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Chief Technology OfficerAI-native transformation leader & hands-on builder-in-chief driving intelligent engineering to create real business value for enterprises. Architect what’s next. Own client revenue. Scale meaningful outcomes.What are we looking forreal solver?We identify better ways of doing things.Solver? Absolutely. But not the usual kind. We're searching for the architects of the audacious & the pioneers of the possible. If you're the type to dismantle assumptions, re-engineer ‘best practices,’ and build solutions that make the future possible NOW, then you're speaking our language.Improver. Solver. Futurist.Great sense of humor.‘Possible. It is.’ Mindset.Compassionate collaborator. Bold experimenter. Tireless iterator.Natural creativity that doesn’t just challenge the norm, but solves to design what’s better.Thinks in systems. Solves at scale.This Isn’t for Everyone. But if you’re the kind who questions why things are done a certain way—and then identifies 3 better ways to do it — we’d love to chat with you.Your Mission: The Rolesolving for better.You are not just a technology leader. You are the chief architect of our future and innovation leader. You lead by doing—by building systems, shipping platforms, and scaling infrastructure that powers real AI outcomes.You won’t be presenting tech strategy on PowerPoint. You’ll be hands-on defining foundational architecture, evolving our platform DNA, and unlocking entirely new capabilities for AI-native product development.You will head Engineering, R&D, and Strategic Partnerships from a tech standpoint, employing first-principles design to create defensible moats and net-new revenue streams. Slide decks are optional after the platform is live.We’re not hiring a spokesperson. We need a CTO who still reviews PRs, whiteboards latency trade-offs, and thinks deployment-first. Relentless prototyper, ruthless refactorer, defender of velocity—you’ll be the Directly Responsible Individual (DRI) for velocity, integrity, innovation cadence and the performance of the engineering org behind it.Your Responsibilitieswhat you will wake up to solve.This isn’t a “manage the tech team” role. You are the architect of reimagine 'what's next' and redefine the 'how' of 'what's next'. Your mission is to define the future of AI-native technology, build scalable platforms, and translate technical excellence into compounding business advantage.Here’s how you’ll make your mark:Set the North Star — Strategy & VisionArchitect the future. Define the 3-year roadmap for futurify.ai & evlos™, platform evolution, and infrastructure scale on Google Cloud.Link tech to P&L. Tie every architectural bet to revenue growth, margin, and client ROI (target ≥ 30% uplift).Build the Moat — Innovation & IPPatent the edge. File 10+ patents in 2 years across hybrid human-AI workflows, adaptive learning loops, and Agent2Agent protocols.Prove novelty. Run continuous prior-art sweeps; partner with legal to lock defensible claims.Accelerate R&D. Spin up internal accelerators—e.g., ROI dashboards with self-improving ML delivering production pilots in < 90 days.Ship with Velocity — Platform ExecutionEngineer for scale. Lead modular, production-grade AI stacks (ML infra, data pipelines, orchestration layers) with 99.9 % uptime.Prototype > PowerPoint. Maintain a “code by day 1” rule; reduce iteration loops by 40 % via agentic automation.Guardrails & reliability. Embed SRE, security, and ethical HITL checks into CI/CD; track NPS > 80 via real-time dashboards.Grow the Engine — People & EcosystemElevate talent. Hire, coach, and retain world-class engineers; double internal promotion rate YoY.Set the bar. Codify standards, design reviews, and architectural principles that scale across squads.Partner to win. Forge deep alliances with hyperscalers, ISVs, and research labs; present Searce’s narrative at industry forums."Welcome to SearceThe ‘process-first’, AI-native modern tech consultancy that's rewriting the rules.We don’t do traditional.As an engineering-led consultancy, we are dedicated to relentlessly improving the real business outcomes. Our solvers co-innovate with clients to futurify operations and make processes smarter, faster & better. We build alongside