ai engineer

devops engineer

full stack engineer

data engineer

infrastructure engineer

distributed systems engineer

NVIDIA AI

<div>
 Job Requisition ID
 <br/>
 <br/>
 JR2024318
 <br/>
 <br/>
 Job Category
 <br/>
 <br/>
 Engineering
 <br/>
 <br/>
 Time Type
 <br/>
 <br/>
 Full time
 <br/>
 <br/>
 For more than two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics. With a rare focus on this field, we offer specialized platforms for the gaming, professional visualization, data center and automotive markets. Our work is at the center of the most consequential mega-trends in technology - virtual reality, artificial intelligence and self-driving - and there has never been a more exciting time to join our team.
 <br/>
 <br/>
 Among other internal services, we develop and operate a globally distributed data storage and auth services based on microservice architecture. We&rsquo;re looking for a new team member who will help us to improve our auth and storage systems, creating new microservices, improving existing ones, doing regression, stress and performance testing.
 <br/>
 <br/>
 <strong>
  What You'll Be Doing
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Participate in architecture design process of our distributed backend systems
  </li>
  <li>
   Maintain and improve existing authentication and authorization microservices along with developing new ones (OCaml / Rust)
  </li>
  <li>
   Connect with customers and provide technical support for APIs and client use cases
  </li>
  <li>
   Improve unit and integration tests coverage
  </li>
  <li>
   Participate in code review process
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What We Need To See
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Degree in Computer Science, Computer Engineering, or closely related field
  </li>
  <li>
   5+ years of relevant experience, ideally in the area of system programming
  </li>
  <li>
   Experience with programming and debugging skills in Linux environment
  </li>
  <li>
   Deep understanding of HTTP and REST or other HTTP-based RPC protocols, e.g: Twirp or gRPC
  </li>
  <li>
   Experience with multi-threaded and asynchronous network programming concepts and frameworks (NodeJS, Akka, Tornado, Erlang/OTP, Rust/Tower)
  </li>
  <li>
   Strong habit to verify and document your work
  </li>
  <li>
   Understanding deployment process and networking in Kubernetes
  </li>
  <li>
   Excellent communication skills in verbal and written technical English, ability to present the current status and final project deliveries
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Ways To Stand Out From The Crowd
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Hands-on experience with Cassandra or similar databases and general curiosity about distributed systems and algorithms
  </li>
  <li>
   Understanding of how modern protocols such as OAuth and OIDC work. Expertise in Active Directory and LDAP would be a big plus.
  </li>
  <li>
   Track record of building secure systems handling sensitive data
  </li>
  <li>
   Ability to debug and profile code on Linux: perf, tcpdump / Wireshark, strace, Valgrind, etc
  </li>
  <li>
   Understanding functional programming paradigm and static strong type systems (relevant knowledge of Haskell, OCaml, F#, Scala, Rust, etc)
   <br/>
   <br/>
  </li>
 </ul>
 With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most brilliant and talented people on the planet working for us and, due to unprecedented growth, our best-in-class engineering teams are growing fast. If you're a creative and autonomous engineer with a genuinely real passion for technology, we want to hear from you.
</div>


