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DeveloperHLS Trading • Doral, FL, United States
Developer

Developer

HLS Trading • Doral, FL, United States
[job_card.1_day_ago]
[job_preview.job_type]
  • [job_card.full_time]
[job_card.job_description]

About the Company

We are a systematic investment manager seeking talented and driven individuals to join us at the ground floor. Its an opportunity for maximum ownership, accelerated impact, and career trajectory :

  • Maximum Impact : You wont just maintain a component; you will be the single owner and architect of the firms most critical asset : its trading infrastructure. Your work directly drives all trading decisions and P&L.
  • Significant Resources and Stability : Despite being a startup, we are well-capitalized and backed by well-known, highly respected Allocators. This provides the stability, scale, and significant resources necessary to invest aggressively in top-tier technology and talent from the outset.
  • Zero Bureaucracy : Work in an agile, flat structure where good ideas move to production fast. Decisions are made quickly and your technical opinion carries immense weight.
  • Upside : In addition to competitive compensation, this role offers a significant opportunity for long-term profit-sharing, aligning your success directly with the growth of the fund.

About the Role

We are seeking a talented and experienced Core Developer to build and refine the foundational platform powering our systematic research and quantitative trading strategies. Youll develop high-performance backend services, data infrastructure, and APIs that our quantitative researchers rely on daily. This role requires someone comfortable working across the stackincluding standing up cloud infrastructure, CI / CD, and containerized deploymentsbut the core focus is building and evolving the trading and investment platform itself.

Responsibilities

Platform Development

  • Architect and develop high-performance backend services and APIs serving as the foundation for quantitative research and trading operations.
  • Build, optimize, and manage scalable data pipelines for processing and validating large-scale financial datasets.
  • Design and maintain storage solutions and querying interfaces that enable researchers to efficiently access and analyze data.
  • Implement data models prioritizing query performance, reliability, and cost efficiency.
  • Collaborate closely with the quantitative research team to translate their requirements into robust, production-grade solutions.

    • Infrastructure & Deployment

  • Establish CI / CD pipelines, containerization (Docker / Kubernetes), and cloud infrastructure to support reliable, scalable deployments.
  • Implement observability layerslogging, monitoring, and alertingto ensure system transparency and reliability.
  • Define infrastructure-as-code practices for reproducible environments.

    • Qualifications

    Technical Skills

  • Experience : 3 years of professional software development experience.
  • Programming : Expert-level Python proficiency; familiarity with a high-performance systems language (C, Go, Rust, or Java) for latency-sensitive components.
  • Data Systems : Experience with large datasets, time-series databases (InfluxDB, TimescaleDB), or columnar databases.
  • Cloud & Infrastructure : Comfortable working in AWS, GCP, or Azure; hands-on experience with Docker, Kubernetes, and CI / CD tooling.
  • Observability : Familiarity with monitoring and logging tools (Prometheus, Grafana, ELK, Datadog, or similar).

    • Preferred Skills

  • Experience with infrastructure-as-code (Terraform, Pulumi)
  • Understanding of Futures and FX market data conventions
  • Familiarity with systematic trading or quantitative research workflows

    • Equal Opportunity Statement

    HLS Trading is an Equal Opportunity Employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, veteran status, disability, or any other characteristic protected by law.

    #J-18808-Ljbffr

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    Developer • Doral, FL, United States

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