our clients. Not for the vanity metrics. But for the transformation to embed lasting competitive advantage for our clients.The result? Modern business reinvention, built on math, tech, and clarity of purpose.Functional SkillsEngineering minded Business & Tech Ownership: Designs, evaluates, and evolves AI & data platforms, Decision Intelligence Engineering, MLOps, Cloud Platform Engineering - owning the blueprint end-to-end.Platform Scalability Sense: Balances performance, tech-debt, and cost to scale reliably without sacrificing maintainability.First-Principles Builder: Uses evlos-style iteration to decide what to build, evolve, or retire—never cargo-culting patterns.Operational Judgment & Reliability: Knows when to optimise vs. refactor; delivers 99.9 % uptime, security, and ethical AI guardrails.Product-Aware Systems Thinker: Aligns architecture with business impact, usability, and extensibility—ties every feature to ROI.Complexity Simplifier: Turns deep tech into plain-speak narratives for execs, engineers, and clients alike.Team-Builder & Culture Carrier: Hires, mentors, and scales “solver” talent; fosters an always-in-beta, high-ownership culture.Strategic Trade-Off Navigator: Makes context-driven calls when speed > polish or robustness > elegance; communicates rationale clearly.Tech SuperpowersAI-Native Architect – Reimagines business with modern Tech to deliver platforms, accelerators & real value to clients. Process first mindset and ready to embrace agentic AI to enable process transformation.Full-Stack Platform Thinker – Builds modular, reusable services across data, MLOps, vector DBs, and Google Cloud infra.Distributed-Systems Savant – Crafts resilient, low-coupling architectures that survive burst traffic and node failure.Security & Privacy Guardian – Embeds zero-trust, privacy-by-design, and ethical guardrails into every pipeline.Multi-Agent Orchestrator – Engineers hybrid human-AI workflows, adaptive learning loops, and Agent-to-Agent protocols.Product-Minded Technologist – Balances technical rigor with user impact; ties every release to measurable ROI.Pragmatic Tool Picker – Chooses the simplest tech that compounds scalability; fluent in Python, TensorFlow/PyTorch, Go.Engineer @ Heart – Writes, reviews, and debugs code daily; proves designs with benchmarks, not slideware. Business-first, tech-second, outcome focused technology leader."Experience & RelevanceScale & Leadership – 15 + years leading high-growth engineering orgs; built teams from 10 → 200 while preserving velocity and culture.Architecture & AI Execution – Led 0→1 and 1→100 deliveries in MLOps, LLM stacks, or large-scale data infra on Google Cloud, Databricks, AWS, OpenAI; agentic workflows.Cross-Functional Business Impact – Bridged R&D, product, and GTM to deliver ≥ 30 % ROI improvements; trusted by founders and Fortune-500 execs alike.High-Stakes Decisioning & Influence – Navigated trade-offs in mission-critical, multi-region deployments; converts technical depth into board-level clarity.Pedigree Credentials – Advanced degree (MS/PhD) in CS/AI/Eng; proven industry disruption record; combines MBB-style strategy with a builder’s execution bias.Bonus Points (you will thrive if you have)Org Architect – Designed or scaled a 100 + engineer AI platform org from scratch.Patent Prodigy – Filed/secured ≥ 5 AI or distributed-systems patents.Open-Source Evangelist – Created or maintained widely adopted OSS in MLOps / vector databases.Recognized Tech Authority – Recognised expert (e.g., Google Dev Champion, AWS or Databricks) who optimises cost, latency, and security at hyperscale.Battle-Tested – Has broken production systems, learned, and automated safeguards to prevent repeats.Adoption-Focused – Proven knack for turning tech into sticky user adoption and recurring revenue.Founder Energy – Combines product vision, engineering heart, and ownership gut; bias for rapid prototyping & decision velocity within Searce “Happier” DNAJoin the ‘real solvers’ready to futurify?If you are excited by the possibilities of what an AI-native engineering-led, modern tech consultancy can do to futurify businesses, apply here and experience the ‘Art of the possible’. 