Senior System Software Engineer

Binance

<div><div>Binance is a leading global blockchain ecosystem behind the world&rsquo;s largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world.</div><div></div><div><br>
The Know Your Customer Technology Team at Binance is dedicated to building a state-of-the-art platform that ensures a seamless onboarding experience for our customers. Our focus is on developing a large-scale KYC platform, launching innovative products, and integrating regional and global compliance vendors. We prioritize the responsible use of AI/ML technologies while adhering to both global and local regulatory standards. Join us and be part of a team that is at the forefront of innovation and compliance in the financial technology industry.</div>
<h3 class="jobSectionHeader"><b>Responsibilities</b></h3><ul>
<li>Collaborate with relevant stakeholders to convert business requirements into services with solid code and meaningful tests.</li>
<li>Proactively initiate performance tuning, troubleshoot incidents, etc.</li>
<li>Write and maintain high-quality technical documentation.</li>
<li>Write high quality code, follows best practices and advocates for engineering excellence.</li>
<li>Collaborate across other engineering teams and mentor junior members of the team.</li>
</ul><h3 class="jobSectionHeader"><b>Requirements</b></h3><ul>
<li>Bachelor's degree in computer science, engineering, or equivalent industry experience.</li>
<li>Minimum 4 years of professional experience in building high-throughput distributed applications.</li>
<li>Proficient in core Java and the Spring Framework.</li>
<li>Proficient in MySQL, and familiar with at least one NoSQL database.</li>
<li>Proficient in distributed system design, and familiar with at least one messaging middleware and the underlying design principles.</li>
<li>A quick learner with the ability to perform under pressure.</li>
<li>Able to collaborate with the remote team across different time zones.</li>
<li>
<p>Bilingual English/Mandarin is required to be able to coordinate with overseas partners and stakeholders.</p>
</li>
</ul><h3 class="jobSectionHeader"><b>Desirable</b></h3><ul>
<li>Performance tuning experience on JVM, SQL, RPC, etc.</li>
<li>Experience in KYC or Compliance is a plus.</li>
</ul><div><b>Why Binance</b></div><ul><li>Shape the future with the world&rsquo;s leading blockchain ecosystem</li><li>Collaborate with world-class talent in a user-centric global organization with a flat structure</li><li>Tackle unique, fast-paced projects with autonomy in an innovative environment</li><li>Thrive in a results-driven workplace with opportunities for career growth and continuous learning</li><li>Competitive salary and company benefits</li><li>Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)</li></ul><div></div><div><br>
Binance is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success.</div><div><i>
By submitting a job application, you confirm that you have read and agree to our </i><b><i>Candidate Privacy Notice</i></b><i>.</i></div>
<p>
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.</p></div>

