Shulman Fleming & Partners
Swaps Java Developer
MUST be local to New York City, Hybrid Schedule at least 3 days onsite
Salary: up to $200k
No Sponsorship Available
We are seeking a hands-on Java Developer to join our Equities Financing Technology team, with a focus on Swaps and synthetic financing products. The ideal candidate will have experience building and supporting trading and lifecycle platforms, and be familiar with vendor tools like
Nuvo Prime
and
SwapOne . Exposure to machine learning or AI platforms such as
DL4J
is highly desirable.
Key Responsibilities: Design, develop, and enhance Java-based systems for swaps lifecycle and synthetic equity financing. Collaborate with traders, product controllers, and operations to deliver front-to-back solutions. Integrate with vendor platforms (e.g., Nuvo Prime, SwapOne) to streamline trade flow and lifecycle management. Leverage AI/ML libraries or platforms (e.g., DL4J) for analytics, trade matching, or optimization use cases. Ensure high availability, performance, and scalability of the trading systems. Participate in code reviews, performance tuning, and support rotational duties. Required Skills & Experience:
Strong core
Java
development skills with multi-threading and low-latency architecture experience. Solid understanding of
Equity Swaps , Total Return Swaps, or synthetic financing products. Prior experience in
Equities Financing
or Prime Brokerage domains. Familiarity with
Nuvo Prime ,
SwapOne , or other industry-standard swaps platforms. Experience with AI/ML tools in Java, such as
DL4J
or other relevant libraries (TensorFlow, PyTorch via Java wrappers). Experience integrating with upstream and downstream systems (e.g., risk, P&L, settlements). Strong analytical and communication skills; ability to work in a fast-paced environment. Preferred Qualifications:
Exposure to Python or data science platforms is a plus. Experience with
Murex
or similar risk/trade processing platforms. Prior experience with Kafka, REST APIs, and messaging protocols (e.g., FIX). Understanding of regulatory and margin implications in synthetic financing.
MUST be local to New York City, Hybrid Schedule at least 3 days onsite
Salary: up to $200k
No Sponsorship Available
We are seeking a hands-on Java Developer to join our Equities Financing Technology team, with a focus on Swaps and synthetic financing products. The ideal candidate will have experience building and supporting trading and lifecycle platforms, and be familiar with vendor tools like
Nuvo Prime
and
SwapOne . Exposure to machine learning or AI platforms such as
DL4J
is highly desirable.
Key Responsibilities: Design, develop, and enhance Java-based systems for swaps lifecycle and synthetic equity financing. Collaborate with traders, product controllers, and operations to deliver front-to-back solutions. Integrate with vendor platforms (e.g., Nuvo Prime, SwapOne) to streamline trade flow and lifecycle management. Leverage AI/ML libraries or platforms (e.g., DL4J) for analytics, trade matching, or optimization use cases. Ensure high availability, performance, and scalability of the trading systems. Participate in code reviews, performance tuning, and support rotational duties. Required Skills & Experience:
Strong core
Java
development skills with multi-threading and low-latency architecture experience. Solid understanding of
Equity Swaps , Total Return Swaps, or synthetic financing products. Prior experience in
Equities Financing
or Prime Brokerage domains. Familiarity with
Nuvo Prime ,
SwapOne , or other industry-standard swaps platforms. Experience with AI/ML tools in Java, such as
DL4J
or other relevant libraries (TensorFlow, PyTorch via Java wrappers). Experience integrating with upstream and downstream systems (e.g., risk, P&L, settlements). Strong analytical and communication skills; ability to work in a fast-paced environment. Preferred Qualifications:
Exposure to Python or data science platforms is a plus. Experience with
Murex
or similar risk/trade processing platforms. Prior experience with Kafka, REST APIs, and messaging protocols (e.g., FIX). Understanding of regulatory and margin implications in synthetic financing.