> Markdown version of [/jobs/ext/4361072-senior-developer](https://www.wearedevelopers.com/jobs/ext/4361072-senior-developer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Developer - **Company:** HLS Trading - **Location:** Coral Gables, FL, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Query Performance, Application Programming Interfaces (APIs), Algorithmic Trading, Amazon Web Services, Microsoft Azure, Big Data, C++ (Programming Language), Cloud Computing, Code Review, Computer Programming, Databases, Continuous Integration, Data Integrity, Data Systems, Python (Programming Language), NumPy, Reference Data, Prometheus, Software Engineering, Parquet, Datadog, Data Logging, Pulumi, Real Time Systems, Pytorch, Large Language Models, Grafana, Model Validation, Pandas, Containerization, Kubernetes, Infrastructure Automation Frameworks, Influxdb, Vertica, Terraform, Docker - **Published:** October 2, 2026 - **Apply:** https://www.disabledperson.com/jobs/75666174-senior-developer ## About the Role Required * Experience: 5+ years of professional software development experience, including direct work on real-time trading systems or research platforms. * Programming: Expert-level Python, including large-scale data processing with NumPy, Pandas, Polars, PyTorch, or similar. * C++: Working proficiency in C++ for performance-sensitive components. * Data Systems: Hands-on experience with very large datasets, including time-series databases (e.g., InfluxDB, TimescaleDB, kdb+/q) and columnar formats and engines (e.g., Parquet, DuckDB, ClickHouse), or similar. * Observability: Familiarity with monitoring and logging tools such as Prometheus, Grafana, ELK, or Datadog. * LLM Fluency: Advanced, hands-on use of LLM coding tools and agents as a core part of how you build, with a clear sense of where they fail. Strongly Preferred * Understanding of futures and FX market data conventions and market microstructure. * Experience with systematic trading or quantitative research workflows. * Experience mentoring engineers or leading technical projects. * Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). * Exposure to CI/CD pipelines and infrastructure-as-code tools (Terraform, Pulumi). ## Description The Senior Developer owns the platform behind our trading and research. Core pieces are already in place, including a position management system that handles order generation, routing, and pre-trade risk controls, and colocated market data infrastructure in NY4, so the work is to extend, harden, and improve that platform rather than build it from scratch. The stack is primarily Python, with C++ for performance-sensitive components. Cloud infrastructure and CI/CD are handled by a dedicated team member, so while familiarity with those areas is useful, this role is squarely focused on the trading and research platform itself. There are no direct reports today, but we expect this role to lead a development team as the firm grows. This is a hybrid role based in either our Miami or Greenwich office, with three days a week in the office., Trading Infrastructure * Own the real-time systems that carry live market data into our models and model target positions into the position management system. * Extend and maintain the connectors that ingest live market data, including high-volume exchange feeds in NY4, broker connections, and vendor APIs (e.g., Bloomberg, LSEG). * Maintain and improve C++ components on latency- and throughput-sensitive paths. Market Data and Research Platform * Build and optimize pipelines that process, clean, and validate tick-level and aggregated historical futures and FX data, along with the reference data they depend on, such as contract specifications, roll schedules, and trading calendars. * Design data models, storage, and query APIs for large volumes of market data, prioritizing query performance, data integrity, and cost efficiency. * Develop Python tooling and libraries that make research, model evaluation, and backtesting faster and more reproducible, with shared code and data paths so strategies behave the same in backtests as in live trading. * Work directly with the investment team to turn complex, often loosely defined research needs into durable technical solutions. Production and Reliability * Improve the reliability, observability, and testability of research and production systems, including monitoring, alerting, and logging for every market data feed and trading system. * Diagnose difficult problems across the research-to-production lifecycle and follow through on root-cause fixes. * Set standards for testing, code review, and production readiness, including simulation and replay testing before changes reach live trading. Technical Leadership * Make pragmatic architecture and build-versus-buy decisions for the platform, and establish the engineering practices a future development team will build on.