Backend Engineer (Java) - KYC Tech

Janus Digital Global

<div>
 <strong>
  About Janus Digital
  <br/>
  <br/>
 </strong>
 <strong>
  Janus Digital is the agentic AI platform that runs the world's real assets. Based in the UAE with global operations, our enterprise platform acts as the central operating system for intelligent buildings, and we earn only on the additional value we create.
  <br/>
  <br/>
 </strong>
 <strong>
  Buildings account for nearly 40% of global energy consumption and carbon emissions, yet most are still run by fragmented systems that react to problems instead of preventing them. We exist to change that, proving that AI for Good is also good business.
  <br/>
  <br/>
 </strong>
 <strong>
  Unlike language models that can guess, our platform is grounded in physics: thermodynamics, pressure dynamics, energy conservation, and fluid mechanics. It builds a live, millimetre-accurate picture of every structure, monitors how energy, water, and air move through every system in real time, anticipates maintenance weeks ahead, and makes thousands of autonomous micro-adjustments around the clock. It calculates; it does not guess.
  <br/>
  <br/>
 </strong>
 The technology is not new, it is battle-hardened: development began in 2009 and has matured through four generations of real-world deployment, built on 15+ years of foundational R&amp;D, 76 granted patents, and over $100M invested. The platform is proven across 10,000+ building datasets in 253 cities, trusted by Fortune Global 500 companies, sovereign wealth funds, and premium hospitality brands, spanning hospitals, airports, malls, theme parks, power grids, and manufacturing. Typical outcomes include around 29% energy savings, 99% equipment-risk detection before failure, and full deployment in 14 days with no phased rollout.
 <br/>
 <br/>
 <strong>
  About This Role
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   This role sits within the AI Office, the team responsible for designing, building, and running Janus Digital's AI platform and the engineering capability behind it. Reporting to the Head of AI Office, the engineer joins a small, senior group working at the core of how the company applies artificial intelligence across its global operations
  </li>
  <li>
   We are looking for a full-stack AI engineer who combines hands-on software delivery with genuine platform depth&mdash;someone who has built and operated systems to a banking-grade standard and is fluent across modern cloud infrastructure, AWS in particular. That background is central to the work: the AI Office ships production systems the wider organisation depends on, where reliability, security, and clean architecture are not optional. The same instincts that keep banking and financial platforms dependable are exactly what this role demands
  </li>
  <li>
   As part of the AI Office, the engineer will own meaningful parts of the platform end to end&mdash;backend services, user-facing interfaces, identity and access, and the AI agent and integration layers&mdash;and will work alongside existing engineers and the CTO function on cloud deployment and reliability. The objective is a platform engineered to a product standard: secure, scalable, observable, and built to evolve as the company and the field do. This engineer is central to making that real
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What you'll do
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Build and own the product across the stack: backend services and APIs in Python and TypeScript; frontend interfaces in React (or equivalent) for web dashboards, administrative surfaces, and AI agent interaction layers
  </li>
  <li>
   Build cloud-native software on AWS (primary), and across the wider cloud ecosystem where relevant, that assumes it will run in a managed, containerized cluster environment
  </li>
  <li>
   Design and implement enterprise-grade authentication and authorization: SSO (SAML/OIDC), SCIM provisioning, RBAC, and fine-grained IAM
  </li>
  <li>
   Design the platform for multi-tenancy from the ground up: configuration isolation, provisioning flows, usage metering, and the operational tooling needed to run it reliably at scale
  </li>
  <li>
   Build and deploy production AI agents using MCP and streaming APIs; design multi-model orchestration across Claude, Gemini, and other models as the landscape evolves
  </li>
  <li>
