Вакансии

Задачи: — проектировать и внедрять защиту в Azure: identity, сеть, нагрузки, данные; — писать Terraform/Bicep и применять контроли через Azure Policy, Entra ID, Key Vault; — строить и тюнить детекты в SIEM/SOAR по MITRE ATT&CK; — быть точкой эскалации по сложным инцидентам, вести управление уязвимостями; — менторить инженеров и аналитиков, участвовать в threat modelling. Требования: — 7+ лет опыта в cybersecurity, cloud или infrastructure security; — практика Azure security и Terraform; — экспертное знание SIEM, SOAR, EDR, IAM; — знание Python или PowerShell, профильное высшее образование; — будет плюсом сертификаты SC-100/SC-200, CCSP, CISSP и опыт в регулируемых отраслях. Условия: — гибридный формат работы с посещением офиса 1–2 раза в месяц. Локация: Killorglin, графство Керри, Ирландия.

Location: Cyprus; Finland; Ireland; Malta; Montenegro; Sweden What you'll be solving A platform engineer opens their AI client of choice, connects it to CAST AI, and types: "Why did our spend jump 40% in eu-west last week?" Thirty seconds later they have an answer, pulled from live cluster state and cost data, with links back to the evidence. No dashboards. No YAML archaeology. Just a question and a correct, permission-checked answer. Your job is to make that interaction boring. Reliably, securely, at production scale. Behind it sits the hard part: an AI assistant that reasons over thousands of production Kubernetes clusters, a platform that safely exposes company infrastructure to external AI clients, and quality pipelines that tell us when the agent is wrong before a customer does. Get it right, and operators stop clicking through consoles entirely. Get it wrong once, and an agent gives a confidently wrong answer to someone managing production. CAST AI already runs Kubernetes infrastructure autonomously. Our automation makes thousands of cost-and-reliability decisions a day. Cast Pilot is the team building the intelligence layer on top of that: AI assistants for Kubernetes and the cloud itself . Our assistant already answers thousands of questions a month from hundreds of organizations. Now we're opening the platform up: a public, permission-aware MCP server so customers can plug CAST AI straight into their own AI clients and agents, deeper connectivity across all three major clouds (AWS, GCP, Azure), and a continuous push to make our agents smarter, better grounded, and more capable. This is greenfield AI platform work on top of battle-tested infrastructure. Most features ship in 1 to 4 weeks. This is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Cyprus, Malta, Finland, Sweden, Ireland, Moldova, North Macedonia, Montenegro, Slovenia, and Ukraine. Requirements Strong software engineering fundamentals: you design clean abstractions, write maintainable code, and can justify your architecture choices, not just make something work. You're a generalist who is as comfortable debugging a distributed system as designing an auth flow or tuning an agent's behavior. Production experience with Go is strongly preferred; candidates without Go should demonstrate strong systems programming skills in a comparable language. Experience building or operating large-scale SaaS platforms in production: multi-tenant systems, high volumes, and the failure modes that only show up at scale. Solid understanding of Kubernetes. Our entire platform runs on it, and the assistants we build answer questions about it. You should be at home with autoscaling, scheduling, and networking concepts. You've personally driven a complex project end-to-end. Hands-on experience with AI coding agents and agentic development workflows. This is how we build, not just what we build. You've used observability tooling in production. CI/CD and DevOps practices experience. Strong English skills, both verbal and written. Startup mindset: adaptable, proactive, and comfortable with ambiguity. What will make you stand out You've built agentic systems that shipped : MCP servers or clients, agent gateways, tool-use orchestration, RAG pipelines, evaluation frameworks, and you can talk about what broke in production and how you found out. This is the single biggest differentiator for our team. Deep hands-on experience with one or more of AWS, GCP, or Azure, with real understanding of IAM, compute, networking, and their APIs, not just console-level usage. Experience with LLM application quality: evaluations, prompt engineering at scale, latency and cost optimization of agent loops. Knowledge of OAuth 2.0 / OIDC and multi-tenant authorization design. Deep knowledge of EKS, GKE, or AKS internals. Kubernetes or cloud-native OSS contributions. Responsibilities Design and build the systems behind our AI assistant: agent flows, context retrieval, and the data connections that let it reason about live Kubernetes infrastructure. Build and evolve our public, permission-aware MCP server : curated tools, identity, audit, and strict safety gates, so customers can use CAST AI from their own AI clients. Develop and maintain cloud connectivity across AWS, GCP, and Azure, and the data foundations our agents build on. Write production Go services that interact with cloud provider APIs, the Kubernetes control plane, and LLM APIs in real time. Own features end-to-end: from design through implementation, testing, and production rollout (most projects ship in 1 to 4 weeks). Debug novel problems: an agent giving a wrong answer, a cross-cloud permission edge case, a data freshness issue that only appears at scale. Build the quality harness: evals, telemetry, feedback loops, that let us ship agent improvements without regressions. Contribute to product direction and backlog. Shape what gets built next, not just how it's built. Participate in the team's on-call rotation. Tools We Use Daily Programming Languages: Go AI & Agents: MCP (servers and clients), agent gateways, LLM provider APIs, RAG, evaluation pipelines Cloud & Orchestration: Kubernetes, AWS, GCP, Azure Infrastructure as Code: Terraform Databases & Storage: PostgreSQL, Cloud Object Storage, ClickHouse Workflows & APIs: Temporal, GCP Pub/Sub, gRPC, REST Observability & Product Analytics: Prometheus, Grafana, Loki, Tempo, PostHog CI/CD & GitOps: GitLab/GitHub CI with ArgoCD and Kargo What's in it for you? Competitive salary (€6,500 to €9,000 gross, depending on the level of experience) Work on genuinely new problems: production MCP platforms and AI assistants for Kubernetes and cloud infrastructure are not solved domains. You'll be defining them, not following a playbook. Equity options. Real users, fast: your work ships to hundreds of organizations in weeks, not quarters. Enjoy a flexible, remote-first global environment. Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology. Spend 10% of your work time on personal projects or self-improvement. Learning budget for professional and personal development, including access to international conferences and courses. Annual hackathon to spark new ideas and strengthen team bonds. Team-building budget and company events to connect with your colleagues. Equipment budget to ensure you have everything you need. Extra days off to help maintain a healthy work-life balance. Hiring process Screening call with Recruiter Hiring Manager interview Technical interview (system design) Live coding Culture Check interview with an executive As part of our standard hiring process, a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr. Please note that Cast AI does not provide any form of visa sponsorship/work permit. #LI-Remote

