Forward Deployed Software Engineer - Equities Technology

Millennium•Miami, FL

1d•$175,000 - $250,000•Hybrid

About The Position

The Equities Embedded Portfolio Management Solutions Team sits within Millennium’s Information Technology organization, which is core to the health and growth of the business. The firm’s active, multi-manager model demands flexible, scalable technology and advanced proprietary systems, including the development of next-generation analytical and trading capabilities. The team is a specialized engineering group at the intersection of technology and quantitative finance. Its mission is to accelerate the research and trading strategies of Millennium’s systematic Portfolio Management teams by serving as an internal center of excellence for expert-level solutions, architecture, and hands-on development in AI, cloud platforms including AWS and GCP, DevOps, and high-performance computing. The team’s engagement model ranges from expert advisory and solutions architecture to fully embedded, project-based implementations that build bespoke solutions directly for Portfolio Management teams. The team also builds and maintains managed services, libraries, and reusable patterns that form the foundation of modern quantitative research at the firm.

Requirements

Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
4+ years of professional software development experience, with a strong foundation in computer science principles including data structures, algorithms, and system design.
High proficiency in an object-oriented programming language, with a strong preference for Python.
Demonstrated experience in a customer-facing or business-facing role, with high emotional intelligence, a customer-first mindset, humility to meet business partners where they are, satisfaction in enabling the success of others, and willingness to go the extra mile to deliver an exceptional client experience.
Hands-on experience with at least one major cloud provider, including AWS or GCP, and familiarity with infrastructure as code concepts and tools such as Terraform, CloudFormation, or AWS CDK.
Experience designing systems and architectures from ambiguous business needs, with the ownership, autonomy, resilience, and composure to break down complex problems, navigate demanding stakeholders, and deliver tangible business value in high-pressure, high-stakes environments.
Proficiency with scheduling or asynchronous workflow frameworks and services such as AWS Step Functions, Airflow, Dagster, or Temporal, as well as DevOps tooling including AWS CodePipeline, GitHub Actions, or GCP Cloud Build, CI/CD practices, and containerization with Docker and Kubernetes.
Excellent verbal and written communication skills, the ability to build strong relationships and articulate complex ideas to diverse audiences, a pragmatic and adaptable approach that balances technical quality with business necessity, willingness to move from high-level architectural design to hands-on scripting and operational support to solve problems, and a foundational interest and passion for AI/ML and its practical applications.

Nice To Haves

Financial services or fintech experience.
Building applications on top of LLMs using frameworks such as LangChain or LlamaIndex.
Retrieval-Augmented Generation patterns.
MLOps tooling and concepts such as MLflow, model serving, feature stores, or pipeline orchestration with Kubeflow, Vertex AI, or SageMaker.
AWS or GCP cloud certifications at the Associate or Professional level.

Responsibilities

Partner directly with systematic Portfolio Management teams, quantitative researchers, developers, and portfolio managers as a trusted technical advisor.
Understand unique business and research needs and translate complex, sometimes ambiguous requirements into robust, scalable, and secure technical architectures across on-premises, hybrid, and cloud environments.
Design, build, and deliver high-quality, production-ready solutions across the full stack, including Python libraries, infrastructure as code with Terraform, CI/CD pipelines, automation scripts, and ML/AI proof-of-concepts.
Develop and maintain managed products, reusable libraries, engineering patterns, and best practice guides that expand self-service capabilities and accelerate onboarding for new and existing teams.
Own embedded engagements from discovery and planning through implementation, knowledge transfer, and support, acting as the primary technical point of contact while removing blockers and navigating the firm’s ecosystem on behalf of business partners.
Prepare and deliver compelling presentations, architectural diagrams, and software demos for technical and non-technical audiences, articulating complex technical concepts in clear, business-centric terms to build consensus and drive decisions.
Stay at the forefront of AI, MLOps, and cloud and hybrid technologies, building solutions for advanced use cases including distributed GPU training, large-scale data processing, and the integration of generative AI into research workflows.
Participate in the team’s on-call rotation, providing expert-level support for managed products and core platforms including cloud, DevOps, and grid environments, while turning support challenges into engineering opportunities through intelligent automation and AI agents that reduce manual work and improve operational efficiency.