   Contribute to and evolve the memory and knowledge architecture at the core of the platform&mdash;a structured, multi-graph, file-based system underpinning institutional intelligence across the company. This is among the hardest and most consequential engineering problems on the platform
  </li>
  <li>
   Architect the platform as a composition of isolated, independently deployable microservices&mdash;each functional domain (finance tools, marketing stack, knowledge layer, agent runtime) a discrete service with well-defined APIs between them
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 <strong>
  What we're looking for
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   5+ years in a full-stack software engineering role, with shipped, production systems at scale&mdash;backend and frontend both visible in your GitHub history
  </li>
  <li>
   Direct experience building or operating banking, fintech, or comparable high-reliability, regulated software; you understand first-hand the reliability, security, and compliance bar these environments demand
  </li>
  <li>
   Demonstrable multi-tenant and/or distributed-systems experience: tenant isolation, provisioning flows, and the operational tooling that keeps distributed systems running in production
  </li>
  <li>
   API design for external consumers: versioning, authentication, rate limiting, and documentation standards
  </li>
  <li>
   Security fundamentals: zero-trust principles, data isolation, audit logging, DLP&mdash;security as a design constraint, not a post-launch checkbox
  </li>
  <li>
   Fluent with agentic development tooling&mdash;Claude Code, Codex, and CLI-based AI workflows&mdash;used with discipline and judgment, not as a substitute for engineering thinking
  </li>
  <li>
   Active GitHub profile mandatory&mdash;applications without a demonstrable commit history will not be considered
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Nice to have
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Broad, hands-on cloud experience: AWS (primary), with working knowledge across the wider cloud ecosystem (GCP/Azure). You architect cloud-native systems, not just deploy to a single VM
  </li>
  <li>
   Containerization and cloud-native deployment in production: Docker and Kubernetes; you write software that assumes it will run in a managed cluster environment
  </li>
  <li>
   Strong Python and TypeScript; React or an equivalent modern frontend framework; genuine comfort moving between layers of the stack
  </li>
  <li>
   Enterprise identity and access management implemented in production&mdash;SSO (SAML/OIDC), SCIM, RBAC, Okta or Azure AD&mdash;not just read about
  </li>
  <li>
   AI/LLM integration: MCP server development, function calling, streaming APIs, and multi-model orchestration
  </li>
  <li>
   Experience with core banking, payments, or other regulated financial systems (transaction integrity, settlement, KYC/AML data flows, and similar)
  </li>
  <li>
   Vertex AI / Google AI Studio / Claude API / Gemini Enterprise
  </li>
  <li>
   Slack Apps (Bolt Framework, Block Kit) and Google Workspace integrations
  </li>
  <li>
   Agent memory patterns, structured knowledge graphs, or evolving AI context-management architectures
  </li>
  <li>
   Regional compliance experience (GDPR, Singapore PDPA, UAE data protection frameworks)
  </li>
  <li>
   Familiarity with Terraform or equivalent IaC tooling (ownership sits with the infrastructure team, but fluency helps)
  </li>
  <li>
   Go or Rust for performance-critical components
  </li>
  <li>
   Experience taking an internal platform or product through significant scale or its first external users
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Benefits
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Competitive compensation with performance-based incentives tied to delivery quality and client outcomes
  </li>
  <li>
   A specialized domain-expert role at the absolute frontier of Agentic AI and autonomous building intelligence
  </li>
  <li>
   Hands-on engagement with prestigious, diverse real estate portfolios (commercial offices, hotels, malls, and mixed-use developments)
  </li>
  <li>
   Direct collaboration with our global Head of AI team
  </li>
  <li>
   Clear career progression paths into senior consulting or regional delivery leadership roles
  </li>
  <li>
   Sponsorship and support for professional development, including certifications in building services and energy management
  </li>
 </ul>
</div>