Location: European Union What you'll be solving A platform engineer opens their AI client of choice, connects it to CAST AI, and types: "Why did our spend jump 40% in eu-west last week?" Thirty seconds later they have an answer, pulled from live cluster state and cost data, with links back to the evidence. No dashboards. No YAML archaeology. Just a question and a correct, permission-checked answer. Your job is to make that interaction boring. Reliably, securely, at production scale. Behind it sits the hard part: an AI assistant that reasons over thousands of production Kubernetes clusters, a platform that safely exposes company infrastructure to external AI clients, and quality pipelines that tell us when the agent is wrong before a customer does. Get it right, and operators stop clicking through consoles entirely. Get it wrong once, and an agent gives a confidently wrong answer to someone managing production. CAST AI already runs Kubernetes infrastructure autonomously. Our automation makes thousands of cost-and-reliability decisions a day. Cast Pilot is the team building the intelligence layer on top of that: AI assistants for Kubernetes and the cloud itself . Our assistant already answers thousands of questions a month from hundreds of organizations. Now we're opening the platform up: a public, permission-aware MCP server so customers can plug CAST AI straight into their own AI clients and agents, deeper connectivity across all three major clouds (AWS, GCP, Azure), and a continuous push to make our agents smarter, better grounded, and more capable. This is greenfield AI platform work on top of battle-tested infrastructure. Most features ship in 1 to 4 weeks. This is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Cyprus, Malta, Finland, Sweden, Ireland, Moldova, North Macedonia, Montenegro, Slovenia, and Ukraine. Requirements Strong software engineering fundamentals: you design clean abstractions, write maintainable code, and can justify your architecture choices, not just make something work. You're a generalist who is as comfortable debugging a distributed system as designing an auth flow or tuning an agent's behavior. Production experience with Go is strongly preferred; candidates without Go should demonstrate strong systems programming skills in a comparable language. Experience building or operating large-scale SaaS platforms in production: multi-tenant systems, high volumes, and the failure modes that only show up at scale. Solid understanding of Kubernetes. Our entire platform runs on it, and the assistants we build answer questions about it. You should be at home with autoscaling, scheduling, and networking concepts. You've personally driven a complex project end-to-end. Hands-on experience with AI coding agents and agentic development workflows. This is how we build, not just what we build. You've used observability tooling in production. CI/CD and DevOps practices experience. Strong English skills, both verbal and written. Startup mindset: adaptable, proactive, and comfortable with ambiguity. What will make you stand out You've built agentic systems that shipped : MCP servers or clients, agent gateways, tool-use orchestration, RAG pipelines, evaluation frameworks, and you can talk about what broke in production and how you found out. This is the single biggest differentiator for our team. Deep hands-on experience with one or more of AWS, GCP, or Azure, with real understanding of IAM, compute, networking, and their APIs, not just console-level usage. Experience with LLM application quality: evaluations, prompt engineering at scale, latency and cost optimization of agent loops. Knowledge of OAuth 2.0 / OIDC and multi-tenant authorization design. Deep knowledge of EKS, GKE, or AKS internals. Kubernetes or cloud-native OSS contributions. Responsibilities Design and build the systems behind our AI assistant: agent flows, context retrieval, and the data connections that let it reason about live Kubernetes infrastructure. Build and evolve our public, permission-aware MCP server : curated tools, identity, audit, and strict safety gates, so customers can use CAST AI from their own AI clients. Develop and maintain cloud connectivity across AWS, GCP, and Azure, and the data foundations our agents build on. Write production Go services that interact with cloud provider APIs, the Kubernetes control plane, and LLM APIs in real time. Own features end-to-end: from design through implementation, testing, and production rollout (most projects ship in 1 to 4 weeks). Debug novel problems: an agent giving a wrong answer, a cross-cloud permission edge case, a data freshness issue that only appears at scale. Build the quality harness: evals, telemetry, feedback loops, that let us ship agent improvements without regressions. Contribute to product direction and backlog. Shape what gets built next, not just how it's built. Participate in the team's on-call rotation. Tools We Use Daily Programming Languages: Go AI & Agents: MCP (servers and clients), agent gateways, LLM provider APIs, RAG, evaluation pipelines Cloud & Orchestration: Kubernetes, AWS, GCP, Azure Infrastructure as Code: Terraform Databases & Storage: PostgreSQL, Cloud Object Storage, ClickHouse Workflows & APIs: Temporal, GCP Pub/Sub, gRPC, REST Observability & Product Analytics: Prometheus, Grafana, Loki, Tempo, PostHog CI/CD & GitOps: GitLab/GitHub CI with ArgoCD and Kargo What's in it for you? Competitive salary (€6,500 to €9,000 gross, depending on the level of experience) Work on genuinely new problems: production MCP platforms and AI assistants for Kubernetes and cloud infrastructure are not solved domains. You'll be defining them, not following a playbook. Equity options. Real users, fast: your work ships to hundreds of organizations in weeks, not quarters. Enjoy a flexible, remote-first global environment. Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology. Spend 10% of your work time on personal projects or self-improvement. Learning budget for professional and personal development, including access to international conferences and courses. Annual hackathon to spark new ideas and strengthen team bonds. Team-building budget and company events to connect with your colleagues. Equipment budget to ensure you have everything you need. Extra days off to help maintain a healthy work-life balance. Hiring process Screening call with Recruiter Hiring Manager interview Technical interview (system design) Live coding Culture Check interview with an executive As part of our standard hiring process, a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr. Please note that Cast AI does not provide any form of visa sponsorship/work permit. #LI-Remote

