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About the Role

The Equities Embedded Portfolio Management Solutions Team is seeking a Forward Deployed Software Engineer to partner directly with systematic Portfolio Management teams, quantitative researchers, developers, and portfolio managers as a trusted technical advisor. This role blends solutions architecture, software engineering, and client engagement to accelerate research and trading strategies.

Responsibilities

Serve as a hands-on, business-facing engineer, partnering 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 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.
Prepare and deliver compelling presentations, architectural diagrams, and software demos for technical and non-technical audiences.
Build 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.
Turn support challenges into engineering opportunities through intelligent automation and AI agents.

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, satisfaction in enabling the success of others, and willingness to go the extra mile.
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 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.
Proficiency with 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.
Ability to build strong relationships and articulate complex ideas to diverse audiences.
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.
Foundational interest and passion for AI/ML and its practical applications.
Preferred experience includes financial services or fintech.
Preferred experience includes building applications on top of LLMs using frameworks such as LangChain or LlamaIndex.
Preferred experience includes Retrieval-Augmented Generation patterns.
Preferred experience includes MLOps tooling and concepts such as MLflow, model serving, feature stores, or pipeline orchestration with Kubeflow, Vertex AI, or SageMaker.
Preferred experience includes AWS or GCP cloud certifications at the Associate or Professional level.

Skills

Python
Terraform
AWS
GCP
Infrastructure as Code
CI/CD
Automation Scripting
ML/AI Proof-of-Concepts
Cloud Platforms
DevOps
High-Performance Computing
Solutions Architecture
Software Engineering
Client Engagement
AWS Step Functions
Airflow
Dagster
Temporal
AWS CodePipeline
GitHub Actions
GCP Cloud Build
Docker
Kubernetes
AI
MLOps
Distributed GPU Training
Large-Scale Data Processing
Generative AI
LangChain
LlamaIndex
Retrieval-Augmented Generation
MLflow
Model Serving
Feature Stores
Kubeflow
Vertex AI
SageMaker

Location

New York

Work Type

Full-time

Experience Level

4+ years of professional software development experience

Education Level

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field

Salary/Compensations

$175,000 to $250,000

Benefits

Discretionary performance bonus
Comprehensive benefits

About the Company

Millennium is a global, diversified alternative investment firm, founded in 1989.
Millennium’s mission is to deliver results for our investors.
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.