Company Description Version 1 has celebrated 30 years in business and continues to be trusted by global brands to deliver technology and transformation solutions that drive customer success. Our deep expertise enables our customers to navigate the rapidly evolving technology landscape. We foster strong partnerships with global technology leaders including Microsoft, AWS, Oracle, Red Hat, OutSystems, Snowflake, ensuring that our customers are provided with the highest quality solutions and services. We’re an award-winning employer reflecting how our employees are at the very heart of what we do: - UK & Ireland's premier AWS, Microsoft & Oracle partner - 3300+ strong, €350/£300m revenue business - 10+ years as a Great Place to Work in Ireland & UK - Best Workplace for Women in the UK & Ireland by GPTW - Best Workplace for Wellbeing in the UK by GPTW We’re a core values driven company, we hire people who share our values, and we reward those who display and foster them, it’s deeply embedded within our DNA. Invest in us and we’ll invest in you. Job Description Role Overview As an AI Engineer focused on Generative and Agentic AI, you will design, build, deploy, and operate production-ready AI systems, taking ideas from early prototypes through to reliable, enterprise-grade solutions. You will work hands-on with real customer and internal use cases, owning the full lifecycle from design and orchestration to deployment, monitoring, and continuous improvement. The role emphasizes building intelligent systems that can reason, plan, use tools, and make decisions, rather than standalone models or simple chatbots. You will apply modern Generative AI techniques and strong software engineering practices to deliver real-world AI outcomes on a scale. Key Responsibilities - Experience needed 5-7 years - Generative & Agentic AI Development - · Design and build LLM-based systems using: - o Retrieval Augmented Generation (RAG) - o Embeddings and vector search - o Prompt engineering and prompt optimization - o Function calling and tool usage - o Agentic and multi-agent workflows - · Develop AI systems that integrate LLMs with REST APIs, enterprise systems, data platforms, and workflows - · Apply LLM evaluation techniques to assess quality, reliability, safety, and performance - End-to-End AI Engineering - · Own the full lifecycle of AI solutions—from prototype to production - · Build, deploy, and operate AI workloads in AWS environments - · Ensure production readiness with focus on scalability, reliability, performance, security, and cost optimization - · Implement CI/CD pipelines, automated testing, and versioning for AI systems - Engineering Excellence & Operations - · Apply strong software engineering and distributed systems principles to AI development - · Implement observability practices including logs, metrics, traces, and alerts - · Monitor model behavior, system health, latency, and failures in production - · Contribute to responsible AI practices, governance, and quality standards - Collaboration & Enablement - · Work closely with other AI engineers, data scientists, platform teams, and business stakeholders - · Contribute to building and scaling AI platforms and reusable components - · Support low-code / Copilot / Flow-style solutions where appropriate - · Share knowledge and mentor junior engineers on Generative and Agentic AI best practices Qualifications Mandatory Technical Skills - Programming & Engineering - · Python - · REST APIs - · CI/CD pipelines - · Automated testing - · Distributed systems fundamentals - Generative & Agentic AI - · Generative AI concepts - · LLM-based systems - · Agentic and multi-agent workflows - · Retrieval Augmented Generation (RAG) - · Embeddings and vector databases - · Prompt engineering - · LLM evaluation - Cloud & AI Platforms - · AWS Bedrock - · Amazon SageMaker - Production & Operations - · Observability (logs, metrics, tracing, alerts) - · Monitoring and performance tuning Nice to Have - · Experience supporting enterprise AI platforms or shared AI services - · Exposure to Copilot-style or workflow automation solutions - · Familiarity with Responsible AI principles and governance - · Experience working with cross-functional or client-facing teams Additional Information Why Version 1? At Version 1, we believe in providing our employees with a comprehensive benefits package that prioritises their wellbeing, professional growth, and financial stability. - Share in our success with our Quarterly Performance-Related Profit Share Scheme, where employees collectively benefit from a share of our company's profits - Strong Career Progression & mentorship coaching through our Strength in Balance & Leadership schemes with a dedicated quarterly Pathways Career Development programme - Flexible/remote working, Version 1 is tremendously understanding of life events and people’s individual circumstances and offer flexibility to help achieve a healthy work life balance - Financial Wellbeing initiatives including; Pension, Private Healthcare Cover, Life Assurance, Financial advice and an Employee Discount scheme - Employee Wellbeing schemes including Gym Discounts, Bike to Work, Fitness classes, Mindfulness Workshops, Employee Assistance Programme and much more. Generous