AI Software Engineer

Ultahost, inc

<div><div>UltaHost is looking for a Senior Internal Security &amp; Security Operations Engineer to take ownership of internal security and help strengthen the protection of our workforce, identities, systems, and day-to-day operations.</div><div></div><div><br>
This is a senior, hands-on technical role with responsibility across Identity &amp; Access Management (IAM), internal security, security monitoring, SOC operations, and incident response. The position requires someone who can combine strong technical security expertise with a structured and operational approach to access control, monitoring, investigation, and risk reduction.</div><div></div><div><br>
You will be responsible for securing employee and contractor identities, privileged access, credentials, internal systems, endpoints, VPN and remote access, while ensuring that appropriate security controls are implemented and maintained throughout the account and access lifecycle.</div><div></div><div><br>
A key part of the role will also involve actively monitoring security events and investigating suspicious activity across authentication systems, endpoints, internal applications, and cloud/SaaS environments. You will take an active role in identifying potential threats, investigating security incidents, collecting evidence, containing risks, coordinating remediation, and ensuring corrective actions are followed through to closure.</div><div></div><div><br>
You will work closely with HR, IT, system owners, and other technical teams to improve access governance, strengthen internal security controls, enhance detection and response capabilities, and reduce security risks across UltaHost&rsquo;s internal environment.</div><div></div><div><br>
We are looking for someone who is comfortable taking end-to-end ownership &mdash; from implementing preventive controls and improving security monitoring to investigating real incidents and driving security improvements across the organization.</div><div></div><div><b><br>
What You&rsquo;ll Own</b></div><div><b>
Identity, Access &amp; Credential Security</b></div><ul><li>
Design and maintain RBAC across departments, roles, and critical systems.</li><li>
Manage MFA, SSO, PAM, password vaults, API keys, SSH keys, recovery codes, and secrets.</li><li>
Own security controls around onboarding, role changes, temporary access, contractor access, and offboarding.</li><li>
Identify and remove shared, dormant, unnecessary, and excessively privileged accounts.</li><li>
Conduct regular access reviews and maintain approval and audit evidence.</li></ul><div><b>
Security Monitoring &amp; Incident Response</b></div><ul><li>
Monitor and investigate alerts from SIEM, EDR, IDS/IPS, authentication systems, cloud/SaaS platforms, internal applications, and endpoints.</li><li>
Investigate suspicious logins, compromised accounts, credential leaks, malware, privilege abuse, insider risk, and unauthorized access.</li><li>
Collect evidence, contain threats, coordinate recovery, and drive corrective actions through closure.</li><li>
Maintain detection rules, alert quality, incident records, escalation paths, and response playbooks.</li><li>
Lead internal security incidents and support infrastructure/product incidents involving identities or credentials.</li></ul><div><b>
Internal Systems &amp; Workforce Security</b></div><ul><li>
Define security requirements for laptops, VPN and remote access, email, code repositories, support platforms, finance tools, and administrative systems.</li><li>
Work closely with HR and IT on joiner/mover/leaver processes and internal security investigations.</li><li>
Support security awareness, phishing prevention, and secure handling of sensitive information and credentials.</li></ul><div><b>
What We&rsquo;re Looking For</b></div><ul><li>
5+ years of hands-on experience in internal security, IAM, SOC/security operations, incident response, IT security, or a closely related role.</li><li>
Practical experience with RBAC, MFA, SSO, PAM, identity providers, password management, account lifecycle management, and access auditing.</li><li>
Hands-on experience with SIEM, EDR, IDS/IPS, centralized logging, authentication logs, alert triage, and case management.</li><li>
Proven ability to investigate compromised accounts, malware, credential leaks, suspicious authentication activity, insider risk, and unauthorized access.</li><li>
Strong understanding of Linux access, SSH, VPN, endpoints, cloud/SaaS administration, email security, and remote-workforce security.</li><li>
Strong organizational skills and the ability to enforce security controls while collaborating with HR, IT, managers, and system owners.</li></ul><div><b>
Preferred Background</b></div><div>
Experience in web hosting, cloud infrastructure, data centers, SaaS, fintech, MSSP, or another distributed technology environment is highly valuable. Preferred certifications include Security+, CySA+, GCIH, SC-200, IAM/PAM vendor certifications, CISSP, or equivalent practical expertise. Certifications are a plus &mdash; hands-on experience matters more.</div><div></div><div><b><br>
What Success Looks Like</b></div><div><b>
You will help us improve:</b></div><ul><li>
MFA and privileged-access coverage</li><li>
Joiner/mover/leaver security and access-removal speed</li><li>
Control of shared, dormant, and excessive access</li><li>
Alert response and incident-resolution times</li><li>
Access-review coverage and security evidence</li><li>
Internal security standards, procedures, and playbooks</li></ul><div><b>
Important</b></div><div>
We are not looking for a policy/compliance-only profile. The successful candidate must have real hands-on experience administering access controls, operating security tooling, investigating logs, and responding to security incidents.</div><div>
You will work closely with our second cybersecurity specialist, the Product &amp; Infrastructure Security Engineer, as well as DevOps, Network, Product, Engineering, Support, Abuse, HR, Finance, Legal, and executive management.</div><div>
If you enjoy taking ownership, building security controls, investigating real incidents, and improving security in a large-scale technology environment, we&rsquo;d like to hear from you.</div></div><div></div>