Location: Estonia; Greece; Latvia; Lithuania; Poland; Slovakia; Ukraine What you'll be solving A platform engineer opens their AI client of choice, connects it to CAST AI, and types: "Why did our spend jump 40% in eu-west last week?" Thirty seconds later they have an answer, pulled from live cluster state and cost data, with links back to the evidence. No dashboards. No YAML archaeology. Just a question and a correct, permission-checked answer. Your job is to make that interaction boring. Reliably, securely, at production scale. Behind it sits the hard part: an AI assistant that reasons over thousands of production Kubernetes clusters, a platform that safely exposes company infrastructure to external AI clients, and quality pipelines that tell us when the agent is wrong before a customer does. Get it right, and operators stop clicking through consoles entirely. Get it wrong once, and an agent gives a confidently wrong answer to someone managing production. CAST AI already runs Kubernetes infrastructure autonomously. Our automation makes thousands of cost-and-reliability decisions a day. Cast Pilot is the team building the intelligence layer on top of that: AI assistants for Kubernetes and the cloud itself . Our assistant already answers thousands of questions a month from hundreds of organizations. Now we're opening the platform up: a public, permission-aware MCP server so customers can plug CAST AI straight into their own AI clients and agents, deeper connectivity across all three major clouds (AWS, GCP, Azure), and a continuous push to make our agents smarter, better grounded, and more capable. This is greenfield AI platform work on top of battle-tested infrastructure. Most features ship in 1 to 4 weeks. This is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Cyprus, Malta, Finland, Sweden, Ireland, Moldova, North Macedonia, Montenegro, Slovenia, and Ukraine. Requirements Strong software engineering fundamentals: you design clean abstractions, write maintainable code, and can justify your architecture choices, not just make something work. You're a generalist who is as comfortable debugging a distributed system as designing an auth flow or tuning an agent's behavior. Production experience with Go is strongly preferred; candidates without Go should demonstrate strong systems programming skills in a comparable language. Experience building or operating large-scale SaaS platforms in production: multi-tenant systems, high volumes, and the failure modes that only show up at scale. Solid understanding of Kubernetes. Our entire platform runs on it, and the assistants we build answer questions about it. You should be at home with autoscaling, scheduling, and networking concepts. You've personally driven a complex project end-to-end. Hands-on experience with AI coding agents and agentic development workflows. This is how we build, not just what we build. You've used observability tooling in production. CI/CD and DevOps practices experience. Strong English skills, both verbal and written. Startup mindset: adaptable, proactive, and comfortable with ambiguity. What will make you stand out You've built agentic systems that shipped : MCP servers or clients, agent gateways, tool-use orchestration, RAG pipelines, evaluation frameworks, and you can talk about what broke in production and how you found out. This is the single biggest differentiator for our team. Deep hands-on experience with one or more of AWS, GCP, or Azure, with real understanding of IAM, compute, networking, and their APIs, not just console-level usage. Experience with LLM application quality: evaluations, prompt engineering at scale, latency and cost optimization of agent loops. Knowledge of OAuth 2.0 / OIDC and multi-tenant authorization design. Deep knowledge of EKS, GKE, or AKS internals. Kubernetes or cloud-native OSS contributions. Responsibilities Design and build the systems behind our AI assistant: agent flows, context retrieval, and the data connections that let it reason about live Kubernetes infrastructure. Build and evolve our public, permission-aware MCP server : curated tools, identity, audit, and strict safety gates, so customers can use CAST AI from their own AI clients. Develop and maintain cloud connectivity across AWS, GCP, and Azure, and the data foundations our agents build on. Write production Go services that interact with cloud provider APIs, the Kubernetes control plane, and LLM APIs in real time. Own features end-to-end: from design through implementation, testing, and production rollout (most projects ship in 1 to 4 weeks). Debug novel problems: an agent giving a wrong answer, a cross-cloud permission edge case, a data freshness issue that only appears at scale. Build the quality harness: evals, telemetry, feedback loops, that let us ship agent improvements without regressions. Contribute to product direction and backlog. Shape what gets built next, not just how it's built. Participate in the team's on-call rotation. Tools We Use Daily Programming Languages: Go AI & Agents: MCP (servers and clients), agent gateways, LLM provider APIs, RAG, evaluation pipelines Cloud & Orchestration: Kubernetes, AWS, GCP, Azure Infrastructure as Code: Terraform Databases & Storage: PostgreSQL, Cloud Object Storage, ClickHouse Workflows & APIs: Temporal, GCP Pub/Sub, gRPC, REST Observability & Product Analytics: Prometheus, Grafana, Loki, Tempo, PostHog CI/CD & GitOps: GitLab/GitHub CI with ArgoCD and Kargo What's in it for you? Competitive salary (€6,500 to €9,000 gross, depending on the level of experience) Work on genuinely new problems: production MCP platforms and AI assistants for Kubernetes and cloud infrastructure are not solved domains. You'll be defining them, not following a playbook. Equity options. Real users, fast: your work ships to hundreds of organizations in weeks, not quarters. Enjoy a flexible, remote-first global environment. Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology. Spend 10% of your work time on personal projects or self-improvement. Learning budget for professional and personal development, including access to international conferences and courses. Annual hackathon to spark new ideas and strengthen team bonds. Team-building budget and company events to connect with your colleagues. Equipment budget to ensure you have everything you need. Extra days off to help maintain a healthy work-life balance. Hiring process Screening call with Recruiter Hiring Manager interview Technical interview (system design) Live coding Culture Check interview with an executive As part of our standard hiring process, a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr. Please note that Cast AI does not provide any form of visa sponsorship/work permit. #LI-Remote

Location: Romania Job Overview React and Next.js | 4 to 6 years This role is responsible for building reliable, responsive user interfaces from approved designs and API contracts. The developer should be able to deliver features independently, diagnose browser issues and contribute maintainable, well-tested code. Must Have Skills • Strong experience with React, Next.js, TypeScript and hooks-based component development. • Good understanding of component lifecycle, effects, memoisation and techniques for preventing unnecessary re-renders. • Experience with Next.js, Vite or a comparable modern front-end build framework. • Experience with Zustand, Redux Toolkit or a similar state-management library, including correct and efficient use of selectors. • Strong HTML5, CSS3 and SCSS skills, including responsive layouts, semantic markup and scoped styling. • Working knowledge of accessibility fundamentals, including keyboard navigation, focus management and appropriate ARIA usage. • Experience using a design system such as IBM Carbon, Material UI or an equivalent component library. • Ability to implement interfaces accurately from Figma designs or other visual specifications. • Experience integrating REST APIs and handling loading, error, empty and partial-data states. • Experience with polling, request cleanup and defensive handling of incomplete or unexpected API responses. • Working knowledge of environment configuration, package management and front-end build processes. • Experience writing unit and component tests with Vitest or Jest and React Testing Library. • Strong browser DevTools debugging skills and experience resolving cross-browser issues. • Working knowledge of Git branching, pull requests, code reviews and collaborative delivery workflows. • Ability to write clean, reusable and maintainable front-end code. • Good knowledge of secure client-side development, including environment variables and safe logging. Good to Have Skills • Experience with animation libraries such as GSAP, Framer Motion or React Spring. • Experience with charting libraries such as Recharts, Chart.js, D3.js or High charts. • Hands-on experience with three.js, React Three Fiber, WebGL or the HTML Canvas API. • Familiarity with performance profiling, bundle analysis, lazy loading and dynamic imports. • Experience with internationalization libraries such as react-i18next or next-intl. • Experience with end-to-end testing tools such as Playwright • Familiarity with error boundaries, front-end monitoring and CI/CD pipelines. • Familiarity with Azure DevOps • Experience working in an Agile team using Jira and Confluence.