holiday allowance, enhanced maternity/paternity leave, marriage/civil partnership leave and special leave policies - Educational assistance, incentivised certifications, and accreditations, including AWS, Microsoft, Oracle, and Red Hat - Reward schemes including Version 1’s Annual Excellence Awards & ‘Call-Out’ platform. - Environment, Social and Community First initiatives allow you to get involved in local fundraising and development opportunities as part of fostering our diversity, inclusion and belonging schemes. And many more exciting benefits… drop us a note to find out more. Version 1 is an equal opportunities employer. We are committed to building a diverse, inclusive and respectful workplace where everyone feels valued and able to thrive. We welcome applications from people of all backgrounds, identities and lived experiences, and we value the different perspectives people bring. We want every candidate to have a positive and accessible recruitment experience. If you need reasonable adjustments at any stage of the process, please contact [recruiter email address][EM1] at Version 1. We will consider all requests carefully, respectfully and confidentially. Video links: https://www.youtube.com/watch?v=F_d3ELTH5zo [EM1]Please add the email address for the lead recruiter - Department: Digital, Data and Cloud

Title: Lead AI/ML Engineer - Remote Location: Remote, United States Requisition number: 2350368 Job category: Technology Primary location: San Diego, CA Overtime status: Exempt Travel: No Job Description: Optum Insight is improving the flow of health data and information to create a more connected system. We remove friction and drive alignment between care providers and payers, and ultimately consumers. Our deep expertise in the industry and innovative technology empower us to help organizations reduce costs while improving risk management, quality and revenue growth. Ready to help us deliver results that improve lives? Join us to start Caring. Connecting. Growing together. Lead the autonomous medical coding enablement in a SaaS platform by integrating machine learning and LLMs. Working closely with data scientists and software engineers through data extraction, research, training, and deployment to create a scalable production solution that can handle millions of medical charts daily. You will be responsible for architecture decisions, code reviews, and coordinating across teams. You will work with cutting edge models, LLM, software, and tools in a fast paced environment. You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. Primary Responsibilities: - Lead end-to-end ML projects: problem definition, data strategy, feature engineering, modeling, evaluation, deployment, and monitoring - Architect scalable training and inference systems with strong SLAs, observability, and cost controls - Establish experimentation rigor: offline evaluation, A/B testing, guardrails, power analysis, and causal insights - Drive MLOps excellence: CI/CD for ML, reproducible pipelines, model registry and governance, automated retraining, drift/quality monitoring - Collaborate with product and design to translate ambiguous goals into measurable ML problems; define success metrics and attribution - Mentor and unblock engineers; conduct design and code reviews; set patterns for reliability, documentation, and testing - Partner with data engineering on feature pipelines, data contracts, and online/offline parity; champion data quality - Communicate tradeoffs and results to technical and non-technical stakeholders; influence roadmap and prioritization - Optional focus areas depending on interest and business needs: LLM applications (RAG, fine-tuning, evaluation/guardrails), recommendations/ranking, anomaly detection, forecasting You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in. Required Qualifications: - Bachelor of Science or higher in Computer Science, Engineering, Statistics, or related field, or 4+ years of equivalent practical experience - 7+ years building and operating ML systems in production with a track record of shipped impact - 5+ years experience in C# or Python - 5+ years experience in Azure - 5+ years experience in supervised learning, feature engineering, evaluation methodology, bias/variance; deep learning and/or gradient boosting - 5+ MLOps: CI/CD for ML, containers, Kubernetes/serverless inference, model registries, reproducibility, and model monitoring - 2+ years experience LLMOps: prompt engineering, retrieval-augmented generation, fine-tuning, evaluation, and safety/guardrails Preferred Qualifications: - Domain experience in recommendations/ranking, time-series forecasting, anomaly detection, optimization, or reinforcement learning - Privacy, security, and responsible AI practices (GDPR/CCPA, PII handling, fairness) - Open-source contributions, publications, or patents; prior experience mentoring or tech leading small teams - Excellent communication and product sense; able to scope ambiguous problems and align stakeholders - Open-source contributions, publications, or patents; prior experience mentoring or tech leading small teams - Data engineering for ML: ETL/ELT, SQL, distributed processing (e.g., Spark), and feature pipelines - Experimentation: A/B testing design/analysis, guardrail metrics, basic causal inference - All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $112,700 to $193,200 annually based on full-time employment. We comply with all minimum wage laws as applicable. At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission. UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations. UnitedHealth Group is a drug - free workplace. Candidates are required to pass a drug test before beginning employment. #OptumTechPJ