Internal Security & Security Operations Engineer

The Emirates Group

<div><h5 class="jobSectionHeader"><b>Job Purpose
</b></h5><p>Join the Emirates Group Analytics Centre of Excellence (ACoE), where data, AI and innovation power decisions across one of the world's most recognised aviation and travel brands.<br>
</p><p></p><br>
<p>As a <b>Data Scientist/AI Engineer </b>, you will solve complex business challenges using machine learning, advanced analytics, GenAI and Agentic AI. Working across commercial, operational and customer domains, you will transform vast amounts of data into actionable insights, intelligent products and measurable business outcomes.
</p><p>This is an opportunity to work on real-world, large-scale problems while helping shape the future of AI and data-driven decision making at Emirates Group.<br>
</p><p></p><br>
<p><b>In this role, you will:
</b></p><ul><li>Develop and deploy machine learning, <b>Agentic AI </b>and analytics solutions that drive measurable business impact.
</li><li>Analyse large structured, semi-structured and unstructured datasets to uncover insights and opportunities.
</li><li>Build predictive, prescriptive and optimisation models to solve business challenges across the Emirates Group.
</li><li>Partner with stakeholders to translate complex business questions into scalable data science solutions.
</li><li>Create visualisations, dashboards and analytical tools that support decision-making.
</li><li>Contribute to the development of reusable libraries, frameworks and production-ready data science assets.
</li><li>Apply experimentation techniques including A/B testing, segmentation and customer analytics.
</li><li>Collaborate with engineers, analysts and product teams in an agile delivery environment.
</li>Support the development and deployment of AI-powered products and intelligent automation capabilities.<br>
<li>
</li></ul><p></p><br>
<h5 class="jobSectionHeader"><b>Qualification
</b></h5><p><b>To be considered for this role, you must meet the below requirements:
</b></p><p><b>Qualifications
</b></p><ul><li>MSc or PhD in Data Science, Artificial Intelligence, Machine Learning, Mathematics, Statistics, Operations Research, Computer Science, Economics or a related quantitative discipline.
</li></ul><p><b>Experience
</b></p><ul><li>2-4+ years of experience delivering advanced analytics, machine learning or AI solutions in a commercial environment.
</li></ul><p><b>Knowledge &amp; Skills
</b></p><ul><li>Strong hands-on experience across the modern Data Science ecosystem.
</li><li>Experience developing and deploying Machine Learning, GenAI, LLM and Agentic AI solutions.
</li><li>Experience with AI Engineering practices including model deployment, monitoring, evaluation, prompt and context engineering and scalable AI application development.
</li><li>Proficiency in Python, SQL and modern analytical toolsets.
</li><li>Experience with Sparkor distributed data processing technologies.
</li><li>Experience with Git, Docker, CI/CD and MLOps workflows.
</li><li>Experience building reusable libraries, APIs or production-grade data science solutions.
</li><li>Strong problem-solving mindset with the ability to communicate technical concepts to non-technical audiences.
</li><li>Experience delivering solutions in complex, fast-paced environments.
</li></ul><p><b>Preferred Experience
</b></p><ul><li>Experience building and deploying AI applications using LLM orchestration frameworks (LangGraph, LangChain, Semantic Kernel or equivalent).
</li><li>Experience with Retrieval Augmented Generation (RAG), vector databases, AI agents and multi-agent systems.
</li><li>Experience evaluating, monitoring and governing production AI systems.
</li><li>Understanding of cloud-native AI platforms and modern AI engineering best practices.
</li></ul><h5 class="jobSectionHeader"><b>Salary &amp; benefits
</b></h5><p>Join us in Dubai and enjoy an attractive tax-free salary, industry-leading travel benefits, and access to one of the most exciting AI and data environments in the region. Alongside discounted flights and hotel stays worldwide, you'll have the opportunity to work on high-impact projects at global scale while advancing your career with Emirates Group.</p></div>