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At Why Hiring, we believe in the power of connecting talented individuals with incredible remote job opportunities. Our mission is to simplify the job search process and empower professionals to find fulfilling roles that align with their skills and passions, regardless of geographical constraints.About The Role:This position requires strong quantitative skills, experience with large and complex datasets, and the ability to collaborate with analysts, engineers, and mission partners to develop high-impact solutions that drive intelligence insight and operational advantage.Perform statistical analysis and data exploration to extract meaningful insights from complex datasetsSupport the development and validation of predictive models to identify trends and patternsContribute to the development of AI/ML models and data-driven solutionsConduct exploratory data analysis to support decision-making and operational planningAssist in building and maintaining data pipelines for data collection, processing, and integrationCollaborate with data scientists, engineers, and cross-functional teams to improve data workflowsDevelop scripts and tools to automate repetitive tasks and improve efficiencySupport initiatives to enhance data quality, structure, and accessibilityApply basic experimental and analytical approaches to test ideas and evaluate outcomesContribute to improving data systems, workflows, and analytical capabilitiesAssist in identifying data gaps, inconsistencies, and opportunities for optimizationParticipate in team meetings, project discussions, and knowledge-sharing sessionsEducationBachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.Required SkillsProficiency in Python, R, SQL, or similar programming languages.Experience with data visualization platforms such as Power BI or Tableau.Strong understanding of statistical techniques and modeling approaches.Foundational knowledge of AI/ML concepts and applications.Experience working with relational and/or NoSQL databases.Familiarity with cloud-based big data technologies.Ability to explain complex technical findings to non-technical audiences.Understanding of intelligence analysis processes and mission requirements.Experience working with structured and unstructured datasets in complex environments.ExperienceMinimum of 0 to 2 years of experience in data science, analytics, machine learning, or related technical fields.Why Hiring does not discriminate on the basis of race, sex, color, religion, age, national origin, marital status, disability, veteran status, genetic information, sexual orientation, gender identity or any other reason prohibited by law in provision of employment opportunities and benefits.

Head of Data & AILocation: Dubai, UAEFull-time | On-site We are hiring a Head of Data & AI to lead and scale the Data & AI function for a goverment backed organisation in Dubai.You will manage an existing team of 7 Data & AI professionals, report directly to C-level leadership, and take ownership of the organisation’s Data & AI strategy, architecture and delivery as the company look to scale its capabilities and drive AI adoption across the organisation.ResponsibilitiesLead, mentor and scale the existing Data & AI teamOwn the Data & AI strategy and technical roadmapLead delivery of production AI/ML, Generative AI, LLM and Agentic AI solutionsOversee modern data platforms, engineering and AI architectureEstablish best practices across Data Engineering, AI/ML and MLOps/LLMOpsWork directly with C-level stakeholders on priorities, investment and deliveryEnsure solutions meet security, governance and scalability requirementsRequirementsStrong experience leading Data & AI teamsProven experience building or scaling technical teamsStrong background across Data Engineering, AI/ML and modern data architectureExperience delivering AI/ML solutions into productionKnowledge of GenAI, LLMs, Agentic AI and cloud technologiesExcellent communication and senior stakeholder-management skillsComfortable remaining technically involved while leading at a strategic levelWhat’s on OfferCompetitive salary packagePerformance-based annual bonusSchooling support for families + other allowancesOpportunity to lead and scale a growing Data & AI functionDirect exposure to and influence with C-level leadershipUAE-based candidates only.