Location: Egypt ABOUT THE ROLE Cincom is bringing Level 1 support, hosting support and infrastructure together into one 24/7 Service Operations function, reporting directly to the COO. It covers all of our main product lines, including CPQ, Eloquence, Cincom Smalltalk, Mantis, Supra and Control, along with the customer environments we host and manage and the infrastructure they run on. Today, these areas work differently from one product to the next. Processes, tools and standards vary in many cases, and too much depends on a few people who know a product or a platform inside out. We want one modern, professional operation that runs around the clock and that customers experience the same way, whichever product they use and wherever/however it is deployed. We are looking for someone to build this team and lead it. You will set the operating model, lead the three teams, own escalations through to resolution, and put the tooling, processes and measures in place to run Service Operations as a true 24/7 managed service. You will sit on the COO’s leadership team and take on wider operational responsibility as the function matures. It is a senior leadership role, but you will need to stay close enough to the work to know what good looks like and to step in when it counts. WHY THIS ROLE This is a new function with a direct line to the COO. You will shape it from the start, with real backing to change how we work and a clear mandate to build a professional service that customers value. It is also a role with room to grow: as the function matures, we expect you to take on wider operational responsibility across the business. The role is remote and the location is open. Because Service Operations runs 24/7, you will take part in senior escalation cover for major incidents, and potentially travel occasionally to meet the team and customers. KEY RESPONSIBILITIES Team Leadership & People Management Lead the three teams that report to you, specifically, Level 1 Support, Hosting Support and Infrastructure Management, and build and retain Level 2 knowledge over time. Build out the Level 1 team, starting with a new team being established, and make sure it works hand in hand with our existing product support specialists in the Cincom business. Hire, develop and coach the team, and cross-skill people across products and platforms so we are not reliant on any one person. Set clear objectives, give regular feedback, and build a team that takes ownership of the customer’s problem. Operational Leadership Sit on the COO’s leadership team and contribute to decisions across engineering, delivery and operations. Deputise for the COO on operational matters when needed, and take on wider operational responsibility as the function matures. Own the Service Operations budget, including hosting and infrastructure costs, and help deliver against the business’s cost and efficiency targets. Manage key operational suppliers and contracts, working with the COO and PartnerOne Group procurement and IT where Group agreements apply. Building a 24/7 Service Operations Function Design and run Service Operations as a true 24/7 service, with coverage, rotas and on-call arrangements that match our customer commitments. Build out-of-hours models that make good use of the team, without burning people out. Replace product-by-product ways of working with one consistent model for intake, triage, severity and prioritisation. Bring in modern support practice, including ITIL-aligned incident, problem and change management and knowledge-centred support. Build a proper Managed Services approach for our hosted platforms, working across the Hosting Support and Infrastructure teams and with the Client Success Team for our key accounts. Escalation Management to Level 2 and 3 Own the escalation process from Level 1 into Level 2/3: product engineering teams for product issues, and Services consultants for issues in project deliverables, where necessary. Set clear criteria for when and how issues escalate, so they arrive with the right information, and nothing gets lost in the handover. Track every escalated issue through to resolution, keep customers informed, chase when timescales slip. Review escalation trends with the product heads, push recurring issues back for permanent fixes and inclusion in roadmaps and make sure what we learn is captured in the smart knowledge base. Hosting Support Hold overall accountability for the customer environments Cincom hosts and manages, delivered through the Hosting Support team, and stay engaged with customer hosted deployments and associated metrics. Make sure hosted services meet their commitments on availability, monitoring, backups, patching, disaster recovery and incident response, around the clock, providing a true Managed Service. Turn hosting into a consistent, repeatable managed service that our commercial team can understand and sell with confidence. Infrastructure Lead the Infrastructure team and own the hardware and deployment design for hosted and on-premise customer environments. Software design stays with the product engineering teams. Set infrastructure standards and reference architectures for each product, covering capacity, resilience, security and cost. Plan capacity and sizing with the product and project delivery teams, so customer environments are built right first time. Keep our cloud and infrastructure estate, including Azure and Kubernetes, secure, patched, documented and cost-effective. Tooling, Automation & AI Make Zoho Desk the single platform for support, configured properly and used consistently across every product, with integrations into other Cincom operational platforms as required. Build and maintain a knowledge base (working with Cincom designated AI tools) that customers and the team actually use and expand self-service and automation where it saves everyone effort. Work with our AI team to explore and develop AI-assisted Level 1 support, including local-language support, with validation before answers reach customers. Performance, Reporting & Compliance Set and track SLAs and internal service levels for response and resolution, by severity. Report on ticket trends by product, customer, region, severity and SLA tracked resolution time, alongside hosting availability and infrastructure cost, not just ticket status, and review them monthly with the COO. Lead the response to major incidents, with clear and timely communication to customers following a well-documented process. Make sure support, hosting and infrastructure processes provide the evidence we need for ISO 27001 and SOC 2, and support our obligations to customers in regulated sectors. Requirements WHAT WE'RE LOOKING FOR Essential Experience Experience leading support, hosting or infrastructure operations for enterprise software customers, ideally across more than one product. Experience leading several teams through team leads, at senior management level. A track record of building or reshaping a support or operations function, not only running an existing one. Experience running or building a 24/7 support operation, including on-call and potential follow-the-sun models. Experience managing escalations into engineering teams and holding them to agreed timescales. Experience running SLA-based support for business-critical customer systems. Experience owning an operational budget, including hosting and infrastructure costs. Technical Knowledge Strong grounding in incident, problem and change management (ITIL or equivalent). Solid understanding of hosted and cloud infrastructure, Azure or similar, including monitoring and alerting, high availability, backup and disaster recovery, and management of guaranteed up-time. Familiarity with containerised deployments such as Kubernetes, and with infrastructure-as-code. Comfortable with service desk platforms, reporting and automation. Leadership & Interpersonal Skills Calm and clear with customers and senior colleagues, especially when things go wrong. Uses data to manage performance and to make the case for change. Builds trust across Engineering, Delivery and Client Success, and gets things done without relying on authority. Thinks beyond their own function, and is comfortable representing operations at leadership and Group level. Fluent Business English communication. Desirable Hands-on experience with Zoho Desk or a comparable service desk platform. Experience introducing AI-assisted support, knowledge-centred support or self-service. ITIL 4 certification. Additional languages, particularly French, German, Italian. Experience supporting customers in regulated sectors such as financial services and insurance, and familiarity with ISO 27001 and SOC 2. Experience with cloud cost management or FinOps practices. Benefits Independent Contractor (Contractor is responsible for applicable taxes and statutory obligations, subject to the agreement and local law) Full-time role Availability for occasional short travels Payment in USD Equipment provided by the company Contractor fee range - $3,900–$6,000 USD per month Equal Opportunity Employer PartnerOne is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected characteristic. AI Use Disclosure During our recruitment process, we may use technology, including AI-assisted tools, to support application review or scheduling. These tools support our recruiting team and do not replace human decision-making. Where required, candidates will receive additional information about the tool and applicable rights. This job posting is for an existing vacancy.

