Why Tamara?

We’re proud to be Saudi’s first FinTech unicorn.

Our mission is to help people own their dreams by building the most customer-centric financial super app in the world. & There is no playbook for that; our Tamarians are writing it. Our teams are made up of innovators, problem-solvers, and learners we thrive on curiosity and collaboration.

If this sounds like you: curious, driven, and ready to build, we’d love to meet you

Apply now and join the next generation of Builders!

About Tamara's Builders Program 

At Tamara, we believe exceptional talent deserves an exceptional launchpad.

Our Flagship Builders Program is designed for ambitious graduates ready to step into real responsibility from day one. This isn’t a rotational “observer” program, it’s a career accelerator built for those who want to build, own, and raise the bar early.
Designed for recent graduates and early-career talent with up to two years of experience, the program places you directly into high-impact roles across Product, Engineering, Design, and beyond. You’ll contribute immediately and grow at an accelerated pace.
From Product to Engineering, Design to Commercial, you’ll tackle meaningful challenges that shape how millions experience fintech across the region. You’ll be trusted with ownership, surrounded by high-caliber peers, and mentored by leaders who expect excellence.

Our January and June cohorts are your opportunity to move fast, think big, and start building what’s next - not someday, but now.

About the role

We’re looking for a fresh graduate or early-career Associate Data Scientist on a builder path.

This role blends product thinking, applied statistics, and production-minded analytics. You will:

• turn ambiguous problems into measurable questions
• build reliable measurement (metrics and experimentation)
• create lightweight models and decision tools that teams can use in real workflows
• partner closely with engineering, product, and risk to improve customer outcomes and business performance
• build AI-assisted decision workflows (for example, LLM-powered analysis copilots backed by a curated metrics layer, with clear guardrails and validation)

With the advancement of AI, we value people who have strong fundamentals and clear thinking. Understanding data generation, measurement, tradeoffs, and how to validate results matters more than memorizing tools. You'll learn how to use AI responsibly to move faster, while still owning correctness, robustness, and interpretation.

Your responsibilities

• Define problems and measurement
  • Translate product or business questions into testable hypotheses and clear success metrics.
  • Build and maintain metric definitions and analysis templates so decisions are consistent and repeatable.
• Experimentation and causal thinking
  • Design, analyze, and interpret A/B tests (and quasi-experiments when randomization is not possible).
  • Partner with product and engineering to ensure correct tracking, guardrails, and experiment quality.
• Modeling for decisions (practical ML)
  • Build baseline predictive and segmentation models (for example, churn propensity, risk signals, customer clustering) with clear evaluation and limitations.
  • Focus on models that are actionable: who will use them, when, and what decision they change.
• Applied AI (LLMs) for analytics and decisioning
  • Prototype small, safe LLM use cases that improve how teams explore data (for example, natural-language Q&A over a curated dataset, summarizing experiment results, or generating investigation checklists).
  • Help define evaluation and validation approaches for AI-assisted outputs (sanity checks, golden queries, offline test sets, and human review loops).
  • Partner with platform and security stakeholders to ensure AI workflows are permissioned correctly and avoid leaking sensitive data.
• Analytics that ships
  • Create reusable, well-documented analysis assets: datasets, feature tables, notebooks, dashboards, and simple services or jobs.
  • Collaborate with data engineering to productionize reliable pipelines where needed.
• Data quality and reliability
  • Validate data inputs, monitor key metrics, and investigate anomalies.
  • Document assumptions and build sanity checks so analyses and models are trustworthy.
• Responsible use of AI tools
  • Use AI to accelerate coding, documentation, and exploration.
  • Validate AI outputs, protect sensitive data, and follow safe data handling practices.

Your expertise (must have)

• Fresh graduate or < 1 year of relevant experience (internships, capstone projects, or part-time roles count).
• Strong SQL fundamentals (joins, aggregations, window functions).
• One programming language for data (preferably Python) with basic skills in:
  • Data manipulation (tables/dataframes)
  • Statistics fundamentals (distributions, sampling intuition, confidence basics)
  • Basic modeling (regression/classification basics and evaluation intuition)
• Strong analytical thinking:
  • Ability to define a problem, validate data, and explain results clearly.
• Strong attention to detail and commitment to accurate, reliable outputs.
• Ability to work effectively in a team-oriented environment.