Data Scientist/AI Engineer

Millennium

<div>
 <em>
  Please direct all resume submissions to
 </em>
 <em>
  QuantTalentASIA@mlp.com
 </em>
 <em>
  and reference REQ-30162 as the subject.
  <br/>
  <br/>
 </em>
 Job Specification: Quant Research Engineer
 <br/>
 <br/>
 <strong>
  Preferred Candidate Profile
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Top-tier academic background from a globally top-20 university (e.g., MIT, Harvard, Princeton, Stanford, Caltech)
  </li>
  <li>
   PhD-level training in Computer Science, Engineering, Physics, Mathematics, or Statistics preferred
  </li>
  <li>
   Gold medal in a national or international olympiad (IMO, CMO, IOI, NOI, IPhO, CPhO) strongly preferred
  </li>
  <li>
   Prior experience at a top-tier quantitative trading firm or a leading AI/technology company preferred
  </li>
  <li>
   Demonstrated passion for applying AI &mdash; candidates who have built LLM-powered tools into their own research or engineering workflow stand out
   <br/>
   <br/>
  </li>
 </ul>
 Key Responsibilities
 <br/>
 <br/>
 <strong>
  Core Infrastructure Ownership
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design, build, and maintain the firm&rsquo;s core quant pipelines, data infrastructure, and research and production compute environments.
  </li>
  <li>
   Ensure the reliability, scalability, and performance of critical systems central to our research and trading activities.
  </li>
  <li>
   Drive the architectural vision for our next-generation data and compute platform &mdash; including how AI-native capabilities (LLM services, agentic workflows, retrieval infrastructure) are embedded into the research stack.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Collaboration &amp; Integration
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Partner directly with Quantitative Researchers and other development teams to understand their requirements and integrate new components into the core infrastructure.
  </li>
  <li>
   Act as a central point of expertise, facilitating the seamless flow of data and computation across teams and systems.
  </li>
  <li>
   Identify where AI can accelerate the research process &mdash; from literature ingestion and data exploration to signal prototyping &mdash; and build the tooling that makes it routine.
  </li>
  <li>
   Establish and enforce rigorous standards for system design, code quality, testing, and deployment.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  DevOps &amp; AI-Augmented Operations
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Own the deployment, monitoring, and operational health of production and research systems.
  </li>
  <li>
   Implement robust observability, logging, and alerting frameworks; apply AI-assisted techniques (automated log analysis, anomaly detection, intelligent incident triage) to raise the bar on reliability.
  </li>
  <li>
   Drive infrastructure-as-code practices and automate operational workflows, leveraging AI coding agents and LLM tooling where they demonstrably improve velocity and quality.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Qualifications &amp; Experience
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   3&ndash;5 years of professional experience in a quantitative development role, focused on building and maintaining quantitative research and production pipelines. Alternatively, significant engineering experience in a fast-paced startup &mdash; or strong hands-on AI/LLM engineering experience (building production LLM applications, agentic systems, or AI-powered developer
   <br/>
   <br/>
  </li>
 </ul>
 tooling) &mdash; with demonstrated ownership of complex infrastructure will be considered in lieu of direct quant experience.
 <br/>
 <br/>
 <ul>
  <li>
   Proven, end-to-end ownership of a significant piece of trading, research, high-performance, or AI infrastructure.
  </li>
  <li>
   Deep expertise in modern C++ and Python in a high-performance computing context.
  </li>
  <li>
   Demonstrable experience with large-scale data infrastructure (e.g., real-time/streaming and historical tick data).
  </li>
  <li>
   Strong background in cloud computing (AWS, GCP, or Azure) and parallel computing paradigms.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Hard Skills &amp; Technical Knowledge
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Broad knowledge of the technology landscape and the judgment to select the right tool for the problem (e.g., KDB+, Apache Spark, Dask, Redis).
  </li>
  <li>
   Practical experience applying LLMs and agentic workflows to real engineering or research problems &mdash; LLM APIs, agent frameworks, retrieval-augmented generation, and structured output pipelines &mdash; with sound judgment about where AI adds value and where determinism must be preserved.
  </li>
  <li>
   Proficiency with different database designs &mdash; SQL, NoSQL, and distributed file systems.
  </li>
  <li>
   Experience with containerization and orchestration technologies (Docker, Kubernetes).
  </li>
  <li>
   Strong experience with DevOps practices: infrastructure-as-code (Terraform, CloudFormation), CI/CD pipelines (GitHub Actions, GitLab CI), and system observability &mdash; including familiarity with AI-assisted operations tooling.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Soft Skills
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Exceptional Logical &amp; Reflective Thinking: Ability to deconstruct complex problems and design elegant, effective solutions.
  </li>
  <li>
   Proactive Collaboration: A team player who thrives in a collaborative environment and builds strong partnerships.
  </li>
  <li>
   High Integrity: Takes initiative and ownership of projects, upholding rigorous ethical standards in handling sensitive data and models.
  </li>
  <li>
   Growth Mindset: Innate curiosity and commitment to continuous improvement &mdash; including genuine enthusiasm for the rapidly evolving AI landscape and a track record of adopting new tools ahead of the curve.
  </li>
  <li>
   Superb Communication: Can articulate complex technical concepts to both technical and non-technical stakeholders.
  </li>
 </ul>
</div>