Location: Remote - Americas Who We Are: Alpaca is a US-headquartered, global leader in agent-first brokerage infrastructure for stocks, ETFs, options, crypto, fixed income, 24/5 trading, and more. Amongst our subsidiaries, Alpaca is a licensed financial services company, serving hundreds of financial institutions across 40 countries with our institutional-grade APIs. This includes broker-dealers, investment advisors, wealth managers, hedge funds, and crypto exchanges, totalling over 10 million brokerage accounts. Our global team is a diverse group of experienced engineers, traders, and brokerage professionals who are working to achieve our mission of opening financial services to everyone on the planet. We're deeply committed to open-source contributions and fostering a vibrant community, continuously enhancing our award-winning, developer-friendly API and the robust infrastructure behind it. Alpaca is proudly backed by $400 million in funding from top-tier global investors including Portage Ventures, Spark Capital, Tribe Capital, Social Leverage, Horizons Ventures, Opera Tech Ventures, SBI Group, Derayah Financial, Unbound, Peak XV, Elefund, and Y Combinator. Our Team Members: We're a dynamic team of 400+ globally distributed members who thrive working from our favorite places around the world, with teammates spanning the USA, Canada, Japan, Hungary, Nigeria, Brazil, the UK, and beyond! We're searching for passionate individuals eager to contribute to Alpaca's rapid growth. If you align with our core values—Stay Curious, Have Empathy, and Be Accountable—and are ready to make a significant impact, we encourage you to apply. Your Role: We are seeking an IT Security Engineer to own the security standards and controls that protect Alpaca’s workforce identities, endpoints, and critical business systems. The scope includes identity and access management, single sign-on, privileged access, multi-factor authentication, endpoint security, secure network access, and email security. You will maintain those standards, measure how the controls are working, and partner with IT, who run devices and day-to-day administration. This role reports to the Enterprise Security Architect and works closely with IT, DevOps, Engineering, GRC, and the wider Security team. The Security Team is 100% distributed and remote. Things You Get To Do: The core responsibilities of the IT Security Engineer are focused on identity security, endpoint security, email and domain protection, and measurable control enforcement. Identity and Access Security: IAM and SSO Standards: Define and maintain security standards for SSO and conditional access across cloud, SaaS, and internal systems. Multi-Factor Authentication: Own multi-factor authentication standards, including phishing-resistant methods, and keep them enforced. Privileged Access: Maintain privileged-access standards, approval policies, and periodic access reviews with system owners. Joiner, Mover, Leaver: Partner with IT and People teams so access changes are timely, complete, and auditable. Endpoint, Email, and Domain Security: EDR Policy: Own endpoint detection and response policy and tuning, with IT handling deployment. Device Posture: Maintain device-posture and secure network access requirements for access to business applications. Control Measurement: Measure identity and endpoint controls and follow up where they are not met. Detection Partnership: Work with Security Operations on identity, endpoint, and email detections and response playbooks. Admin Access: Maintain security baselines for administrator access to critical SaaS platforms and vendor accounts. Vendor Security Events: Assess the identity and account impact when a SaaS provider or vendor reports a security event. Email Security: Own email authentication standards and email security configuration. Domain Protection: Maintain security standards for company domains and for monitoring lookalike domains. Phishing Response: Triage reported phishing and coordinate takedowns. Incident Response and Collaboration: Incident Support: Lead the identity, endpoint, and email aspects of security incidents, including account containment. On-Call: Participate in the Security Operations on-call rotation after onboarding and cross-training. Enablement: Give IT and employees clear guidance on security requirements, so controls are adopted without slowing the business. Who You Are (Must-Haves): Excited about Alpaca’s mission and what we’re building 3+ years of experience in IT security, identity security, or security engineering roles Hands-on experience with an identity provider and SSO, including SAML and OIDC Experience enforcing phishing-resistant MFA, such as FIDO2 or hardware security keys Hands-on experience with an endpoint detection and response platform Scripting or automation experience (Python, Bash, or PowerShell) Experience with zero-trust network access or device-posture controls Working knowledge of email authentication (SPF, DKIM, DMARC) and phishing response Experience working closely with IT teams and translating security requirements into operational workflows Experience investigating identity, endpoint, or email security alerts Willing to participate in an on-call rotation Strong written and verbal communication skills, especially during incidents Comfortable working cross-functionally and handling escalations calmly and decisively Who You Might Be ( Nice-to-Haves): Experience securing financial, trading, or other highly regulated platforms Familiarity with compliance frameworks such as SOC 2 or ISO 27001 Experience with just-in-time privileged access tools Experience securing administrator access to SaaS platforms Experience with password managers and secrets management at company scale Experience with MDM platforms for macOS and Windows Experience with cloud IAM in AWS, GCP, or Azure Ability to balance security rigor with operational efficiency and business needs How We Take Care of You: Competitive Salary & Stock Options Health Benefits New Hire Home-Office Setup: One-time USD $500 Monthly Stipend: USD $150 per month via a Brex Card Alpaca is proud to be an equal opportunity workplace dedicated to pursuing and hiring a diverse workforce. 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Location: Intellias Meet your recruiter Stephen Palmer stephen.palmer@intellias.com https://www.linkedin.com... Vacancy details Management Manager Director Bulgaria, Croatia, Poland, Portugal, Spain, United Kingdom Remote APPLY NOW REFER A FRIEND Over 20 years of market experience, Intellias brings together technologists, creators and innovators in Europe, North and Latin America, and the Middle East. Join our international team and take the mission to solve the advanced tech challenges of tomorrow! What project we have for you We are building a market-leading AI Solutions practice and are looking for a senior leader to anchor it across Europe. This is a hands-on leadership role at the intersection of technical depth, client advisory, and commercial growth. You will work with business segments and co-own AI outcomes end to end — from shaping opportunities and advising client executives, through architecting and delivering production-grade solutions, to building the team and offerings that let us scale. This is not a pure management role and not a pure architect role. The right person can sit with a client CTO in the morning to frame a transformation roadmap, dive into a model architecture or agent design review in the afternoon, and shape the next quarter’s offering and pipeline in between. You will be a founding pillar of how we take AI from pilot to production at enterprise scale. What you will do Client Advisory & Pre-Sales Act as the senior AI advisor and trusted partner to enterprise clients, translating business problems into pragmatic, value-driven AI strategies and roadmaps. Lead pre-sales and solutioning: shape opportunities, scope and estimate engagements, run discovery and design workshops, and present to senior and C-level stakeholders. Drive proposal and RFP responses, solution narratives, and commercial framing that differentiate us in competitive situations. Identify and grow account opportunities, partnering with business development to convert advisory engagements into delivery programs. Offering & Practice Development Define and productize repeatable AI offerings, accelerators, and reusable assets that shorten time-to-value and improve delivery margins. Establish reference architectures, delivery playbooks, and engineering standards for ML, GenAI, and agentic solutions. Contribute to AI practice strategy and external thought leadership (points of view, frameworks, speaking, content). Delivery Leadership Support end-to-end delivery of AI programs — from PoC and pilot through to hardened production — ensuring solutions actually ship and operate, not just demonstrate. Drive production readiness across the lifecycle: MLOps/LLMOps, evaluation, monitoring, cost management, security, and AI governance. Manage program economics, scope, risk, quality, and stakeholder alignment across distributed delivery teams. Technical Leadership Provide hands-on technical direction across machine learning, deep learning, and GenAI/agentic systems, with the credibility to lead architecture and design reviews. Make and defend platform and architecture decisions across hyperscaler and data ecosystems (AWS, Azure, GCP, Databricks, Salesforce etc.). Set technical standards and uphold engineering quality, mentoring senior technical staff. Team Building & Leadership Recruit, build, and grow a high-performing AI delivery organization in Europe across data science, ML/AI engineering, and solution architecture. Manage, coach, and develop senior practitioners; foster a culture of capability growth, certification, and continuous learning. Operate effectively within a collaborative leadership model alongside business development and technology peers. What you need for this 12+ years in technology, data, or engineering, with strong hands-on background in AI / ML / data science, including genuine hands-on practice (not solely oversight). Demonstrable hands-on expertise in machine learning and deep learning— model development and experimentation with frameworks such as PyTorch or TensorFlow, and a working command of modern ML/DL techniques. Proven track record delivering AI/ML solutions into production at enterprise scale — you have shipped systems that operate reliably in the real world. Production experience on at least one major hyperscaler or data platform(AWS, Azure, GCP, or Databricks); multi-platform fluency is a strong advantage. Hands-on production experience with GenAI and agentic systems — LLMs, RAG, orchestration and agent frameworks, tool/function calling, and evaluation of non-deterministic systems. Experience leading both internally and externally — line-managing internal teams and owning external client programs as a delivery lead, engagement lead, or equivalent accountable role. Executive-grade client presence — able to advise, influence, and build credibility with senior business and technology stakeholders. Nice to Have: Prior consulting or IT/professional-services experience — pre-sales, offering development, and accountability for running AI projects and programs (including revenue or margin contribution). Experience building or scaling an AI / data practice or capability from an early stage. Deep domain expertise in one or more priority verticals — e.g., retail, automotive & mobility, financial services, healthcare / medtech & life sciences, or telecom — sufficient to speak the client’s language and frame value, not just technology. Familiarity with EU AI Act, GDPR, and responsible-AI / governance frameworks as applied to enterprise deployments. Relevant certifications (AWS / Azure / GCP ML or AI, Databricks). Advanced degree (MSc or PhD) in Computer Science, Data Science, Machine Learning, Engineering, or a related field. Experience operating within nearshore / distributed delivery models. Additional European languages. What Success Looks Like (First 6–12 Months) Established credibility with key clients and internal stakeholders as the go-to senior AI leader for one or more business segments. Shaped and helped win AI engagements, with a measurable contribution to pipeline and bookings. Stood up or sharpened a set of productized AI offerings and accelerators that the team can sell and deliver repeatably. Promoted delivery and engineering standards and begun building a growing, high-quality AI team with measurable impact Delivered (or put firmly on track) at least one flagship AI program running in client production. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success.