General Summary:The Sr. Digital Delivery Specialist at EMSTEEL designs, builds and delivers advanced AI and machine-learning solutions that create measurable business value across the Group’s steel and building-materials operations. The role sits within the Digital Centre of Excellence and focuses on Generative AI, Agentic AI, Computer Vision, AI Digital Twins and productionizing models through modern MLOps practices applied to industrial use cases such as process optimization and predictive maintenance. Working end-to-end from use-case discovery and experimentation to deployment, monitoring and adoption. Essential Duties and Responsibilities:Partner with business stakeholders and SMEs to identify, qualify and prioritize high-impact AI/ML use cases aligned to EMSTEEL’s strategic objectives.Design, develop and deploy Generative AI solutions (LLM-based assistants, RAG pipelines, document intelligence, summarization and content generation) tailored to enterprise needs.Build Agentic AI systems — autonomous and multi-agent workflows that reason, plan, use tools and orchestrate tasks, including Agent-to-Agent (A2A) collaboration and protocols across enterprise applications.Deliver industrial AI use cases across the value chain — process optimization, predictive maintenance, quality prediction, energy and yield optimization, and anomaly detection for steel and building-materials operations.Develop and operationalize AI Digital Twin solutions that simulate, monitor and optimize plant assets and production processes in real time.Build Computer Vision solutions for defect detection, surface-quality inspection, safety monitoring and process automation on the shop floor.Develop, validate and optimize classical and deep-learning models for prediction, optimization, anomaly detection and process control.Implement robust MLOps practices: CI/CD for models, automated pipelines, feature stores, model registry, versioning, monitoring, drift detection and retraining.Engineer scalable data and AI pipelines on Databricks and integrate solutions across the Microsoft (Azure) stack and Dataiku.Own end-to-end AI project delivery — from proof-of-concept to production — ensuring quality, security, performance and on-time delivery.Drive AI adoption by embedding solutions in downstream applications, updating SOPs, enabling users and delivering relevant training and change management.Establish responsible-AI, governance, evaluation and guardrail practices for GenAI and agentic solutions (accuracy, safety, bias, data privacy and cost control).Communicate findings, model behavior and business impact clearly to both technical and non-technical audiences.Additional Duties and ResponsibilitiesContribute to the AI reference architecture, reusable components and internal best-practice standards.Stay current with emerging GenAI/agentic frameworks, foundation models and tooling, and pilot promising innovations.Mentor junior Sr. Digital Delivery Specialists and analysts and support a culture of experimentation and continuous learning.Knowledge, Skills and/or Abilities RequiredStrong hands-on experience in machine learning, deep learning and statistical modelling using Python (and SQL).Proven expertise in Generative AI LLMs, prompt engineering, RAG, embeddings, vector databases and fine-tuning.Experience building Agentic AI solutions and multi-agent / Agent-to-Agent (A2A) systems using frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen or similar.Experience delivering industrial AI use cases process optimization, predictive maintenance and AI digital twins.Hands-on Computer Vision experience (OpenCV, PyTorch/TensorFlow, object detection, segmentation, defect/anomaly detection).Solid MLOps capability MLflow, model deployment, containerization with Docker/Kubernetes, CI/CD, GitHub / GitHub Actions and model monitoring.Proficiency with Databricks (Spark, Delta Lake, Unity Catalog, notebooks) for large-scale data and ML workloads.Working knowledge of the Microsoft/Azure AI stack (Azure Machine Learning, Azure OpenAI, Azure AI Foundry, Fabric/Synapse) and Dataiku.Ability to translate business problems into technical solutions and communicate results effectively.Strong problem-solving, stakeholder-management and cross-functional collaboration skills.Minimum Requirements (Must Have):EducationBachelor’s / Master’s in Computer Science, Data Science, AI, Statistics, Engineering, Physics or Mathematics.Experience4+ years in data science / machine learning delivery.Demonstrated delivery of GenAI or agentic solutions to production.2+ years implementing cutting-edge AI/GenAI technologies.Exposure to manufacturing, heavy industry or steel operations.Experience with responsible-AI governance and LLMOps.Training / CertificationsCertifications in Machine Learning / AI, Databricks, Microsoft Azure AI or Dataiku.