Nice to have

• Exposure to experimentation platforms or frameworks (for example Statsig, Optimizely, internal experimentation tooling).
• Familiarity with modern analytics stacks (dbt, BigQuery, Snowflake, Looker, PowerBI, Tableau) through coursework or projects.
• Exposure to ML tooling (scikit-learn, notebooks, basic MLOps concepts) and version control (Git).
• Familiarity with LLM concepts (prompting basics, retrieval/RAG intuition, and evaluation approaches) through coursework or side projects.
• Understanding of product analytics concepts (funnels, cohorts, retention) and causal pitfalls (selection bias, confounding).
• Experience creating AI-ready data assets (clean semantic layers, metric definitions, data contracts, documentation, and sanity-check checklists).
• Knowledge of responsible data handling (PII basics, access controls, safe sharing).

What success looks like

• You can independently deliver an end-to-end analysis with clear assumptions, validation steps, and a concrete recommendation.
• You help ship at least one decision tool (experiment, metric framework, or lightweight model) that changes a product or business decision.
• Stakeholders can run repeatable analyses with less back-and-forth, and your work reduces ambiguity in key metrics.
• You can spot when results look off, debug quickly, and explain the root cause.

Responsibilities:

• Own the CMA (SCA) license application end-to-end: documentation, submissions, regulator meetings, and responses to queries
• Be named as the designated Compliance Officer; obtain and maintain personal fit & proper approval
• Serve as the Company`s primary liaison with relevant regulatory authorities.
• Design the UAE Compliance Framework: policies manual, compliance monitoring program, internal controls register, and client classification
• Prepare and submit the Annual Compliance Report (ACR) and semi-annual internal controls reports to the CMA
• Act as the named MLRO with full statutory responsibility, register and maintain MLRO designation on the UAEFIU goAML system
• Build the Compliance Management Framework (CMF) specifically for Category 5 activities: Investment Intermediation, Client Classification (Retail vs. Professional), and Suitability Assessments
• Manage the end-to-end STR lifecycle: alert review, investigation, goAML filing, and liaison with UAEFIU and law enforcement where required
• Conduct the annual Business-Wide AML Risk Assessment and present findings to the board; ensure sanctions screening (OFAC, UN, EU, UAE) is embedded across onboarding and transaction monitoring
• Monitor CMA regulatory developments; translate changes into concrete actions with defined timelines; evaluate new business initiatives and provide compliance opinions
• Review and approve all UAE client-facing marketing materials; maintain the complaints handling framework with defined resolution timescales and regulatory reporting
• Prepare monthly and quarterly board-level compliance reports; coordinate external audits and manage remediation of findings to closure
• Design and deliver AML/compliance training for all UAE staff; act as the internal regulatory advisor to partners, operations, finance, and product teams

Requirements:

• 7+ years in financial compliance: Minimum 3 years in the UAE under CMA (SCA) regulation. DFSA/FSRA background considered
• Bachelor's degree: Law, Finance, Economics, Business Administration, or a related field
• Proven CMA (SCA) license track record: Personally led a CMA (SCA) license application
• Retail FX/CFD expertise: Deep understanding of retail FX/CFD products from a compliance perspective
• Relevant professional qualification acceptable to the CMA (e.g. CISI UAE Financial Rules & Regulations or equivalent)
• Clean fit & proper record: Must have been previously approved as a CO/MLRO by the SCA (CMA)
• goAML expert proficiency: Hands-on experience with UAEFIU goAML: registration, STR filing, and ongoing system maintenance
• UAE residency: ​​physically based in the UAE and eligible to serve as a named Compliance Officer and MLRO with the CMA
• AML/CFT legal framework mastery

Will be a plus:

• CAMS, ICA Diploma, ACFCS, or equivalent compliance qualification
• LLM, MBA, or postgraduate degree in compliance, law, or finance
• Prior experience coordinating multi-jurisdiction compliance standards within an international group
• Professional proficiency in Arabic is a meaningful advantage in regulator engagement

We offer:

• Paid time off, including annual leave, sick leave, and public holidays
• Medical budget
• Professional education budget
• Language learning budget
• Wellness budget (gym membership, sports gear and related expenses)

The Mission
We believe the transformative potential of AI is significantly under-realised in our region. To bridge this gap, we are incubating a new division within Careem dedicated to Enterprise AI Transformation. 
We are reimagining and building the future of work to simplify and improve how businesses function in the era of GenAI with WorkOS: a next-generation ‘operating system’ designed to deploy, orchestrate, and improve AI agents across every customer and operational journey (and increasingly autonomously). This isn’t just automation; it’s about creating a hybrid workforce where self-learning AI agents handle the heavy lifting, empowering our people to focus on the highest-value, most creative work.