• Lead the definition and evolution of the enterprise data platform strategy by developing, maintaining, and continuously evolving architecture standards, reference architectures, and design patterns aligned with business priorities, analytical requirements, and AI/ML enablement across data and ETL/ELT platforms.

Partner with product owners, product managers, business stakeholders, and SMEs to elicit, analyze, validate, and document functional and non-functional needs, business rules, product requirements, and acceptance criteria.

Design, develop, and maintain GIS software applications and geospatial solutions. Build interactive mapping applications and location-based services.

Location: Intellias Meet your recruiter Dariia Ulianova dariia.ulianova@intellias.com https://www.linkedin.com... Vacancy details Business Analysis Business Analyst Senior Business Analyst Bulgaria, Croatia, Poland, Portugal, Spain, Ukraine, United Kingdom Remote APPLY NOW REFER A FRIEND We are hiring a Business Analyst to join an Intellias delivery team on a large-scale enterprise data platform migration programme for a financial services client. You will bridge the client’s domain owners and stewards on one side and the delivery engineers on the other, and you will own the backlog in Azure DevOps. What project we have for you Our client is an independent, active global asset manager with over R3 trillion in assets under management. They are executing a firm-wide data strategy to govern, manage and engineer data as a product across more than 70 business-owned sub-domains. As part of this, they are migrating to Databricks as the foundational layer of their Enterprise Data Platform, adopting a lakehouse architecture built on open formats, declarative pipelines and Unity Catalog. What you will do Data Modelling Run data modelling workshops with business SMEs, domain owners, analysts. Design conceptual and logical data models across multiple business domains, working from business definitions as well as from existing data structures in mastering systems. Model business complexity appropriately: e.g. class hierarchies, inheritance, controlled vocabularies, reusable patterns, shared data domains, business rules, and define where cross-domain references exist. Present models back to stakeholders for review, information-sharing, and agreement Ensure every model element traces back to a business term from data governance, and that the trace survives all the way to the delivered column. Help to resolve conflicts or missing inputs/outputs where they exist Review other domain data models from the modelling team. We envisage a small team of modellers who contribute to the federated data model as a whole. Standards and federation Contribute to and enforce the modelling standards that make federated delivery safe: naming conventions, data type standards, model layering rules, and the conventions that prevent domains colliding as the model grows Define reusable enterprise-level structures — shared types, reusable/common patterns, balancing core versus domain-local Delivery and automation Work in Git and GitHub as your primary environment: branches, pull requests, code review, releases Review model changes raised by others — including, ultimately, any changes drafted by AI agents — and apply the judgement that automated checks cannot Version models, assess the impact of breaking changes on downstream consumers in order for migration planning Contribute to the automated checks that enforce standards in CI, in collaboration with engineering Have input into the logical-to-physical mapping — deciding and documenting where a normalised structure can/should be denormalised for query performance or analytics (e.g. a data product), an define agreed and named patterns for these transformations rather than ad-hoc judgement so they can be automated. What you need for this Key Responsibilities Substantial data modelling experience, with a track record of conceptual, logical modelling that powered physical models that went into production, consumed, iterated upon & versioned accordingly. You must be competent in the principles of abstraction, inheritance, normalisation. Experience with dimensional/denormalization techniques. Demonstrable domain knowledge in asset/investment management, or a closely related financial services area — sufficient to hold a credible conversation with a SME, e.g. a portfolio manager, a fund accountant or a risk analyst about what their data actually means. We are building out domain by domain. You would be expected to develop working depth across more than one area. We expect some in depth asset management knowledge in at least 3 of these areas: Instrument/Security reference, Index & Benchmarks, Party, Counterparty/ Client, Portfolio, Holdings & Valuations, Execution, Trade Life cycle, Performance & Attribution, ESG/sustainability, Fund Accounting, Sales & Marketing Working fluency with Git and GitHub: branching, pull requests, resolving conflicts, reviewing others’ changes. You do not need to be a software engineer, but you must be comfortable that your model lives in a repository and moves through code review. Comfort authoring in YAML, and working with JSON data – plus the willingness to learn a schema language – prior exposure is welcome but not expected. Experience establishing or working to modelling standards — naming conventions, data dictionaries, glossaries, and the ability to add/enhance those standards as part of the platform maturation and greater automation. Soft Skills: The ability to run a workshop with business stakeholders and leave with clarity, and not a list of open questions. Precision with language. Dealing with ambiguity. Much of this role is writing definitions that all stakeholders can agree on. Nice to have: Databricks, Delta Lake or a comparable Lakehouse platform Data contracts, particularly ODCS, or equivalent interface-versioning practice CI/CD concepts Experience of developing/using agentic workflows for delivering model artefacts Experience of a federated or data mesh operating model, and its failure modes Traditional modelling tools such as Erwin, ER/Studio is useful, for reference, however our way of working will be different. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success. Skills Fintech

