned agents, secret handling. - Comfortable with audit trails, access scoping, and "least privilege" defaults. - Ships working solutions — demonstrates bias toward done over perfect, with a clear standard for what 'done' means. - Owns outcomes, not just outputs — follows through on whether the automation is actually being used and delivering value. - Earns trust quickly within business teams by demonstrating domain curiosity and delivering fast. - Comfortable operating as a change agent in teams that may be skeptical — wins people over through results, not persuasion. - Knows when to escalate and involve central engineering — and how to hand off cleanly. Benefits - International and fast-paced environment - Unlimited Paid Time Off - Sick Days & Community Service Days - Multisport card - Maternity and Parental Benefit - Chance to work with the world's biggest brands at the CX tech leader - Agile and open-minded culture, with high levels of trust and flexibility - Opportunity for professional growth and development - Possibility to learn new and cutting-edge technologies, in an environment that encourages new ideas - Flexible working environment - Internal tech talks, Udemy courses, and workshops - Meetups & conferences - Possibility to work from offices in Prague (Karlin), Brno (Impact Hub), Pilsen (Roudná), or remotely within the Czech Republic - There's more as well! Speak with us to find out all the details!

• Build and enhance Microsoft Copilot Studio agents • Work with LLMs, agentic workflows, and autonomous AI actions • Develop intelligent agents within the Microsoft ecosystem • Integrate agents with enterprise systems using Power Automate and APIs • Support iterative rollout, testing, optimization, and scaling of AI agents • Design reusable agentic workflows and orchestration patterns • Collaborate with business and technical stakeholders to translate requirements into AI-driven solutions • Improve agent performance, prompt quality, and workflow efficiency • Stay updated with Microsoft AI ecosystem advancements and Copilot Studio capabilities

• Develop and maintain AI features from researching to building a POC and productionizing them • Assess the technical feasibility of customer Feature requests using AI solutions • Collaborate with product managers, designers, and fellow engineers to translate requirements into well-architected, reliable software • Partner with the AI Core Team on adoption, ensuring an approach fits into the agentic system design • Participate in code reviews • Create measurements and evaluations for the accuracy of the model’s predictions • Identify and resolve performance bottlenecks, bugs, and technical debt across the stack

Role Description Du bist die technische Schlüsselfigur in Enterprise-Projekten auf AWS. Du sitzt mit Kunden zusammen, verstehst ihre Herausforderungen und entwirfst Lösungen. Dann orchestrierst du AI Agents, lässt Infrastructure as Code generieren, prüfst den Output kritisch und iterierst. Nicht Zeile für Zeile. Sondern Architektur für Architektur. - Du entwirfst hochverfügbare AWS-Architekturen und setzt sie mit AI-gestütztem IaC um - Du arbeitest direkt mit Kunden an Cloud-Strategien und Migrationsprojekten - Du nutzt AI CLI-Tools als Multiplikator: Claude Code, Cursor oder Gemini CLI - Du mentorst andere Engineers und definierst technische Standards - Du triffst Architekturentscheidungen und übernimmst Verantwortung für das Ergebnis Qualifications - Mindestens 5 Jahre Erfahrung mit AWS und Cloud-Architekturen - AWS Professional Zertifizierung oder vergleichbar - Erfahrung mit mindestens einem AI CLI-Tool (Claude Code, Cursor, Gemini CLI) - Solide Kenntnisse in IaC (Terraform, CDK oder CloudFormation) - Sicherheitsbewusstsein für Enterprise-Anforderungen - Du kannst komplexe technische Zusammenhänge verständlich kommunizieren - Fließend Deutsch und Englisch Benefits - Flexible Arbeitszeiten und 100% Remotearbeit - Zugang zu AI-Tools und LLM-Keys. Nicht als Benefit, sondern als Arbeitsmittel - Echte Enterprise-Projekte mit Ownership. Du baust Produkte, auf die du stolz sein kannst - AWS-Zertifizierungen und Konferenzen - Ein Team von ~30 Engineers, das Wissen teilt statt hortet - Keine Folien-Kultur. Wir arbeiten an der Sache, nicht am Konzept Company Description FNTIO sind AI-First Systems Engineers für Enterprise. Wir verbinden tiefe Cloud- und AI-Expertise mit Hands-on-Mentalität, um Produkte zu bauen, die Unternehmen wirklich transformieren. Keine Buzzwords, kein Body Leasing. Ergebnisse.