We are looking for a Senior Quantum Field Engineer. As a Senior Quantum Field Engineer, you’ll be part of a team whose mission is to lead IonQ on its journey to build the world’s best quantum solutions and solve the world’s most complex problems.  Field Engineering sits at the intersection of customers, markets, products and product teams, algorithms, applications, innovation and strategy - this is the team where ideas become applied and have impact.

Join a nimble team of scientists, engineers, salespeople, marketers, business developers, and product managers to drive an entirely new quantum computing business. We’re seeking versatile engineers and architects skilled in technical sales, technical demos and customer interactions who feel energized to deliver IonQ’s quantum computing products and quantum applications. 

Responsibilities:

• Inspire prospective clients by explaining IonQ’s strategy, portfolio and answering technical questions about quantum portfolio (compute, network, security, sensing and space) and quantum applications.
• Lead and shepherd client discussions, inspiring them to see how quantum applications can be implemented in their business domain.
• This includes working through business needs and mapping Quantum Algorithms (financial services, bioscience, chemistry and materials, optimization, generative AI, and other domains) into application code and executing Proof-of-Concepts together with the IonQ Application team.
• Share insights from clients with the IonQ Product Management and Engineering teams such that client feedback is incorporated into our products.
• Navigate competitive objection handling
• Translate business needs expressed by our clients into technical work projects in collaboration with other team members.
• Create assets to explain features of our quantum applications and other IonQ quantum products.
• Move dialogs from initial ideation to focused exploration domain through to proof-of-concept and ultimately into production workflows.
• Lead client discovery sessions for business oriented use cases that uncover potential overlap with development of useful quantum algorithms together with the IonQ Application team
• Partner with marketing, developer relations and business development to grow awareness of IonQ in the world at large.
• Attend industry conferences, as needed, to talk to client and support our booth activities.
• Some travel expected in the US (20%) but opportunities for global travel are available as well for client meeting and IonQ conference activities.
• This is a technical customer-facing role with the appropriate balance of compensation acceleration for success and a base salary to ensure that credibility and technical correctness always comes first.

You’d be a good fit with:

• 5 years of experience in technical customer-facing roles or equivalent capacity.  The ability to communicate (at the various context-appropriate levels of depth) and persuade clearly, have strong EQ, and other customer facings skills are critical.
• Bachelor’s degree or above in Computer Science, Machine Learning, Data Science, or other STEM field, such as Chemistry, Physics or Engineering
• Motivated learner with a strong interest in quantum computing.

You’d be a great fit with: 

• Masters or PhD in a STEM field, perhaps adjacent to quantum computing.
• Time on the customer side in various verticals included leadership roles - this provides customer empathy
• Hands-on experience with Qiskit, Cirq or other quantum computing SDK.
• Proficient in Python and Jupyter Notebooks.
• Expert architecture skills across various technologies (“full stack skills”)
• Experience leading technical events.

Location: This role is based in Saudi Arabia or Dubai, UAE, and requires candidates to be locally based in one of these locations.
Travel: 20% travel domestically and globally
Job ID: 1374

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.

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 AI Engineer on a builder track.

This role sits between software engineering and applied AI. You will build AI-powered features end-to-end: from turning a product problem into an AI approach, to building pipelines and evaluation, to shipping reliable services in production.

You’ll work with both classical ML and generative AI (LLMs, RAG, agents) where they make sense. With the rapid pace of AI, we care more about fundamentals than buzzwords. Use AI assistants to move faster, but always own correctness, privacy, safety, and user impact.

Your responsibilities

• Build AI products that ship
  • Design and implement AI-powered features and internal tools.
  • Integrate models into real systems (APIs, workflows, dashboards, and operational processes).
• Work with LLMs in a production-ready way
  • Build retrieval-augmented generation (RAG) pipelines: data sourcing, chunking, embeddings, retrieval, and prompt templates.
  • Build agent-style workflows when needed (tool use, guardrails, and deterministic fallbacks).
• Own evaluation and quality
  • Define what “good” means: success metrics, offline tests, and human-in-the-loop review.
  • Set up evaluations for quality, safety, latency, and cost.
• Make AI reliable and safe
  • Add observability: logging, tracing, and monitoring for quality regressions.
  • Implement privacy and security controls (PII handling, access control, redaction where needed).
  • Participate in incident response and postmortems when AI systems misbehave.
• Partner across teams
  • Work with product, data, design, and engineering stakeholders to translate messy problems into measurable solutions.
  • Collaborate with platform teams to use existing data pipelines, event streams, and AI tooling responsibly.
• Use AI tools thoughtfully
  • Use AI assistants for prototyping, debugging, and documentation.
  • 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 backend services.
• Strong foundations in:
  • Software engineering basics (APIs, testing, reliability)
  • Data handling (SQL and/or dataframes)
  • ML/AI fundamentals (training vs. inference, evaluation, overfitting intuition)
• Clear communication and a collaborative approach.