Location: Intellias Meet your recruiter Olha Yakuba olha.yakuba@intellias.com https://www.linkedin.com... Vacancy details Data Engineering Data Architect Architect Bulgaria, Croatia, Poland, Portugal, Spain, Ukraine, United Kingdom Remote APPLY NOW REFER A FRIEND Let’s breathe life into great tech ideas! With 3,000 people globally, Intellias is a company where benchmark technological solutions are born. Join in and take your part in digitalizing the world. What project we have for you The client is a US-headquartered engineering, architecture, construction and commissioning firm delivering complex facilities for the life sciences and advanced technology sectors. Its knowledge lives across SharePoint, CRM, project management, cost and document systems, and the client is investing in data and AI to put that knowledge to work. Intellias is the client’s data and AI delivery partner. The engagement covers several streams that run in parallel or follow one another: Data platform: a governed Microsoft Fabric lakehouse that consolidates project, commercial and document data into one trusted source. Knowledge and document AI: extraction, search and cited generation over large archives of proposals, specifications, drawings and project records. AI agents and workflow automation: assistants embedded in pre-construction, proposal, delivery and innovation processes, including idea intake, triage and approval flows. Governance and enablement: AI governance, security, environment set-up, including isolated or offline deployments, and capability building for client teams. What you will do Own the account’s target data and AI architecture, keep every initiative aligned to it, and maintain the architecture documents and decision records. Design lakehouse data models (medallion, Delta) with clear lineage, data quality rules and reusable data products. Plan environments, capacity and the path from pilot to production. Design integrations with enterprise systems such as Microsoft 365/SharePoint, CRM, ERP, finance and project systems, plus entity resolution to link clients, projects and documents. Build document intelligence pipelines that use OCR, classification and LLM-based extraction. Architect RAG solutions and AI agents on Azure AI Foundry and Power Platform, with grounded answers, tool use and human-in-the-loop steps. Set up evaluation frameworks with golden datasets, and use them to gate model and prompt changes. Design security and governance: Entra ID/RBAC, document-level access, Purview, audit logging, monitoring and cost controls, plus isolated deployments where required. Act as the client’s trusted technical advisor: run workshops and present trade-offs, cost and risk clearly. Support new client initiatives with estimates, RFP responses, demos, proposals and proofs of concept Mentor data and AI engineers through design reviews, code reviews and prototyping, and help grow the client’s in-house capability. What you need for this Tech stack: Microsoft Fabric / OneLake, Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure AI Document Intelligence, Power Platform and Dataverse, Microsoft Purview, Entra ID, Key Vault, Azure Monitor; integrations with SharePoint (Graph API), Salesforce and Procore. Requirements 8+ years in data engineering or data platforms, including 3+ years as a solution or data architect leading end-to-end designs for enterprise clients. 3+ years of Azure experience (Microsoft Fabric / OneLake, Azure AI Foundry and Azure OpenAI, Azure AI Search etc.) including security and governance (Entra ID, RBAC, Key Vault, private networking). Proven delivery of production data platforms (medallion patterns), experience in data modelling with lineage and provenance, data quality, entity resolution and master data. Delivered at least one generative AI solution (RAG, document AI or agents) beyond the prototype stage. Strong hands-on Python and SQL; working knowledge of PySpark. Ability to explain architecture and AI limits to non-technical business stakeholders, and to defend decisions with trade-offs, cost and risk. Comfortable working across several initiatives at once and switching between strategy and hands-on detail. English at B2+ (Upper-Intermediate) or higher for daily work with US stakeholders. Nice to have Experience in the AEC (architecture, engineering, construction) or life sciences domain: pre-construction, estimating, proposals, commissioning and qualification. Exposure to Procore, Salesforce, Cosential or similar construction and professional-services systems. Power BI / Microsoft Purview / Power Platform / Copilot Studio. Agentic frameworks (Semantic Kernel, LangGraph, Azure AI Foundry Agent Service), Model Context Protocol and LLM evaluation tooling. Infrastructure as code (Bicep or Terraform) and CI/CD for Fabric and Azure (Azure DevOps or GitHub Actions). Azure / Fabric certifications. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success.

Location: Intellias Meet your recruiter Olha Huk olha.huk@intellias.com https://www.linkedin.com... Vacancy details AI/ML Engineering GenAI Engineer Senior Romania Hybrid APPLY NOW REFER A FRIEND Intellias helps retailers deliver consistent, omnichannel experiences through technology. Join us to develop scalable solutions that drive performance and customer value What project we have for you We are looking for a hands-on Senior AI Engineer to lead the technical design and delivery of enterprise AI agents and MCP-based integrations. The team will develop Model Context Protocol (MCP) services for local business applications and build AI agents that consume both these local MCPs and MCP services provided by a global platform team. The Senior AI Engineer will own solution design, support use-case discovery, provide technical leadership to the engineering team, and participate directly in implementation. What you will do Lead technical discovery and translate business use cases into AI/agentic solution designs. Design the architecture of AI agents and their interaction with local and global MCP services. Design and develop MCP services exposing capabilities of local applications to AI agents. Build enterprise AI agents and agentic workflows. Integrate agents with multiple MCP servers, APIs and enterprise systems. Define agent instructions, reasoning flows, tool-selection logic, approval workflows and human-in-the-loop guardrails. Define reusable patterns and engineering standards for MCP and agent development. Lead and support other AI engineers during implementation. Ensure compliance with enterprise security, architecture and AI governance requirements. Define and monitor agent quality and performance metrics, including task completion, tool failures, hallucinations, latency and cost. Collaborate with global AI/platform teams to ensure interoperability between local and global MCP capabilities. What you need for this Required skills Strong hands-on Python engineering experience. Experience building LLM-based applications, AI agents or agentic workflows . Strong knowledge of REST APIs and enterprise integrations. Strong Microsoft Azure experience. Experience with authentication/authorization such as OAuth 2.0 and Microsoft Entra ID. Understanding of tool/function calling and agent-to-system integration patterns. SQL, JSON, Git and CI/CD. Ability to design production-grade solutions and provide technical leadership. Strong English communication skills. Strong advantage Hands-on Model Context Protocol (MCP) experience. Azure AI Foundry / Azure OpenAI. Copilot Studio. Power Automate. Agent orchestration frameworks such as Semantic Kernel, LangGraph or similar. Azure Functions / API Management / Logic Apps. Experience with enterprise AI governance, evaluation and observability. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success.

We are looking for an experienced Senior / Lead DevOps Engineer to own, scale, and evolve our cloud infrastructure at Qtech!

Location: Intellias Meet your recruiter Yustyna Vozna yustyna.vozna@intellias.com https://www.linkedin.com... Vacancy details Business Analysis Business Analyst Senior Business Analyst Bulgaria, Croatia, Poland, Portugal, Spain, Ukraine, United Kingdom Remote APPLY NOW REFER A FRIEND We are hiring a Business Analyst to join an Intellias delivery team on a large-scale enterprise data platform migration programme for a financial services client. You will bridge the client’s domain owners and stewards on one side and the delivery engineers on the other, and you will own the backlog in Azure DevOps. What project we have for you Our client is an independent, active global asset manager with over R3 trillion in assets under management. They are executing a firm-wide data strategy to govern, manage and engineer data as a product across more than 70 business-owned sub-domains. As part of this, they are migrating to Databricks as the foundational layer of their Enterprise Data Platform, adopting a lakehouse architecture built on open formats, declarative pipelines and Unity Catalog. What you will do Elicit requirements from domain owners and stewards and turn them into engineer-ready specifications with source-to-target mappings, semantic definitions and DQ expectations. Define data contracts and agree acceptance criteria for each migrated domain. Maintain the programme backlog in Azure DevOps against the client’s ways of working. Track cross-domain dependencies and surface them to the Delivery Manager and Programme Steering. Own the domain migration readiness checklist (steward committed, source contracts documented, consumption use cases agreed) before a domain enters build. Contribute to documentation living alongside the code. What you need for this Financial services background, ideally asset management, banking or capital markets. Knowledge of at least one asset class, ideally fixed income. Familiarity with investment management data (positions, transactions, portfolio, performance, security master, reference data). 5+ years of business analysis on data or platform programmes. Strong experience of Azure DevOps for backlog management, sprint planning and reporting. Comfort with data engineering vocabulary: schemas, contracts, lineage, DQ, medallion architecture, Unity Catalog. Track record of writing engineer-ready requirements rather than high-level statements. Experience working across multiple domain teams and stakeholders on a single programme. Experience with AI tooling, in particular AI agents Fluent working English. Nice to have Prior experience in a federated data mesh or data domain operating model. Databricks working knowledge sufficient to walk a steward through Unity Catalog artefacts. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success. Skills Fintech

