Role Description Most engineers get to use large language models. You will get to build the systems that run them in production, at scale, under real latency and reliability constraints, for one of the most recognised names in application security and traffic management. Our client is expanding its AI Core group and is looking for a Senior or Staff AI & ML Engineer in the UK. This is hands-on, build-focused work at the centre of how the business turns generative AI from a prototype into a dependable product. You will design and ship multi-agent systems, retrieval-augmented generation pipelines, anomaly detection, fine-tuned models, and the real-time inference layer that serves them. If you want ownership over a serving stack rather than a single notebook, and you want your work measured by what holds up in production rather than what demos well, this is the seat. What you will own - Building and shipping generative AI features end to end: from model selection and fine-tuning through to the inference path that serves them. - Designing multi-agent and RAG architectures, and anomaly detection, that are accurate, observable, and cost-aware at scale. - Owning the real-time inference layer on Triton and TensorRT, optimising for latency, throughput, and GPU efficiency. - Standing up the surrounding microservices in Python and FastAPI, containerised and orchestrated for reliability. - Setting the technical bar: making architecture decisions, raising code quality, and mentoring engineers around you. - Partnering with research and product teams to take ideas from experiment to a service customers depend on. Qualifications - 5 to 10 years of relevant experience, including a proven track record as a technical lead who mentors others. - Strong, current Python engineering, with production services built and shipped (FastAPI or similar). - Genuine hands-on GenAI depth: LLMs, RAG, agentic or multi-agent workflows, anomaly detection, and fine-tuning (for example LoRA or PEFT). - Real-time inference experience with NVIDIA Triton and TensorRT, with real attention to latency, throughput, and cost. - A microservices mindset, with services built in Python and FastAPI, containerised and orchestrated for reliability. - Solid grounding in Docker and Kubernetes, and large-scale distributed systems on a major cloud. - Right to work in the UK. We welcome applications from all backgrounds and are committed to equal opportunity. Requirements - Experience with vLLM or other serving frameworks alongside Triton and TensorRT. - Experience in security, networking, or other high-reliability domains. - Big-data tooling (Spark, Databricks, Snowflake) and modern MLOps practice. Benefits - A genuine build mandate inside an established AI Core team, not a proof-of-concept that never ships. - Fully remote working anywhere in the UK, built around delivery rather than presence. - Competitive salary, strong benefits, and clear scope to grow into staff and principal-level influence. - The backing of C-Serv throughout: a delivery partner that runs a real quality filter and looks after its people, end to end. - A clear path to grow into staff and principal-level technical influence. - Full support from C-Serv across the hiring process and beyond, with full-cycle accountability. - A values-led, woman-owned delivery partner built on empathy, integrity, collaboration, and growth.

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 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. Not vibes. Reusable prompt chains over one-shot cleverness. - 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 eval-gated before release — not just demo-proven. - Writes and maintains Python and/or JavaScript at a production level, with strong leverage of AI coding assistants; fluent across code-first and low-code environments, and knows when each is the right call. - Deep understanding of agentic systems and workflow orchestration: autonomous agents, deterministic workflows, API calls, and human-in-the-loop decision points — knows when to use which. - Strong integration skills: API docs, OAuth, webhooks, JSON parsing, retry logic, rate limits, and connecting AI to existing business systems and data sources. - Solid grasp of LLM fundamentals — context windows, temperature, tool use, structured outputs, RAG, model cost, and latency tradeoffs — and applies them to make sound decisions on model selection, output quality, and workflow design. - Moves fast from proof of concept to production through rapid iteration, user feedback, and a clear-eyed understanding of how data structure and output formatting affect downstream reliability. - 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 — wins people over through results, not persuasion. - 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. - There's more as well! Speak with us to find out all the details!

Role Description Product Heroes seleziona un AI/ML Engineer per Live Story, la piattaforma next-generation che sta rivoluzionando il modo in cui i brand gestiscono il digital storytelling. Il tuo codice renderà la piattaforma "intelligente", automatizzando processi creativi e analitici. In concreto, ti occuperai di: - AI Product Development: Progetterai e implementerai feature basate sia su Generative AI (fine-tuning e orchestrazione di LLM come Llama o OpenAI) che su modelli di Machine Learning classico. - Bridge Tech-Business: Lavorerai a stretto contatto con il Product Team per identificare i casi d'uso ad alto impatto, traducendo i bisogni di business in progetti di data science concreti. - MLOps & Infrastructure: Non scriverai solo modelli, ma contribuirai a costruire l'infrastruttura per il prompt management, il monitoraggio dei modelli, l'ottimizzazione dei costi e le pipeline di deploy. - Continuous Improvement: Monitorerai le performance dei modelli in produzione, analizzando i dati di utilizzo per iterare e garantire che l'AI porti vero valore al business. Qualifications - Almeno 3 anni di esperienza applicata in AI/Data Science, idealmente maturata in contesti di prodotto o SaaS. - Hard Skills: - Python Mastery: Conoscenza profonda di Python e delle sue core libraries. - GenAI Stack: Esperienza pratica con framework di Deep Learning (PyTorch, Hugging Face) e strumenti di orchestrazione come LangChain. - Classical ML: Padronanza di Scikit-Learn, Pandas, Numpy e modellazione statistica. - MLOps: Hai esperienza nel portare modelli in produzione (deployment, performance tuning, ottimizzazione costi/latenza). - Mindset: - Pragmatismo: Sai muoverti lungo tutto lo spettro del ML, dalla semplice classificazione ai Transformers complessi, scegliendo sempre lo strumento più adatto al problema. - Comunicazione: Sai spiegare concetti tecnici complessi a stakeholder non tecnici e collaborare efficacemente con il business. - Nice to have: - Esperienza nella creazione di "AI Copilots" o strumenti di generazione contenuti. - Familiarità con l'implementazione Frontend delle feature AI. Benefits - Retribuzione (RAL): Range 35.000€ - 45.000€. - Flessibilità: L'azienda opera con una policy Remote-first. Puoi lavorare in Full Remote da dove vuoi, oppure sfruttare gli uffici a Milano se preferisci il contatto dal vivo. - Ambiente Tech: Entrerai in un team dove la qualità del codice e l'innovazione sono al primo posto.