Nice to have

• Hands-on experience with LLMs and/or RAG from projects (LangChain/LlamaIndex or similar patterns).
• Familiarity with model serving and deployment (REST/gRPC services, batch jobs, streaming consumers).
• Exposure to MLOps concepts (experiment tracking, model registry, monitoring).
• Familiarity with vector databases, search, or information retrieval.
• Understanding of responsible AI, privacy, and security (PII handling, access control, prompt injection awareness).
• Experience using AI assistants responsibly for coding and analysis.

What success looks like

• You ship at least one AI feature or internal tool that is used by real users.
• You set up a simple evaluation and monitoring loop so the system improves over time.
• Your solutions balance quality, latency, and cost, with clear tradeoffs.
• When the AI output is wrong or risky, you can debug, mitigate, and explain why.

All qualified individuals are encouraged to apply.

About Armada

Armada delivers sovereign, industrial-grade AI infrastructure designed to operate where traditional cloud and centralized data center models fall short. Our platform includes Atlas as the control plane, Galleon modular edge data centers powered by the Armada Edge Platform, and Leviathan, Armada’s AI Factory, which partners with Bridge, our GPU-as-a-Service offering. Together, these capabilities enable enterprises and governments to deploy, operate, and scale AI workloads securely, efficiently, and close to where data is generated.

Saudi Arabia is Armada’s operational anchor for the ME region. As we scale, we are intentionally building a team of senior, versatile operators who can both get systems live and own customers long-term. This role is designed for engineers who want full lifecycle ownership, not narrow scope.

Role Overview

The Senior Forward Deploy Engineer is a hybrid role responsible for hands-on deployment execution and ongoing technical account ownership for Armada customers across ME. This role combines the intensity and depth of a Forward Deploy Engineer with the long-term customer ownership of a Technical Account Manager.

In the early phases of customer engagement, this role leads deployments, platform bring-up, and initial workload execution. Once customers are live, the same engineer remains the primary technical owner, driving adoption, operational maturity, and expansion.

This role reports into the Sr. Director of Customer Success & Delivery, EMEA & ANZ and is intentionally designed to avoid split ownership between deployment and post-sale success. Success is measured by speed to production, customer confidence, platform adoption, retention, and expansion.

Key Responsibilities

Deployment execution and platform bring-up

• Lead end-to-end deployment of Armada platforms including Atlas, Galleon with AEP, and Leviathan AI Factory integrated with Bridge GPU-as-a-Service
• Own on-site and in-country deployments across Saudi Arabia and the broader ME region
• Own infrastructure bring-up, platform configuration, and production readiness validation
• Make real-time technical decisions across hardware, networking, Kubernetes, storage, and GPU layers

Technical account ownership and customer success

• Serve as the primary technical point of contact for assigned customers post go-live
• Own the technical success plan, adoption milestones, and operational maturity roadmap
• Build trusted, long-term relationships with customer engineering, IT, OT, and security team
• Lead technical governance discussions, roadmap planning, and platform optimization conversations

Joint Success Plan ownership

• Build, maintain, and actively drive Joint Success Plans (JSPs) for each assigned customer
• Align deployment milestones, platform adoption, and operational maturity to customer business objectives
• Use the Joint Success Plan as the primary framework for prioritization, execution, risk management, and value tracking
• Regularly review progress against success plans with customer stakeholders and Armada leadership
• Ensure JSPs inform deployment sequencing, adoption strategy, roadmap discussions, and expansion planning
• Surface risks, dependencies, and blockers early and drive resolution with clear ownership

Time-to-value acceleration and adoption

• Reduce time-to-try and time-to-value by unblocking workloads and accelerating early production use cases
• Drive adoption across new workloads, business units, and countries
• Identify expansion opportunities including additional Galleon deployments and Leviathan AI Factory capacity through Bridge GPUaaS

Operational excellence and reliability

• Ensure customer environments remain stable, secure, and production-ready
• Proactively identify scaling risks, architectural gaps, and technical debt
• Coordinate with Product, Engineering, and Support teams to resolve issues efficiently

Sovereign data, security, and compliance execution

• Operate confidently within Saudi and regional sovereign data and security requirements
• Support security validation, audits, and governance processes as required by customers
• Maintain disciplined access control, documentation, and operational hygiene

Field leadership and mentorship

• Act as a senior technical presence for ND8 customers, setting the bar for execution and professionalism
• Mentor junior FDEs, TAMs, and delivery engineers as the region scales
• Contribute to deployment standards, runbooks, and repeatable best practices

Cross-functional collaboration

• Partner closely with the Sr. Director of Customer Success & Delivery, EMEA & ANZ on customer priorities and escalations
• Work with Sales on expansion planning while maintaining a trusted post-sale posture
• Provide structured feedback to Product and Engineering based on real customer usage

Qualifications and Experience

• 8+ years of experience in infrastructure, platform engineering, SRE, forward-deployed engineering, or technical account roles
• Proven ability to own both hands-on delivery and long-term customer technical relationships
• Deep technical expertise across Linux, networking, Kubernetes, storage, and GPU-accelerated compute
• Strong troubleshooting skills in live, production environments
• Experience working directly with customers in regulated, high-stakes settings
• Willingness to travel across Saudi Arabia and the broader ME region
• Clear, confident communication style suitable for executive and engineering audiences

