Senior Backend Engineer

Spencer Logic, LLC.; New York, Northern (NY, KY); Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

Equity participation

Annual learning budget

Job summary

Spencer Logic, LLC. seeks a veteran backend engineer to design and implement distributed, low-latency systems powering multi-region trading infrastructure in New York/Remote. You will build real-time data pipelines and ML-enabled risk modules for high-stakes production environments.

Responsibilities include mentoring engineers, leading design reviews, and integrating with FIX and liquidity APIs. Competitive comp, equity, learning budget.

Qualifications

• 6+ years in backend engineering with production-scale distributed systems.
• Proficiency in Go, Rust, Java or C++ (low-latency focus).
• Hands-on ML/AI in production using PyTorch, TensorFlow or scikit-learn.
• Deep knowledge of stream processing (Kafka, Flink).
• Experience with FIX-like financial systems or order management.
• Strong DB fundamentals (TimescaleDB, Redis, PostgreSQL).
• Strong concurrency, memory mgmt and performance profiling.
• Cloud & container orchestration (AWS, GCP, Azure; Kubernetes).

Responsibilities

• Design and build high-throughput, low-latency backend services for routing, execution and risk.
• Develop ML/AI models for predictive risk scoring and order-fill optimisation.
• Build real-time data pipelines processing millions of market events per second.
• Architect scalable microservices across multi-region cloud infra.
• Integrate with FIX, MT4/MT5 bridges and liquidity provider APIs.
• Participate in on-call rotations and own system reliability.
• Mentor junior engineers and lead design reviews.
• Contribute to AI Risk Management platform.

Skills

Backend engineering

Distributed systems

Go

Rust

Java

C++

ML/AI in prod

Kafka

Flink

AWS

Kubernetes

PostgreSQL

Redis

TimescaleDB

Tools

PyTorch

TensorFlow

scikit-learn

TimescaleDB

Redis

PostgreSQL

Job description

You'll be part of the core platform team building the infrastructure that powers over $6.5 trillion in annual trading volume across 200+ brokerages worldwide. This is a technically deep role — you will design and implement distributed systems, low-latency execution engines, and AI-augmented risk modules that must perform flawlessly under extreme market conditions.

We're looking for engineers who think in systems, move fast without breaking things, and have genuine experience applying machine learning or AI in high-stakes production environments.

What You'll Do

• Design and build high-throughput, low-latency backend services for order routing, execution, and risk management
• Develop and productionise ML/AI models for predictive risk scoring, adverse-selection detection, and order-fill optimisation
• Build and maintain real-time data pipelines processing millions of market events per second
• Architect scalable microservices deployed across multi-region cloud infrastructure
• Integrate with FIX protocol, MT4/MT5 bridges, and third-party liquidity provider APIs
• Participate in on-call rotations and own system reliability for critical trading infrastructure
• Mentor junior engineers and lead technical design reviews
• Contribute to our AI Risk Management platform — one of Spencer Logic's most strategic products

Requirements

• 6+ years of backend engineering experience with production-scale distributed systems
• Strong proficiency in Go, Rust, Java, or C++ (low-latency experience preferred)
• Hands-on experience with ML/AI frameworks (PyTorch, TensorFlow, scikit-learn) in production
• Deep understanding of stream processing (Kafka, Flink, or equivalent)
• Experience with financial systems, trading protocols (FIX), or order management systems
• Solid grasp of database internals — TimescaleDB, Redis, PostgreSQL
• Strong understanding of concurrency, memory management, and performance profiling
• Experience with cloud infrastructure (AWS, GCP, or Azure) and container orchestration (Kubernetes)

AI / ML Experience (Required)

Designing and shipping ML models for real-time inference in latency-sensitive environments

Feature engineering from tick-level market data and order-book snapshots

Model monitoring, drift detection, and retraining pipelines in production

Experience with reinforcement learning or time-series forecasting is a strong plus

Nice to Have

• Experience with MetaTrader (MT4/MT5) bridge integrations
• Knowledge of FX/CFD/crypto market microstructure
• Contributions to open-source trading, quant, or ML projects

Role Summary

Location New York, NY / Remote

Type Full-time

Reports to VP Engineering

Compensation

$180K – $240K base

Equity participation

Annual learning budget