Senior AI Delivery Engineer
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Senior AI Delivery Engineer
180,000–300,000 / Year
Location
New York
Experience
Senior
Posted
Jul 10, 2026
Apply by
August 9, 2026
Applicants
0
Early applicantEasy applyFull-timeWork from Office
Job Description
Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT's collaborative mindset which enables us to solve the most complex challenges. QRT's culture of innovation continuously drives our ambition to deliver high quality returns for our investors.
You'll work closely with QRT's engineers, quantitative researchers and data scientists to accelerate software delivery using modern AI coding tools and agents. This is a hands-on engineering role focused on solving real problems, building practical solutions and helping teams deliver high-quality software to production faster. You'll have significant autonomy and will be measured by the impact you deliver.
## Your Future Role within QRT:
## Delivery -
- Partner with engineering and research teams to identify high-value opportunities and deliver practical solutions.
- Use AI coding agents to take ideas from specification through to production.
- Build targeted tooling, integrations and automation to improve engineering workflows.
- Work across teams, codebases and technical domains as priorities evolve.
### AI-Assisted Engineering -
- Apply AI-assisted development to accelerate software delivery while maintaining engineering quality.
- Integrate AI agents into existing development workflows, including CI/CD and code review.
- Establish pragmatic guardrails and human oversight for AI-assisted development.
- Share reusable approaches and best practices across engineering teams.
### Ownership & Impact -
- Own delivery from problem definition through production deployment.
- Balance speed, quality and reliability in a fast-paced trading environment.
- Communicate effectively with technical and non-technical stakeholders.
- Drive outcomes with autonomy, sound judgement and a bias for execution.
## Your Present Skillset:
We value strong engineering judgement, hands-on AI-assisted delivery and a bias for impact. We do not expect candidates to meet every requirement below.
- Significant software engineering experience within a quantitative hedge fund, systematic trading firm or similarly demanding engineering environment.
- Strong programming skills in one or more modern languages, with the ability to learn new technologies quickly.
- Hands-on experience using AI coding agents or LLMs to deliver production software.
- Proven ability to solve ambiguous problems and deliver practical solutions independently.
- Comfortable working across unfamiliar codebases, teams and technical domains.
- Experience with CI/CD, code review workflows and human-in-the-loop development practices.
- Strong engineering judgement, including balancing rapid delivery with long-term maintainability.
- Excellent communication and collaboration skills.
- Demonstrated ownership, pace and delivery of measurable business impact.
## Nice to Have:
- Experience with market data, real-time systems or trading infrastructure.
- Experience building deployment pipelines or AI-assisted execution workflows.
- Experience building or self-hosting LLM infrastructure.
- Familiarity with Kafka or similar streaming technologies.
- Familiarity with authentication, permissions and access control systems (e.g. OIDC).
- Contributions to open-source projects.
Base salary range for this position is $180,000 to $300,000 per year.
QRT Total Compensation includes discretionary performance-based bonuses and a competitive benefits package.
Key Responsibilities
- Partner with engineering and research teams to identify high-value opportunities and deliver practical solutions.
- Use AI coding agents to take ideas from specification through to production.
- Build targeted tooling, integrations, and automation to improve engineering workflows.
- Apply AI-assisted development to accelerate software delivery while maintaining engineering quality.
- Integrate AI agents into existing development workflows, including CI/CD and code review.
- Establish pragmatic guardrails and human oversight for AI-assisted development.
- Share reusable approaches and best practices across engineering teams.
- Own delivery from problem definition through production deployment.
- Balance speed, quality, and reliability in a fast-paced trading environment.
- Communicate effectively with technical and non-technical stakeholders.
Skills Required
Software EngineeringAI Coding AgentsLLMsCI/CDCode ReviewHuman-in-the-loop DevelopmentProgrammingEngineering JudgementProblem SolvingCommunicationCollaborationOwnershipAutonomyBias for ExecutionMarket dataReal-time systemsTrading infrastructureDeployment pipelinesAI-assisted execution workflowsLLM infrastructureKafkaStreaming technologiesOIDCOpen-source contributions
Benefits
- Discretionary performance-based bonuses
- Competitive benefits package
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