Title: Senior AI/ML Engineer - Remote Location: Minneapolis or Washington, D.C. San Diego, California Work Type:Remote, Hybrid, Full Time Job ID: 2350371 Job Description: Optum Insight is improving the flow of health data and information to create a more connected system. We remove friction and drive alignment between care providers and payers, and ultimately consumers. Our deep expertise in the industry and innovative technology empower us to help organizations reduce costs while improving risk management, quality and revenue growth. Ready to help us deliver results that improve lives? Join us to start Caring. Connecting. Growing together. This role will enable autonomous medical coding in a SaaS platform by integrating machine learning and LLMs. Working closely with data scientists and software engineers through data extraction, research, training, and deployment to create a scalable production solution that can handle millions of medical charts daily. You will work with cutting edge models, LLM, software, and tools in a fast-paced environment. You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week. Primary Responsibilities: - Ship production ML systems end-to-end: problem framing, data discovery, feature engineering, training, evaluation, deployment, monitoring, and iteration - Design robust ML system architectures with low-latency inference and high availability - Build and maintain reliable data and model pipelines using modern MLOps practices (CI/CD for ML, model registries, experiment tracking, automated retraining) - Contribute to technical scoping and break down complex initiatives into executable roadmaps; drive execution across cross-functional partners - Establish evaluation strategies: metrics, simulation, counterfactuals, and A/B tests; quantify impact and ensure statistical rigor - Implement model observability and governance: drift detection, performance monitoring, fairness/bias assessments, and model documentation - Collaborate closely with product, design, data, and platform teams to translate product goals into ML opportunities and measurable outcomes You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in. Required Qualifications: - Bachelor of Science or higher in Computer Science, Engineering, Statistics, or related field, or 4+ years of equivalent practical experience - 5+ years of industry experience building and operating ML systems in production (or equivalent depth), with a track record of shipped impact - 3+ years of experience in C# or Python - 3+ years of Azure experience - 3+ years of experience in supervised learning, feature engineering, evaluation methodology, bias/variance; deep learning and/or gradient boosting - 3+ years of MLOps expertise including CI/CD for ML, containers, Kubernetes/serverless inference, model registries, reproducibility, and model monitoring - 1+ years of experience with LLMOps including prompt engineering, retrieval-augmented generation, fine-tuning, evaluation, and safety/guardrails Preferred Qualifications: - Domain experience in recommendations, ranking, time-series forecasting, optimization, or reinforcement learning - Demonstrated excellent communication and product sense; able to translate business needs into technical plans and explain tradeoffs to non-ML stakeholders - Proven privacy, security, and responsible AI practices (GDPR/CCPA, PII handling, fairness) - Open-source contributions, publications, or patents experience - Proven solid ML/statistics fundamentals: supervised learning, evaluation methodology, feature engineering, bias/variance tradeoffs; deep learning or gradient boosting experience - MLOps expertise including CI/CD for ML, containers, Kubernetes, model registries, reproducibility, and model monitoring - All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $91,700 to $163,700 annually based on full-time employment. We comply with all minimum wage laws as applicable. Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants. At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

FNTIO sind AI-First Systems Engineers für Enterprise. Wir arbeiten seit 2022 produktiv mit AI in echten Kundenprojekten. Siemens, Deutsche Börse, Volkswagen. Wir liefern Projekte mit Ergebnisverantwortung. Kein Body Leasing, keine PowerPoints. Unsere Engineers denken in Architekturen und Entscheidungen. AI übernimmt die Ausführung. Wer bei uns arbeitet, ist Produktmanager seines eigenen AI-Teams: mit Claude Code, Cursor und den Tools, die wirklich funktionieren. Aufgaben 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 Qualifikation - 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 Wir freuen uns auf deine Bewerbung. Schick uns deinen CV und gerne ein kurzes Statement, warum du zu FNTIO passt. Wir melden uns.