Emplifi (external posting)

Role Description We're not running an AI pilot. We're not building a chatbot. We're systematically rebuilding repeatable workflows across Sales, Marketing, Finance, Customer Success, HR, Legal, and Operations on an AI-native foundation. We call this initiative AI Pioneer , and it is the defining internal transformation program at Emplifi. The Agentic Builder is at the heart of that transformation. Embedded directly within business teams, you'll rapidly turn business problems into working AI solutions by building agents, workflows, automations, and integrations that deliver measurable impact. You'll operate within a federated model: a small central AI team provides shared infrastructure, governance, and engineering standards, while you own solution discovery, delivery, and adoption within your business function. You'll partner closely with AI Engineers to scale successful solutions into production when needed. 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 solutions using the fastest appropriate approach — combining code-first development (Python, JavaScript), agent frameworks, APIs, and low-code/no-code platforms (n8n, Make, Zapier, or equivalent). - Build agents, automations, and workflow systems that solve specific business problems and can be rapidly tested, improved, and scaled. - Engineer prompts as production assets — versioned, evaluated, regression-tested. - Build integrations between AI solutions and existing business systems using APIs and modern integration patterns. - Leverage AI coding assistants to accelerate development while maintaining ownership of code quality, reliability, and maintainability. - Embed & Enable - Act as the in-team AI expert for your assigned function — training colleagues, documenting workflows, and building institutional knowledge. - Collaborate closely with AI Engineers and the AI Pioneer Governance team to review, harden, and transition solutions requiring production infrastructure, security review, or advanced engineering support. - 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 - Evidence of building automations, agents, integrations, AI-powered workflows, or other solutions that delivered real business value. Requirements - Technical & AI Engineering Foundations - Production-grade prompt engineering: systematic, versioned, regression-tested, and evaluated before release. - Writes and maintains Python and/or JavaScript at a production level, with strong leverage of AI coding assistants. - Deep understanding of agentic systems and workflow orchestration: autonomous agents, deterministic workflows, API calls, and human-in-the-loop decision points. - Strong integration skills: API docs, OAuth, webhooks, JSON parsing, retry logic, rate limits. - Solid grasp of LLM fundamentals — context windows, temperature, tool use, structured outputs, RAG, model cost, and latency tradeoffs. - Moves fast from proof of concept to production through rapid iteration, user feedback, and understanding of data structure and output formatting. - Business & Systems Thinking - Thinks in end-to-end workflows rather than isolated tasks. - Comfortable designing for failure: edge cases, fallback paths, and human escalation. - Can scope what should and shouldn't be automated. - Quickly translates ambiguous business problems into buildable technical solutions. - Understands how business functions operate and designs for real-world processes. - Communicates technical concepts clearly to non-technical stakeholders. - Governance & Security - Recognizes security, privacy, and compliance risks in AI workflows and knows when to involve central governance. - Understands core AI security concepts, including prompt injection, permissions, and secure handling of secrets. - Delivery & Ownership - Ships working solutions with a bias toward action. - Owns outcomes, measuring whether solutions deliver business value. - Builds trust through curiosity, execution, and results. - Comfortable operating as a change agent in teams that may be skeptical. - Knows when to involve AI Engineering and how to hand off effectively. 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.

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!