A leading multi-strategy investment firm is seeking a Quantitative Researcher to join a high-performing systematic equities team. This is a front-office opportunity focused on the research, development and implementation of data-driven investment strategies across global equity markets.Working directly with senior investment professionals, the successful candidate will contribute to the full research lifecycle, from idea generation and signal discovery through to portfolio construction and live strategy analysis. The role offers significant exposure to investment decision-making within a collaborative, research-intensive environment that values innovation, intellectual curiosity and rigorous analytical thinking.Key ResponsibilitiesResearch and develop quantitative signals and alpha factors across global equity markets.Analyse large-scale market, fundamental and alternative datasets to identify investment opportunities.Design, test and refine systematic investment strategies using robust quantitative methodologies.Conduct statistical analysis and backtesting to evaluate the predictive power of signals and models.Partner closely with Portfolio Managers to generate actionable investment insights.Contribute to portfolio construction, risk management and performance attribution processes.Develop and maintain research tools, analytical frameworks and data infrastructure.Evaluate new datasets, modelling approaches and machine learning techniques to enhance research capabilities.Monitor live strategies and investigate drivers of portfolio performance.Collaborate with researchers, engineers and investment professionals to improve the overall investment process.Requirements2-8 years of experience within quantitative research, systematic equities, statistical arbitrage or a related investment strategy.Open to exceptional PhD/Postdoctoral candidates with backgrounds in Machine Learning, AI, Statistics, Mathematics, Physics or Computer Science.Candidates from leading technology and AI research organisations with expertise in neural networks and advanced modelling techniques are also encouraged to apply.Experienced Quantitative Researchers with a strong academic background and track record of alpha generation within systematic equities are of particular interest.Strong understanding of statistics, probability, data analysis and quantitative modelling.Advanced Python programming skills and experience working with large datasets.Experience developing and evaluating predictive signals or systematic investment strategies.Excellent analytical, problem-solving and communication skills.For more information contact:Thomas Hennelly – thomas@pointonetalent.comGraham Murphy – graham@pointonetalent.com

About the Role: The Data Analytics Expert is responsible for conducting advanced analytics, building predictive models, and applying statistical and machine learning techniques to extract actionable insights that support customer, commercial, revenue, pricing, and growth-related decision-making across the organization.Role Responsibility: Use Case Identification:Conduct exploratory data analysis and develop advanced analytical use cases in collaboration with commercial, sales, marketing, finance, and customer experience stakeholders.Identify opportunities for customer segmentation, churn prediction, lifetime value (CLV), demand forecasting, pricing optimization, and revenue uplift.Translate business questions into data science problems, including feature engineering, hypothesis formulation, and model development. Advanced Analytics Development and Implementation:Identify relevant datasets and ensure data readiness for modelling, including cleansing, normalization, and transformation of customer, transaction, pricing, and commercial datasets.Assess data quality and completeness; work closely with data engineers to enhance data pipelines and data models.Design and develop advanced analytical, ML, and AI models to generate insights across customer behavior, sales performance, product profitability, and commercial efficiency.Tune and optimize models for performance, accuracy, robustness, and business relevance.Create and maintain clear documentation for models, algorithms, assumptions, limitations, and results.Market Research and External AnalyticsConduct market research to assess market size, growth, demand drivers, and competitive landscape.Develop market sizing (TAM, SAM, SOM) and demand forecasting models using internal and external data.Identify and integrate external data sources to enrich customer and commercial analytics.Analyze market trends and scenarios to support strategic planning, pricing, and go-to-market decisions.Insight Generation development and Decision Support:Translate analytical findings into actionable commercial recommendations and communicate insights clearly to non-technical stakeholders.Partner with business intelligence and analytics teams to align predictive insights with dashboards, KPIs, and reporting frameworks.Support strategic initiatives related to customer growth, retention, pricing strategy, cross-sell/upsell, and commercial optimization.Translate market insights into clear recommendations for senior stakeholders.Qualifications & Experience: Bachelor’s in data science, Statistics, Mathematics, Computer Science, or a related quantitative field.Having a master’s or PhD degree in a related field is a plus.Minimum of 8–10 years of hands-on experience in advanced analytics and data science.Strong domain experience in customer analytics, commercial analytics, revenue management, pricing, or growth analytics is required.Experience with CRM data and data models (Salesforce CRM preferred)Proficiency in SQL (Oracle preferred) for data extraction and transformation.Familiarity with working on cloud platforms (e.g., Azure ML) is a plus.