Quant Research Engineer

Fuse Energy

<div>
 Fuse Energy is an energy startup on a mission to make energy abundant and affordable, fast. We combine first-principles thinking with cutting-edge technology to build a radically better energy system.
 <br/>
 <br/>
 We've raised over $200M from top-tier investors including Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, 20VC, Hummingbird and Collaborative Fund, alongside strategic angels including Nico Rosberg and GPs behind Meta, Revolut, Spotify and Uber.
 <br/>
 <br/>
 We're building a fully integrated energy company: developing our own solar, batteries and other generation projects, building our own hardware, improving and developing grid infrastructure, trading power in real time, using AI across the business, and installing distributed energy in homes. By selling directly to consumers we cut out the middleman, lower costs and pass the savings on to our customers.
 <br/>
 <br/>
 We're building a cutting-edge AI team. As an Applied AI Engineer, this role suits someone with the technical depth of a backend engineer who is specifically interested in applied AI and how it can improve the energy experience for our customers and our internal operations. You'll work on consumer features such as the Energy Co-Pilot and speedy onboarding (using VLM and LLM tools) and build AI tools that make teams across Fuse more productive.
 <br/>
 <br/>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design, develop and deploy AI-powered features that directly impact consumer experiences, including personalised energy recommendations and seamless onboarding via AI models (e.g. using energy bills for quick setup)
  </li>
  <li>
   Build and optimise internal AI tools that make the whole company more productive, with a focus on automation and enhancing workflows
  </li>
  <li>
   Collaborate with backend engineers and data scientists to integrate AI-driven features into our platforms
  </li>
  <li>
   Collaborate with the trading and operations teams to ensure AI models are aligned with real-time market conditions and energy pricing
  </li>
  <li>
   Improve AI models to optimise trading strategies by anticipating market shifts based on weather and demand forecasts
  </li>
  <li>
   Stay up to date with the latest advancements in applied AI and machine learning and apply them to real-world problems in the energy space
  </li>
  <li>
   Monitor the performance of AI tools and models, ensuring they run efficiently and effectively
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Minimum 3 years of engineering experience
  </li>
  <li>
   Proven experience as a backend engineer with a strong interest and practical experience in applied AI or machine learning
  </li>
  <li>
   Strong programming skills in Python (or similar) with familiarity in AI/ML libraries (TensorFlow, PyTorch, etc.)
  </li>
  <li>
   Experience working with large-scale models (LLMs/VLMs) and deploying AI-driven solutions into production
  </li>
  <li>
   Solid understanding of cloud technologies, containerisation and building scalable AI applications
  </li>
  <li>
   Ability to integrate AI/ML models into real-world applications, focusing on usability and performance
  </li>
  <li>
   Strong problem-solving skills and a practical approach to implementing AI solutions in a fast-paced environment
  </li>
  <li>
   Experience working with large datasets, particularly in relation to demand and supply forecasting
  </li>
  <li>
   Bonus: experience or strong interest in energy markets and trading strategies; understanding of weather forecasting, energy demand patterns and production modelling; exposure to NLP or related fields
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Benefits
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Competitive salary and eligibility for equity
  </li>
  <li>
   Biannual bonus scheme
  </li>
  <li>
   Fully expensed tech to match your needs
  </li>
  <li>
   Private health insurance
  </li>
  <li>
   Breakfast and dinner allowance for office-based employees
   <br/>
   <br/>
  </li>
 </ul>
 As we hire globally, benefits may vary by location.
</div>


Applied AI Engineer

Explore 264+ Distributed systems engineer in Dubai this September. Find roles across top companies and apply now to boost your career.