Team Overview
The Equities Embedded Portfolio Management Solutions Team is a specialized group of engineers operating at the intersection of technology and quantitative finance. Our mission is to accelerate the research and trading strategies of Millennium's systematic Portfolio Management teams. We function as an internal center of excellence, providing expert-level solutions, architecture, and hands-on development in AI, Cloud (AWS/GCP), DevOps, and high-performance computing. Our engagement model is dynamic, ranging from expert advisory and solutions architecture to fully embedded, project-based implementations where we build bespoke solutions directly for Portfolio Management teams. We are a high-impact team that builds and maintains a suite of managed services, libraries, and patterns that form the bedrock of modern quantitative research at the firm.
Role Description
We are seeking a hands-on, business-facing engineer to join our team. In this role, you will partner directly with some of the most sophisticated quantitative researchers, developers, and portfolio managers in the industry. You will be their trusted technical advisor, helping them design, build, and optimize their research environments and workflows. This is not a typical software development role; it is a unique blend of solutions architecture, software engineering, and client engagement.
Success in this role requires more than just technical excellence. It demands a deep-seated, customer-first mindset, the humility to meet our business partners where they are, and the resilience to thrive in a high-pressure, high-stakes environment. You will be an influencer, a problem-solver, and a builder, often navigating ambiguous requirements to deliver tangible business value. As part of our full-cycle ownership model, you will also participate in supporting the solutions we build and the platforms we enable. You are someone who finds satisfaction in enabling the success of others and is willing to do what it takes—from high-level architectural design to hands-on scripting and operational support—to solve a problem.
Who You Are
Humble & Service-Oriented: You have high emotional intelligence and a customer-first mindset. You measure your success by the success of those you support and are willing to go the extra mile to deliver exceptional client experience.
Resilient & Composed: You thrive in high-pressure, high-stakes environments and can navigate demanding stakeholders with professionalism and a solutions-oriented attitude.
Owner & Problem-Solver: You are a proactive, self-starter who can operate with a high degree of autonomy. You are comfortable with ambiguity and skilled at breaking down complex problems into actionable steps.
Pragmatic & Adaptable: You understand the balance between technical purity and business necessity. You are an influencer, not a purist, and can adapt your approach to meeting the client's needs.
What You'll Do (Principal Responsibilities)
Partner & Architect: Engage directly with Portfolio Management teams to understand their unique business needs. Translate complex research requirements into robust, scalable, and secure technical architectures across on-prem, hybrid, and cloud environments.
Build & Implement: Write high-quality, production-ready code across the full stack. This includes Python libraries, infrastructure-as-code (Terraform), CI/CD pipelines, automation scripts, and ML/AI proof-of-concepts.
Enable & Accelerate: Develop and maintain our suite of managed products, reusable patterns, and best practice guides to provide self-service options and accelerate onboarding for new and existing teams.
Problem Solve: Act as the primary technical point of contact for embedded engagements. You will own projects from discovery and planning through to implementation, knowledge transfer, and support, removing blockers and navigating the firm's ecosystem on behalf of your client.
Communicate & Influence: Prepare and deliver compelling presentations, architectural diagrams, and software demos to both technical and non-technical audiences. You will need to articulate complex technical concepts in simple, business-centric terms to build consensus and drive decisions.
Innovate: Stay at the forefront of technology in AI, MLOps, and Cloud/Hybrid. You will build solutions for cutting-edge use cases, including distributed GPU training, large-scale data processing, and the integration of Generative AI into research workflows.
Support & Automate: Participate in the team's on-call rotation, providing expert-level support for our managed products and the core platforms we enable (Cloud, DevOps, Grid, etc.). You will be challenged to turn support challenges into engineering opportunities by building intelligent automation and AI agents to reduce tedious tasks and improve our operational efficiency.
Required Qualifications
Bachelor’s or Master’s Degree in Computer Science, Engineering, or a related field.
4-7 years of professional software development experience with a strong foundation in computer science principles (data structures, algorithms, system design).
High proficiency in an object-oriented language, with a strong preference for Python.
Demonstrated experience in a customer-facing or business-facing role, with the ability to translate business requirements into technical solutions.
Hands-on experience with at least one major cloud provider (AWS or GCP) and familiarity with infrastructure-as-code concepts (e.g., Terraform, CloudFormation, or AWS CDK).
Excellent verbal and written communication skills, with the ability to build strong relationships and articulate complex ideas to diverse audiences.
A foundational interest and passion for AI/ML and its practical applications.
Experience designing systems and architectures from ambiguous business needs.
Experience with scheduling or asynchronous workflow frameworks/services (i.e. AWS Step Functions, Airflow, Dagster, Temporal)
Proficiency with DevOps tooling (AWS CodePipeline, Github Actions, or GCP Cloud Build), CI/CD practices, and containerization (Docker, Kubernetes).
Preferred Qualifications
Experience in the financial services or fintech space.
Experience building applications on top of LLMs using frameworks like LangChain or LlamaIndex and knowledge of patterns like Retrieval-Augmented Generation (RAG).
Experience with MLOps tooling and concepts, such as experiment tracking (MLflow), model serving, feature stores, or pipeline orchestration (Kubeflow, Vertex AI, SageMaker).
Cloud certifications (AWS or GCP) at the Associate or Professional level.