Role Description As a key player in the AdTech domain, you will be involved in cutting-edge digital advertising solutions, including: - Real-time bidding - Programmatic integrations - Audience targeting - Performance optimization You will take on a key role at the core of a fast-scaling ad exchange and performance monetization ecosystem, operating in a large-scale, real-time, multi-platform environment. Qualifications - 4+ years of experience in Ad Operations, Programmatic Advertising, or AdTech monetization roles - Strong understanding of the programmatic ecosystem (SSPs, DSPs, ad exchanges, RTB, header bidding) - Hands-on experience with platforms and proven relationships with SSPs, DSPs - Strong analytical and problem-solving skills with a performance-first mindset - Proven ability to manage multiple demand partners and optimize revenue streams - Deep understanding of monetization metrics (eCPM, fill rate, CTR, RPM, ARPU) - Fluent in English, both written and verbal - Ability to operate independently in a fast-paced, data-driven environment Requirements - Own and optimize day-to-day ad operations across Clixbee’s inventory and traffic sources - Manage relationships with SSPs, DSPs, ad networks, and programmatic partners globally - Drive yield optimization across all demand sources (eCPM, fill rate, RPM, revenue performance) - Monitor and analyze monetization performance across desktop, mobile web, and in-app environments - Identify and resolve operational and technical issues (tracking discrepancies, demand drops, latency, integration issues) - Work closely with the Business and engineering teams to improve ad placements, integrations, and monetization infrastructure - Support the implementation and optimization of header bidding, waterfalls, and server-side integrations - Build and maintain strong partner relationships while ensuring consistent revenue growth - Translate data insights into actionable monetization strategies - Continuously test, optimize, and scale new demand opportunities across the ad stack Benefits - People-first management with minimal bureaucracy - A friendly company culture, proven by employees who choose to return - Flexible working hours - 29 days of PTO (18 working days per year, plus all national holidays) - 9 paid recovery days - Full financial and legal support for independent contractors - Free English classes, with native speakers or Ukrainian teachers - Dedicated HR support

Role Description The IT Operations Lead is responsible for the hands-on delivery, reliability, and security of Wifinity’s IT services and infrastructure. This is a deeply technical, player-manager role leading a small team of three, with significant personal involvement in: - M365 - Linux systems - Nutanix-hosted infrastructure - Cloud platforms - Monitoring - Incident management - Automation The role ensures that core IT platforms and services are robust, well-monitored, and operationally sound, supporting both corporate users and operational teams. While leadership and structure are important, this role is fundamentally hands-on, requiring strong individual technical contribution alongside team leadership. Qualifications - Strong, demonstrable hands-on Linux experience in production environments. - Strong, demonstrable experience of managing and optimising an M365 tenant, particularly within an E5 licence tier. - Broad IT operations background across infrastructure, service desk, and incidents. - Practical experience with cloud platforms, automation, and monitoring tools. - Comfortable acting as both technical lead and individual contributor. - Understanding of security, resilience, and operational risk. - Calm, methodical, and comfortable operating in live, operational environments. - Experience leading a small team/Line Management. Requirements - Own the end-to-end delivery of IT Service Desk services and act as a senior escalation point, frequently resolving issues hands-on. - Ensure clear prioritisation, SLAs, escalation paths, and accurate documentation. - Drive pragmatic improvements to tooling, self-service, and knowledge base content. - Manage endpoint device management including robust configuration of MDM, InTune, and Conditional Access alignment to InfoSec policies. - Hands-on ownership of on-premise infrastructure predominantly hosted on Nutanix. - Design, build, patch, harden, and troubleshoot Linux systems in production environments. - Manage compute, storage, networking, backups, and platform resilience within Nutanix. - Own capacity planning, lifecycle management, and platform upgrades in line with operational demand. - Operate cloud services using a Linux-first approach, aligned with on-premise standards. - Implement and maintain infrastructure as code, automation, and standardised builds. - Own identity, access management, and authentication, backups, disaster recovery, and cost optimisation. - Own monitoring tools across infrastructure and services. - Lead and actively participate in major and complex incident response. - Own root cause analysis (RCA) and follow-through of corrective actions. - Own software asset and license management across the estate. - Maintain accurate inventories and ensure license compliance. - Lead a small team of 3 through direct involvement, mentoring, and coaching. - Balance delivery discipline with pragmatism. - Maintain high standards of documentation, runbooks, and operational hygiene. - Collaborate closely with Business Systems, Network Operations, and Information Security. - Execute against the IT operational plan while remaining responsive to real-world issues. Benefits - Competitive salary and benefits package. - Annual Leave Buy & Sell Scheme. - Remote first working environment for better work/life balance.

• Responsible for the hands-on delivery, reliability, and security of Wifinity’s IT services and infrastructure. • Lead a small team of three, with significant personal involvement in M365, Linux systems, Nutanix-hosted infrastructure, cloud platforms, monitoring, incident management, and automation. • Ensure that core IT platforms and services are robust, well-monitored, and operationally sound, supporting both corporate users and operational teams. • Own the end-to-end delivery of IT Service Desk services and act as a senior escalation point. • Ensure clear prioritisation, SLAs, escalation paths, and accurate documentation. • Hands-on ownership of cloud infrastructure platforms (e.g. Azure / AWS). • Lead and actively participate in major and complex incident response, coordinating resolution across IT, Network Operations, and third parties. • Maintain accurate inventories and ensure license compliance.