Preferred Experience

• Experience with edge compute, modular data centers, or distributed infrastructure
• Familiarity with AI workloads, GPU clusters, and high-performance computing environments
• Exposure to sovereign or national-scale customer environments
• Experience operating in Saudi Arabia, UAE or across ME
• Comfort operating with ambiguity and owning outcomes end to end

What Success Looks Like

• Customer environments reach production quickly and operate reliably
• The same engineer who deploys the platform remains the trusted technical owner
• Adoption expands across sites, workloads, and teams without handoff friction
• Customers view Armada as a strategic AI infrastructure partner due to consistent technical ownership

Key Responsibilities

• Develop and deploy AI, machine learning, and generative AI solutions.
• Build AI-powered tools such as chatbots, copilots, and workflow automation.
• Prepare and process data for model training, testing, and deployment.
• Integrate AI models into products and internal systems through APIs.
• Fine-tune, evaluate, and monitor model performance.
• Work closely with Product, Engineering, Data, and business teams to identify AI use cases.
• Ensure AI solutions follow data privacy, security, and governance standards.
• Document AI models, workflows, and technical designs.

Requirements

• Bachelor’s degree in Computer Science, AI, Data Science, Software Engineering, or related field.
• 2–5 years of experience in AI, machine learning, data science, or software engineering.
• Strong Python programming skills.
• Experience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn.
• Knowledge of LLMs, NLP, embeddings, vector databases, and RAG.
• Experience with APIs, cloud platforms, and production deployment.
• Strong problem-solving and collaboration skills.

Preferred

• Experience with OpenAI, Azure OpenAI, AWS Bedrock, or Google Vertex AI.
• Experience with LangChain, LlamaIndex, Pinecone, FAISS, or similar tools.
• Experience in fintech, banking, payments, or regulated environments.

Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth.
The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner…

What you will be doing?
As a Data Engineer, your role involves crafting and maintaining robust data pipelines, utilising Python and SQL, to ensure efficient extraction, transformation, and loading (ETL) of data.

Your responsibilities will include:

• Data Pipeline Development: Building and optimising data pipelines to facilitate seamless data flow across systems and platforms.
• Database Management: Managing databases, ensuring their integrity, and implementing data storage and retrieval solutions.
• Cloud Services Integration: Leveraging cloud services such as MS Azure, GCP, and AWS to architect and deploy scalable data solutions.
• Machine Learning Integration: Collaborating with teams to integrate machine learning models into data pipelines for enhanced data processing.
• Utilising Spark & Kafka: Implementing and working with Spark and Kafka for real-time data processing and analytics.

What we are looking for?

• 2-5 years: Data Engineer
• Proficiency in Python, SQL, and database management.
• Experience with Data Pipelines ETL, Cloud Services (MS Azure, GCP, AWS), ML Modeling, Spark & Kafka.
• Proven problem-solving skills and a solution-oriented mindset.
• Experience working with business stakeholders either internally or externally
• Excellent communication skills to collaborate effectively within teams and with stakeholders.
• Strong business acumen with an interest in business-facing roles.
• Adaptability and a start-up mentality to thrive in a dynamic environment.
• Minimum of a bachelor's degree in Computer Science, Electronics, and Communication Engineering degrees.

Artefact is the place to be: come and build the future of data and AI

Innovation: We have a passion for creating impacting projects and believe innovation can come from anyone.
Action: We make things rather than telling people how to make them.
Collaboration: We believe in bringing talented people together, winning together, and in learning from each other.

Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth.
The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner…

What you will be doing?
As a Data Engineer, your role involves crafting and maintaining robust data pipelines, utilising Python and SQL, to ensure efficient extraction, transformation, and loading (ETL) of data.

Your responsibilities will include:

• Data Pipeline Development: Building and optimising data pipelines to facilitate seamless data flow across systems and platforms.
• Database Management: Managing databases, ensuring their integrity, and implementing data storage and retrieval solutions.
• Cloud Services Integration: Leveraging cloud services such as MS Azure, GCP, and AWS to architect and deploy scalable data solutions.
• Machine Learning Integration: Collaborating with teams to integrate machine learning models into data pipelines for enhanced data processing.
• Utilising Spark & Kafka: Implementing and working with Spark and Kafka for real-time data processing and analytics.

What we are looking for?

• 2-5 years: Data Engineer
• Proficiency in Python, SQL, and database management.
• Experience with Data Pipelines ETL, Cloud Services (MS Azure, GCP, AWS), ML Modeling, Spark & Kafka.
• Proven problem-solving skills and a solution-oriented mindset.
• Experience working with business stakeholders either internally or externally
• Excellent communication skills to collaborate effectively within teams and with stakeholders.
• Strong business acumen with an interest in business-facing roles.
• Adaptability and a start-up mentality to thrive in a dynamic environment.
• Minimum of a bachelor's degree in Computer Science, Electronics, and Communication Engineering degrees.

Artefact is the place to be: come and build the future of data and AI

Innovation: We have a passion for creating impacting projects and believe innovation can come from anyone.
Action: We make things rather than telling people how to make them.
Collaboration: We believe in bringing talented people together, winning together, and in learning from each other.