The Team
This group operates as a startup within Careem with a distinct mandate: move fast, build boldly, and deliver production-grade AI systems that fundamentally change how the region leverages technology. 

The Opportunity
We are looking for an exceptional founding Backend Engineer to build the WorkOS platform. This is a role for a systems-thinker who wants to work at the intersection of high-scale distributed systems and AI orchestration. You will be responsible for building the "brain" of WorkOS, the engine that deploys and manages autonomous agents across the region’s most complex operational journeys at massive scale.

As one of the first engineers in WorkOS, you will have a disproportionate impact on our technical foundation, culture, and the speed at which we move from 0 to 1.

What You’ll Do

• Architect and Build the WorkOS Engine: Design and build the scalable backend services and architectures required to orchestrate complex AI workflows and real-time data streaming. Leverage novel technologies to build cutting-edge capabilities. 
• Set the Engineering Gold Standard: As a founding member, you will establish our backend best practices, from CI/CD and observability to security and system integrity, ensuring a high-velocity but rigorous engineering culture.
• Solve for Distributed Complexity: Navigate the unique challenges of integrating AI agents into legacy enterprise stacks, ensuring low-latency communication and robust data consistency.
• Database design: Build our data infrastructure, leveraging relational, schemaless, and vector stores to power the platform and create persistent brains for our Agents. 
• Full-Cycle Ownership: Own the lifecycle of the platform, from rapid prototyping of new agent capabilities to maintaining production-grade systems at enterprise scale.
• Drive AI-Accelerated Engineering: Constantly experiment with AI-assisted development to move faster than traditional teams, while maintaining a bar for superb technical quality and craft.
• Lead Pioneer Deployments: While building the core platform, you will occasionally lead the charge on first-of-their-kind implementations for strategic partners, ensuring our tech solves real-world operational complexity.
• Operate with High Agency: In this lean, startup-style environment, you will be responsible for outcomes over inputs, rolling your sleeves up to code and balancing investments in the long-term technical roadmap with the need to ship value quickly.

What You’ll Need: 

• 8–12+ years of professional backend engineering experience, with significant tenure acting as a Staff Engineer or Technical Lead for complex, high-scale distributed systems.
• Mastery of Backend Systems: Deep expertise in languages like Python, Go, or Node.js, with a proven track record of architecting concurrency, microservices, and high-throughput data pipelines.
• AI-Native Infrastructure Depth: Hands-on experience with LLM orchestration (LangChain, etc.), vector databases (Pinecone, Milvus), and RAG architectures at a production-grade level.
• Systems-Level Visionary: The ability to design "platform-first", thinking in terms of APIs, modularity, and extensibility so that the WorkOS core can support infinite customer use cases.
• Obsession with Performance: A specialist's focus on latency and system observability; you believe that AI interactions must feel "instant" and "bulletproof" to be valuable.
• Startup-level Autonomy: Comfortable navigating a "0-to-1" environment where you define the technical roadmap and ship high-quality code without a playbook.
• Willingness to work on-site full time in UAE, to foster the high-intensity collaboration required for this incubation phase.
• Experience with enterprise software transformation or legacy system integration is a significant plus.

What You’ll Receive:

• A Blank Canvas and Live Ammunition: The rare opportunity to build a "0-to-1" product while immediately deploying it into the real-world operations of a regional giant. No "sandbox" projects here, you’ll be shipping code that moves people and goods on day one. This is a huge opportunity to create impact in our region. 
• Architecting the Engine: We’re a lean, impact-obsessed team operating with total autonomy. You’ll be free from corporate bureaucracy and legacy baggage, focused entirely on building the core orchestration layer and agentic frameworks that will serve as the "brain" of the region’s enterprises.
• Direct Collaboration with Leadership: Direct engagement with Careem and enterprise client leadership, in addition to working side-by-side with the WorkOS founding team including Magnus Olsson (Careem’s original Co-founder). 
• Competitive Compensation: Including direct equity in this new division. Our philosophy is meritocratic: we want you to own a meaningful stake in the value you create.