Location: Intellias Meet your recruiter Mariia Tislenko mariia.tislenko@intellias.com https://www.linkedin.com... Vacancy details Software Engineering PHP Engineer Senior Ukraine Remote APPLY NOW REFER A FRIEND The team develops Intems, Intellias’s in-house core platform, and drives AI automation of the company’s internal processes. Intems covers employee records, time tracking and time off (PTO), employee engagement, benefits, and performance evaluation and development. It also serves as the corporate portal, is integrated with the company’s other information systems, and acts as the main interface for HR processes and a key data source for analytics. What project we have for you The team is part of the IT department, which plays a key role at Intellias in driving change management, process improvement and AI enablement across the company. What you will do Develop backend and frontend features for the Intems platform Build and support integrations between Intems and other company systems Turn business requirements into technical solutions: research options, compare trade-offs and propose the best approach Build AI-powered automations for internal processes Write clean, secure and maintainable code covered by unit and integration tests Estimate and plan tasks, and deliver on commitments Suggest technical and functional improvements that add value to the product What you need for this Must have skills: 7+ years of commercial PHP development experience, including PHP 8.x Strong understanding of OOP, SOLID principles and software design patterns Solid experience with MVC frameworks (Laravel or similar) Experience building REST APIs and integrating with external systems Experience with JavaScript (ES6+), TypeScript Experience with HTML5 and CSS/SASS Experience with relational databases (MySQL), including schema design and query optimization Experience with non-relational databases: MongoDB, Redis Experience with Docker Experience with Git and pull-request-based workflows Experience configuring and maintaining CI/CD pipelines (GitHub Actions, Azure DevOps or similar) Experience writing unit and integration tests (PHPUnit or similar) Daily hands-on use of AI coding assistants (GitHub Copilot, Cursor or similar) in modern IDEs (VS Code, PhpStorm) Practical experience using AI tools across the SDLC: code generation, refactoring, test creation, code review and documentation Knowledge of secure coding practices (OWASP Top 10) Experience doing code reviews Understanding of the SDLC and Agile principles Ability to estimate tasks accurately and deliver on commitments Nice to have skills: Experience with MS Foundry (deploying models and building AI agents) Experience automating the SDLC with AI: AI-assisted code review and test generation in CI/CD pipelines, coding agents, custom instructions and prompts for the team Experience with MCP and building tools and integrations for AI agents Experience with Azure cloud services (Service Bus, Storage account, Azure func, VM, Managed identity, Key-Vaults) Experience with Vue.js (2.x/3.x) Knowledge of Webpack, npm and modern front-end build tools Experience implementing responsive web designs Experience with Jira Certification: CCDV-F or a similar AI certification What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success.

Location: Bangalore - Engineering Workplace: OnSite LIFE AT UIPATH The people at UiPath believe in the transformative power of automation to change how the world works. We’re committed to creating category-leading enterprise software that unleashes that power. To make that happen, we need people who are curious, self-propelled, generous, and genuine. People who love being part of a fast-moving, fast-thinking growth company. And people who care—about each other, about UiPath, and about our larger purpose. Could that be you? Your mission We see boundless potential in the way we live. It drives the way we work. Our culture is our most valuable asset. It acts like a compass for us. We are fast, immersed, humble and bold. And thatʼs not just words on the walls. Eliminating time-consuming tasks means people get to do more of what they love. Itʼs an inspiring, high stakes challenge that motivates us, and this common passion bonds UiPath employees globally. We all strive every day to be better and to accelerate human achievement. We make software robots, so people donʼt have to be robots. Would you like to be part of this journey? At UiPath's Site Reliability team, we build the platforms and systems the entire company depends on to deliver on our compliance and SLA promises to customers. These span services and tools that enforce cloud access policies, cost governance, observability, operational excellence, and reliability across UiPath. We are scaling each of these pillars, and building the next generation of capabilities on each, powered by AI. This is a software engineering role. You will not be the person who identifies a reliability gap and files a ticket for another team to fix. You are the engineer who identifies the gaps across teams, designs the system that closes it, builds it, ships it, and drives its adoption — often by doing the integration work yourself rather than asking other teams to come to you. You build platforms that other engineers depend on in their critical path, and you hold yourself accountable to outcomes, not outputs. You treat every system you ship as a product: you put it in front of users early, seek feedback aggressively, and iterate until it delivers real results. If adoption is slow, you donʼt blame the docs — you sit with the team, understand the friction, and remove it. What you will be doing at UiPath As a Principal Software Engineer, you will - Design, engineer, and build SRE platform systems and capabilities with cutting-edge AI, treating them as products that other engineering teams depend on in their critical path. - Participate in livesite monitoring rotations, handle escalations, and drive effective mitigations — aggressively reducing customer impact through broad, detailed, and effective postmortems. - Drive availability, scalability, and performance improvements based on livesite learnings. Generate (or codify existing) best practices and ensure they are followed widely across UiPath — not by publishing guidance, but by embedding them into the systems you build. - Ensure technical deliverables meet or exceed expectations on reliability, scalability, quality, and performance. Identify and drive architectural changes that significantly move the needle on these dimensions. - Onboard other teams onto your platforms by driving outcomes yourself — writing the integrations, pairing with their engineers, removing friction — rather than handing off documentation and waiting. - Ship early, seek feedback relentlessly, and iterate fast. Treat every user complaint as a design input, not a support ticket. - Drive task planning, estimation, scheduling, and staffing. - Mentor Software Engineers to develop their skills and knowledge through hands-on coaching, advice, and training opportunities. - Participate in and influence process improvements and best practices across the engineering organization.   What youʼll bring to UiPath - Proven track record (10+ years) of architecting and engineering world-class, large-scale, distributed commercial applications and services, and ensuring customer success. - Experience building large-scale, complex internal platforms adopted by 10+ teams in their critical path at a large company — systems that have stood the test of time, not prototypes that were handed off or abandoned. - Demonstrated ability to drive adoption of your systems by doing the hard work yourself: writing integrations, removing friction for other teams, and measuring success by outcomes delivered — not features shipped. - Experience building and maintaining complex AI-powered applications in production. - Proficiency in one or more object-oriented languages (such as C#, C++, Go, or Python), backed by solid computer science fundamentals. - Deep understanding of data structures, algorithms, multithreading, synchronization, asynchronous patterns, and cloud programming. - Experience with service-oriented and microservice-based architectures, HTTP applications, and web services development. - Familiarity with modern engineering practices including agile development, CI/CD, and DevOps. Ability to work with globally distributed teams. - Experience working with or managing production Kubernetes infrastructure is a plus. - Experience with any of the cloud providers (Azure, AWS, GCP) and managed services (AKS, GKE, etc.) is a must. - Experience with database backends (e.g., Azure SQL, CosmosDB, Azure Data Lake, Power BI, MongoDB, MySQL, DynamoDB, etc.) #LI-VR1 Maybe you don’t tick all the boxes above—but still think you’d be great for the job? Go ahead, apply anyway. Please. Because we know that experience comes in all shapes and sizes—and passion can’t be learned. Many of our roles allow for flexibility in when and where work gets done. Depending on the needs of the business and the role, the number of hybrid, office-based, and remote workers will vary from team to team. Applications are assessed on a rolling basis and there is no fixed deadline for this requisition. The application window may change depending on the volume of applications received or may close immediately if a qualified candidate is selected. We value a range of diverse backgrounds, experiences and ideas. We pride ourselves on our diversity and inclusive workplace that provides equal opportunities to all persons regardless of age, race, color, religion, sex, sexual orientation, gender identity, and expression, national origin, disability, neurodiversity, military and/or veteran status, or any other protected classes. Additionally, UiPath provides reasonable accommodations for candidates on request and respects applicants' privacy rights. To review these and other legal disclosures, visit our privacy policy https://www.uipath.com/legal/trust-and-security/privacy-policy.