Role Description Our LiveOps team sits at the front line of this mission: monitoring systems, responding to incidents, and continuously improving the automation and observability that keep our services healthy. Every action you take directly contributes to the stability and trust our customers depend on. As a LiveOps Engineer, you will help operate, monitor, and enhance Civica’s production and cloud environments. Working closely with SRE, Platform, and Development teams, interfacing with the support and services teams, you will support uptime, automation, and observability improvements that make our services more reliable. You’ll contribute to incident response, environment management, and the ongoing evolution of how Civica delivers and supports its software in the cloud. Working closely with SRE, Platform, and Development teams, you will help detect, troubleshoot, and resolve live issues; while also contributing to the continuous improvement of our monitoring, deployment, and incident management practices. You will participate in an on-call rotation, respond to production alerts, and you will play a key role in maintaining Civica’s high standards for reliability, performance, and customer experience. What you will be doing: - Monitoring and incident response: Operate our live environments using modern observability tools (Grafana, Prometheus, DataDog, Azure Monitor). Respond quickly to alerts, triage incidents, and coordinate with SRE and Platform teams to resolve issues and restore service. - Automation and operational efficiency: Automate environment builds, deployments, and day-to-day operational tasks using Terraform, Ansible, PowerShell, or Bash. Reduce manual intervention and help improve speed, consistency, and resilience. - Cloud and infrastructure operations: Support and maintain our environments across Azure, AWS, and VMware. Work with containerised workloads (Docker, Kubernetes) and contribute to scaling and performance improvements. - Continuous improvement: Capture learnings from incidents and partner with SREs and developers to drive root cause analysis (RCA) and preventative action. Help refine alerting thresholds, deployment processes, and monitoring coverage. - Collaboration and documentation: Work closely with engineers across teams to maintain runbooks, document operational standards, and ensure knowledge is shared and applied consistently across Civica’s cloud services. Qualifications - Experience operating production systems in cloud or hybrid environments (Azure, AWS, or similar). - Familiarity with Kubernetes, containerisation, and supporting tools (Helm, ingress controllers). - Basic understanding of networking and infrastructure fundamentals (DNS, load balancing, VPNs, and firewalls) and able to troubleshoot (e.g., pcap). - Hands-on experience with scripting or automation (PowerShell, Bash, or Go/Python). - Knowledge of CI/CD pipelines and fluent with version control (GitHub Actions, Azure DevOps, Jenkins, or similar). - Experienced with monitoring and alerting solutions (Prometheus, Grafana, DataDog, Elastic, Azure Monitor). - Strong analytical and problem-solving skills, with the ability to stay calm during incidents. - Collaborative communicator who thrives in cross-functional, fast-paced environments. Benefits - 25 Days Annual Leave + bank holidays – plus the option to buy up to 10 extra days! - Days of Difference – Up to 3 extra days off for volunteering. - Pension Contributions – 5% employer match to support your future. - Income Protection – Up to 75% salary cover for long-term illness. - Life Assurance – 4x salary tax-free lump sum. - Critical Illness Cover – £25,000 lump sum (extendable to dependents). - Private Medical Insurance – Fast access to private healthcare. - Health Cash Plan – Claim back physio, therapies & more. - Dental Insurance – Cover for routine & emergency care. - Affinity Groups – Join employee-led communities. - Bounty Bonus – Refer a friend & get rewarded. Company Description At Civica, we are committed to building an inclusive and diverse workplace where everyone feels valued and supported. We believe that a variety of perspectives drives innovation and excellence, and we welcome applicants from all backgrounds, cultures, and experiences. We are an equal opportunity employer. We do not discriminate based on race, ethnicity, religion, gender, sexual orientation, disability, age, or any other legally protected characteristic. Our recruitment process is designed to ensure fairness and transparency, so every candidate has an equal chance to contribute to our mission. If you need any adjustments or accommodations to participate in our recruitment process, please let us know. We are here to support you.