Role Description We are seeking a senior MLOps Architect to design and scale a modern ML and Generative AI platform across AWS. This role will own the architecture for traditional ML and LLM/Generative AI pipelines, ensuring production reliability, governance, cost optimization (FinOps), and enterprise-grade security. The ideal candidate has deep expertise in AWS, SageMaker, Databricks, Atlan (data catalog/governance), and modern MLOps tooling, and understands how to operationalize LLMs, RAG systems, and foundation models within a governed, scalable MLOps stack. This is a strategic, hands-on architecture role responsible for integrating GenAI capabilities into an enterprise ML platform. What you’ll Do - MLOps & GenAI Platform Architecture - Design and implement scalable ML and LLM infrastructure on AWS (SageMaker, EKS, S3, IAM, Lambda, Step Functions, CloudWatch). - Architect end-to-end ML and Generative AI lifecycle workflows: - Data ingestion & preprocessing - Feature engineering / embedding generation - Model training & fine-tuning (traditional ML + foundation models) - Model evaluation & validation - Deployment (real-time, batch, streaming) - Monitoring & retraining - Integrate LLM pipelines (prompt workflows, RAG architectures, fine-tuning flows) into the enterprise MLOps stack. - Define standards for CI/CD/CT pipelines across ML and GenAI workloads. - Generative AI & LLM Operationalization - Architect Retrieval-Augmented Generation (RAG) pipelines including: - Embedding generation workflows - Vector database integration - Document ingestion and chunking strategies - Retrieval evaluation and monitoring - Design and deploy LLM-based services using: - Managed services (e.g., SageMaker endpoints, Bedrock-style APIs) - Containerized custom inference services - Establish prompt versioning, evaluation frameworks, and experiment tracking for LLM systems. - Implement guardrails for hallucination control, safety monitoring, bias detection, and usage logging. - Define architecture for LLM fine-tuning workflows (including data curation, evaluation, and cost controls). - Implement scalable orchestration of LLM pipelines using workflow engines and event-driven patterns. - Deployment, Monitoring & Reliability - Architect scalable inference patterns for: - Traditional ML models - LLM APIs - RAG systems - Implement model monitoring frameworks for: - Performance degradation - Drift detection - LLM output quality - Latency and token usage metrics - Define SLAs/SLOs for ML and GenAI systems. - Design safe deployment strategies (blue/green, canary, shadow testing). - Establish logging, observability, and traceability standards for GenAI systems. - FinOps & Cost Optimization - Implement cost tracking for: - Training workloads - Inference endpoints - Vector database storage - Optimize LLM workloads for cost-performance tradeoffs (model size, batching, caching strategies). - Design autoscaling and compute optimization strategies for GPU and CPU-based inference. - Partner with finance and engineering teams to forecast ML/GenAI infrastructure spend. - Platform Enablement & Standards - Define enterprise standards for: - Experiment tracking - Model registry - Prompt registry - Artifact management - Embedding versioning - Provide architectural guidance to data science, AI, and engineering teams. - Evaluate and recommend tooling across the ML/GenAI stack (MLflow, feature stores, vector databases, orchestration tools). - Drive documentation and reusable patterns for ML and GenAI development. Qualifications - 6+ years of experience in ML engineering, data engineering, or MLOps roles. - Proven experience architecting ML platforms in AWS. - Strong hands-on experience with SageMaker (training, pipelines, deployment). - Experience operationalizing LLM or Generative AI systems in production. - Experience building RAG pipelines and integrating vector databases. - Experience working with Databricks in production. - Experience implementing data governance and catalog systems (e.g., Atlan). - Strong understanding of CI/CD principles for ML and GenAI. - Experience with containerization (Docker) and orchestration (Kubernetes/EKS). - Deep knowledge of infrastructure-as-code (Terraform, CloudFormation). - Strong understanding of observability and monitoring for ML systems. - Experience implementing cloud cost optimization strategies (FinOps). - Strong Python proficiency. - Experience with foundation model fine-tuning and parameter-efficient methods. - Experience implementing model registries and experiment tracking tools. - Experience designing feature stores and embedding stores. - Familiarity with AI risk management, bias mitigation, and safety controls. - Experience supporting regulated or data-sensitive environments. - Platform-level architectural thinking. - Deep understanding of how to integrate GenAI into enterprise ML ecosystems. - Ability to balance scalability, governance, security, performance, and cost. - Strong technical leadership and cross-functional collaboration skills. - Hands-on ability to move from architecture design to implementation. Benefits - Competitive Base Salary Range of $117,800 – $189,000. - Annual Incentive Compensation Eligibility – Up to 10% annually. - Health Insurance: Comprehensive medical, dental, and employer-paid vision plans through UnitedHealthcare (UHC). - Flexible Spending Account: Set aside pre-tax dollars for qualified out-of-pocket expenses. - Lifestyle Spending Account: Employer-sponsored post-tax benefits for well-being expenses. - 100% Company Paid Insurances: Basic short-term and long-term disability insurance, as well as vision insurance. - Voluntary Insurance: Supplemental life insurance and enhanced short- and long-term disability coverage available. - Paid Maternity and Parental Leave: Company-paid leave beyond state-mandated policies. - Commuter Benefits: Pre-tax benefits on parking and commuter expenses. - LifeBalance Program: Discounts on outdoor activities, arts, health, and fitness. - Plum Benefits Discount Program: Exclusive discounts on shows, travel, car rentals, and more. - Tuition Reimbursement: Up to $5,000 annually for further education and career development. - Travel Reimbursement: Support for work-related travel expenses. - Paid Time Off and Sick Time. - Retirement Benefits: 401K plan with a 25% match on contributions, up to 6% of annual salary.