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 the 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 Machine Learning Engineer on a builder track.

This role is for someone who wants to take ML from “cool idea” to “running in production”. You will work across data, modeling, and software engineering to build, deploy, and operate models that improve customer experience, reduce risk, and unlock operational efficiency.

With the advancement of AI, we care more about fundamentals than buzzwords. Use AI assistants to move faster, but always own correctness, safety, privacy, and performance.

Your responsibilities

• Build and ship ML systems
  • Develop and deploy ML models and services that solve real business problems.
  • Write production-quality code, tests, and documentation.
• Own the full model lifecycle
  • Help with data understanding, feature creation, training, evaluation, and iteration.
  • Set up offline and online evaluation, and monitor performance after release.
• Make ML reliable in production
  • Improve model serving reliability, latency, and cost.
  • Implement monitoring for data drift, model drift, and key quality metrics.
  • Participate in incident response and postmortems when needed.
• Work with data and platform teams
  • Partner with data engineers and platform engineers on pipelines, event-driven signals, and data quality.
  • Use event streaming patterns when appropriate (near-real-time features, online scoring, CDC signals).
• Build tools that help others move faster
  • Contribute to reusable training and serving components (templates, libraries, CI/CD, feature pipelines).
  • Help enable safe self-serve ML and AI usage across teams.
• Use AI tools thoughtfully
  • Use AI to accelerate prototyping, debugging, documentation, and test generation.
  • Validate outputs, document assumptions, and protect sensitive data.

Your expertise (must have)

• Fresh graduate or < 1 year of relevant experience (internships and projects count).
• Solid programming fundamentals in Python (preferred) or another language used for ML systems.
• Strong fundamentals in:
  • Data structures and algorithms (enough to write efficient, reliable code)
  • Probability and statistics basics
  • ML fundamentals (supervised learning, overfitting, validation, metrics)
• Comfort working with data using SQL and/or Python.
• A problem-solving mindset and curiosity to learn quickly.
• Clear communication and a collaborative approach.

Nice to have

• Experience with common ML libraries (scikit-learn, PyTorch, TensorFlow) through coursework or projects.
• Familiarity with model deployment patterns (APIs, batch scoring, streaming/online scoring).
• Exposure to MLOps concepts (experiment tracking, model registry, CI/CD, monitoring).
• Familiarity with cloud (GCP/AWS) and containers (Docker) is a plus.
• Understanding of responsible AI and privacy (PII handling, access control, evaluation).
• Experience using AI assistants responsibly for coding and analysis.

What success looks like

• You ship at least one end-to-end ML improvement (model, feature, or service) that runs reliably.
• You can explain model performance clearly: what improved, what did not, and why.
• Monitoring is in place for your models, and you react quickly when metrics drift.
• You reduce manual effort for the team by adding a reusable component, template, or automation.

Summary:

The Cloud team at Lucid is currently seeking a Senior Site Reliability Engineering role. In this position, the individual will be responsible for providing
reliability to the cloud infrastructure that enabled Lucid Motors' cloud-based services and internal systems.

Responsibilities:

• Provide Reliability Engineering to cloud services deployed and managed in the region of KSA.
• Continuous delivery (CI/CD) using ArgoCD, Jenkins, Maven, and Docker.
• Architect cloud systems in highly available design, ensuring Disaster Recovery (DR) measures are in place.
• Containerization and deployment of microservices and data pipeline on Kubernetes using Helm installation.
• Advocate for a DevOps culture of automation and engineering best practices to enable development teams.
• Auto-scale and monitoring performance for Kubernetes and running applications using Prometheus and Grafana or similar tools.
• Performing SRE activities such as availability and reliability monitoring and reports.
• Deploy, configure and maintain tools such as Kafka, Spark, Trino, Airflow, MQTT, and Microservices.
• Setting up infrastructure as a service using Terraform.
• Work and deploy using the codebase repositories in GitLab, along with participation in the peer review activities.
• Support No-SQL databases such as Elastic Search, Mongo, Cassandra, and other open sources services.
• Setup and monitor various applications and services. Continuously enhance the alerts and automate the recovery process.
• Articipate in the on-call rotation to keep up the service SLA per the business needs.
• Work with Product Owners, engineering managers, and other team members in Agile Scrum and Kanban mode.
• Take appropriate actions by doing impact analysis during the incidents.

Requirements and Skills:

• B.S. or M.S. degree in Computer Science, Engineering, or equivalent field.
• Can speak English fluently to communicate with teams across geographical regions.
• +6 years of experience in SRE or DevOps Engineering.
• +5 years of experience deploying and maintaining systems on Oracle cloud (OCI), and Amazon web services (AWS).
• +3 years of experience in Terraform.
• +3 years of experience in Kubernetes.
• +3 years of experience with tools such as Jenkins, ArgoCD, etc. to build automation and CI/CD pipelines.
• Professional experience in Programing or scripting languages using Python, Go, Bash/Shell, or others.
• Experience in administrative operations knowledge in RDBMS (e.g. PostgreSQL, MySQL), and NoSQL databases (e.g. MongoDB).
• Moderate experience in distributed computing for running data systems using Spark, Hive, Zookeeper, and Kafka.
• Moderate experience in debugging tools and troubleshooting performance bottlenecks at the infrastructure or at the application tier.
• Good to have experience with Config Management using Ansible, Chef, Puppet, or others.

Job Summary

Design, develop, and maintain backend services and APIs that power Hala services web and mobile platforms.
Build and optimize scalable, secure, and high-performance systems to support growing user and data demands.

Key Responsibilities

• Design, develop, and maintain backend services and APIs that power Hala services web and mobile platforms.

• Build and optimize scalable, secure, and high-performance systems to support growing user and data demands.

• Collaborate closely with product managers, frontend engineers, and other teams to define technical requirements and deliver end-to-end solutions.

• Integrate with third-party systems, internal APIs, and external services to enable seamless functionality.

• Write clean, maintainable, and testable code following best practices and team standards.

• Implement authentication, authorization, and data protection mechanisms to ensure system security and integrity.

• Contribute to architecture discussions and technical design reviews to ensure scalable and future-proof backend solutions.

• Monitor system performance, identify bottlenecks, and implement performance improvements.

• Participate in code reviews, mentoring, and continuous improvement of engineering processes.

• Collaborate in deploying and maintaining services in staging and production environments (e.g., via CI/CD pipelines).

• Support troubleshooting, debugging, and resolving production issues in a timely manner.

Qualifications

• Education: Bachelor’s degree in Computer Science, Software Engineering, or a related field (or equivalent practical experience).

• Experience: 1+ years of backend development experience in a production environment.

• Strong proficiency in one or more backend languages (.NET, Node.js, Python, Go, or Java).

• Experience with RESTful APIs and/or GraphQL design and development.

• Solid understanding of microservices architecture and event-driven systems.

• Familiarity with databases (SQL and NoSQL), such as PostgreSQL, MySQL, MongoDB, or Redis.

• Hands-on experience with cloud platforms (OCI, AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes).

• Knowledge of CI/CD pipelines, automated testing, and modern DevOps practices.

• Understanding of security principles, authentication (OAuth2, JWT), and data privacy best practices.

• Excellent problem-solving skills, teamwork, and communication abilities.

• Strong focus on performance, scalability, and reliability.