Role Description At Orbitant we are looking for AI Engineers (mid and senior, remote) specialized in building production-grade systems with LLMs, with experience across different types of projects and environments, but above all with a strong desire to keep growing. We are looking for people who not only code, but understand the why behind what we do, and want to deliver real value. We don't hire someone for a project, but people we want to work with long-term. Responsibilities - Design, build, and ship to production AI agents and LLM-based systems for national and international clients — from scoping with the client to deployment and operation. - Take projects from pilot to production: define the evaluations that matter, instrument traceability, and ensure that what ships meets the agreed business outcomes. - Implement and maintain RAG systems over client documentation and knowledge: chunking strategy, retrieval, reranking, ingestion pipelines. - Design multi-step agent and workflow architectures (e.g. with LangGraph) — state management, tool use, error recovery, cost management. - Build evals (offline and online) with tools like Langfuse: define metrics, datasets, benchmarks against real outcomes — not against "the demo works". - Design and integrate MCP servers and connect agents with existing client systems (ERPs, CRMs, internal tools). - Contribute to Orbitant's internal AI-first platform: reusable skills, libraries, templates, and components that accelerate delivery of future projects. - Question the "why" before the "how" — collaborate with business profiles to define the outcome before the architecture. - Review and improve code (your own and your teammates'), work with legacy code when needed, and maintain high quality standards. - Mentor more junior teammates and share learnings (technical sessions, documentation, code reviews). - Propose new techniques, tools, and processes when they add real value (not for hype). - Be accountable for what you put in production: cost, latency, observability, failures. Qualifications - Experience building production systems with LLMs: agents, RAG, generation pipelines, automations. - Solid Python as your main working language. - Hands-on knowledge of an agent/workflow orchestration framework (e.g. LangGraph, LangChain, etc.). - Experience designing and implementing evaluations (evals) and traceability of LLM-based systems (e.g. Langfuse or another observability tool). - Real understanding of prompt engineering: structuring, techniques (few-shot, CoT, structured output, tool use). - Experience with Vector DBs (pgvector, Qdrant, Pinecone, Weaviate, Chroma...) and RAG patterns (chunking, retrieval, reranking). - Ability to reason about trade-offs between providers and models (cost, latency, context window, capabilities) without being locked into a specific API. - Anthropic power user: hands-on mastery of Claude Code, Claude SDK, and the Anthropic ecosystem. - MCP (Model Context Protocol): designing or consuming MCP servers. - Solid engineering practices: clean code, testing, CI/CD, version control, ability to work with legacy code. - Level of English that allows communication with international team and clients. - "Pilot-to-production" mindset: errors, retries, observability, cost, offline + online evals. Requirements - TypeScript/Node for full-stack integrations and AI-native product backends. - Experience with Cloud infrastructure (AWS/GCP/Azure) and knowledge of Docker/Kubernetes. - Experience with fine-tuning or lightweight training (LoRA, custom embeddings, reranking). - Experience mentoring and helping other people grow. - Knowledge of AI security and privacy (PII, prompt injection, jailbreaks, data leakage). - OSS contributions, papers, talks, or public AI side-projects. Benefits - 100% remote work (Spain-based) - Top office in Madrid with free attendance - Real flexibility - Latest generation MacBook - Claude license - Training and mentoring - Flexible benefits with the possibility of health insurance - Salary between €40,000 and €60,000 gross per year - Referral bonus - The chance to build the kind of engineering that gives companies escape velocity, and to reach your own - Be part of a spectacular team that can't wait for you to join

Role Description Chi cerchiamo - Cerchiamo un AI Engineer con esperienza nell'applicazione di LLM, framework agentici e modelli on-device a problemi di prodotto reali. - Ruolo hands-on, in un team che lavora sia in cloud sia direttamente sui dispositivi mobile dei nostri utenti. Cosa farai - Sviluppo end-to-end di nuove funzionalità AI nei nostri prodotti, con focus rilevante su soluzioni edge AI che girano su iOS e Android. - Scelta dei modelli giusti per il contesto giusto (cloud vs on-device), valutando trade-off di accuratezza, dimensione, latenza e consumo di risorse. - Definizione, insieme ai team mobile, di come integrare i modelli nelle app e di come sfruttare l'accelerazione hardware disponibile. - Contributo attivo alla strategia AI dell'azienda insieme a engineer, product manager, designer e data scientist. - Sei membro effettivo dell'AI Guild e dell'AI Squad: le direzioni si decidono insieme. - Definizione di metriche e metodologie di valutazione per misurare qualità, accuratezza e sicurezza delle funzionalità AI rilasciate. - Diffusione di best practice e cultura del miglioramento continuo nel team engineering. Qualifications - 3+ anni di esperienza come ML / AI Engineer, hands-on. - Esperienza concreta nella progettazione e nel rilascio di applicazioni e sistemi multi-agent basati su LLM (RAG, vector database, modelli di ultima generazione per testo e audio). - Esperienza nel fine-tuning di LLM. - Capacità di valutare gli output dei modelli e di costruire metriche di accuratezza, qualità e sicurezza. - Ottima padronanza di Python e dello stack ML/DL (LangChain, PydanticAI, scikit-learn, pandas, PyTorch). - Familiarità con piattaforme di observability per LLM (Langfuse). - Capacità di progettare e mantenere servizi basati su FastAPI. Requirements - Esperienza su AI on-device e contribuire alle scelte tecniche. - Conoscenza dei principali runtime di on-device ML: Core ML (iOS) e TensorFlow Lite / LiteRT (Android). - Familiarità con i framework di computer vision e image analysis su mobile: Vision (iOS), ML Kit (Android), MediaPipe. - Conoscenza di ONNX come formato di interscambio e di tecniche base di quantizzazione per ridurre il footprint dei modelli. - Capacità di ragionare su trade-off tra latenza, batteria, qualità dell'inferenza e privacy. Mindset - Approccio orientato al prodotto: prima l'impatto, poi la tecnologia. - Ottime capacità comunicative, scritte e verbali — fondamentali per lavorare a ponte tra team AI, mobile e prodotto. - A proprio agio in contesti ambigui, con autonomia decisionale. - Soft skill mature: intelligenza emotiva, gestione del tempo, capacità di collaborazione. Nice to have - Esperienza nel portare un modello AI in produzione su un'app mobile reale. - Esposizione a strumenti di infrastructure-as-code. Benefits - Interessanti opportunità di crescita tecnica e professionale. - Accesso a formazione continua come un processo no-stop, ti metteremo a disposizione strumenti e piattaforme per formarti continuamente. - Meritocrazia. - Un contesto davvero data driven e people centric. - Potrai vivere un’eccitante fase di scaleup ed espansione in nuovi mercati. - Lavorerai con un team stimolante e super competente. - Possibilità di avere un forte impatto su milioni di utenti. - Parteciperai a eventi di settore. Company Description La nostra anima è 100% italiana e le nostre ambizioni sono internazionali. Qui in Italia gestiamo l’intera filiera produttiva, dall’ideazione del prodotto a tutta l’esperienza utente web e app, dalla comunicazione alla produzione fino alla consegna a casa. I nostri capolavori sono Made in Italy, risultato dell’unione di tecnologia e cura artigianale. - Certificazione per le pari opportunità. - Italy’s Best Customer Service per 3 anni di fila.

Role Description This role is to measure, analyze and optimize performance of AppViewX products. - 5+ years of experience as a performance test engineer. - Technically strong to do a deep-dive analysis into problem areas and contribute to redesigns that are faster, cleaner, and require less maintenance. Qualifications - Expertise in Load Testing, Stress, Endurance, availability, capacity and resilience testing. - Expertise in Jmeter/Loadrunner scripting and preparing performance test reports. - Experience with Kubernetes and microservices, log analysis. - Experience in Performance testing of SaaS applications in AWS with EKS. - Strong experience with commercial and open source code profiling tools (JProfiler, JVisualVM, JMC, etc.). - Thread / Heap Dump Analysis. - Mongo DB monitoring, profiling and query tuning by looking into query execution plans. - Good at Linux commands, OS monitoring commands and shell scripting. - Live monitoring tool expertise is preferred (Grafana, Influx DB, telegraf). - Understands system scalability concepts and develops methodologies to validate system capabilities. - Experience in application architecture and design techniques and familiarity with data modeling. Requirements - Good experience on working with auto scalable applications. - Should be able to analyze and propose right metrics to auto scale components in Kubernetes. - UI profiling with Fiddler and developer tools. - Experience working in an Agile development environment. - Hands on programming experience in Java or other common programming language. Benefits - Competitive incentives. - Health & wellness policies. - Saving & investment schemes. - Time off/sabbatical eligibility. - Dedicated L&D. - Flexibility to work remotely and define own hours.