AI Software Engineer

Location: Remote
Engagement: Contract (W2 only)
Start: ASAP

Team Overview

You will join a global risk‑technology organization composed of three engineering blocks - Platform, Data, and Modeling - each operating as a high‑performance, cross‑functional squad.
Teams collaborate across North America, Europe, and APAC, delivering reliable, secure, and scalable technology that supports the firm's risk management functions.

This role sits specifically within the Data block, responsible for building intelligent services and AI‑augmented capabilities that improve risk insight, automation, and operational efficiency across the organization.

Role Overview

As a Senior AI Software Engineer, you will develop and deploy AI‑powered backend services that enhance the firm's risk workflows and operational decision‑making. You will implement production‑grade machine learning and LLM‑based solutions, create reliable inference services, and integrate these capabilities into existing risk platforms.

This role is hands‑on and engineering‑focused: strong Python engineering, backend systems knowledge, and applied AI/ML experience are essential. You will work closely with Product Owners, Business Developers, and engineering teams across global regions to translate business requirements into secure, robust, and measurable AI capabilities.

Key Responsibilities

AI Engineering & Model Integration

• Build and maintain LLM‑powered services, embeddings pipelines, and retrieval‑augmented generation components.
• Develop production‑ready inference APIs, ensuring high reliability, controlled latency, and operational safety.
• Implement model evaluation frameworks, versioning, guardrails, and monitoring for responsible AI deployment.

Backend & Systems Engineering

• Design scalable backend components in Python (primary) and selectively in C++ for performance‑critical workloads.
• Integrate AI services with the firm's existing risk platforms, APIs, and distributed systems.
• Ensure all services meet strict standards for performance, auditability, and operational resilience.

Cross‑Functional Collaboration

• Work with Product Owners and global engineering teams to define requirements, refine use cases, and deliver AI features that provide measurable impact.
• Support risk and operations teams by automating manual workflows and developing intelligent tooling where appropriate.

Security, Governance & Compliance

• Implement AI solutions aligned with enterprise security policies, data governance, and regulatory expectations typical of financial institutions.
• Maintain clear documentation, audit trails, and structured release processes for all deployed models and services.

Required Qualifications

• 3+ years of experience in AI/ML engineering or software engineering with hands‑on AI responsibilities.
• Strong programming skills in Python; familiarity with C++ for high‑performance or low‑latency components.
• Production experience using:
  • PyTorch or TensorFlow
  • HuggingFace Transformers
  • LangChain or LlamaIndex
  • Vector databases (FAISS, Pinecone, Milvus)
• Solid understanding of backend development, distributed systems, API design, and performance optimization.
• Experience monitoring ML/LLM systems, evaluating model outputs, and implementing safeguards.
• Familiarity with OpenShift or AWS and containerized deployments.
• Ability to work effectively in a global, agile engineering environment with high autonomy.

Preferred Experience

• Experience with LLM fine‑tuning, LoRA/PEFT, prompt engineering, or RAG optimization.
• Exposure to financial services, risk technology, or regulated environments.
• Background in building guardrails, safety layers, or policy‑aligned AI behavior.
• Experience with lightweight MLOps practices (model registries, experiment tracking, packaging).

Why This Role Matters

• You will build AI capabilities that directly support risk controls, analytics, and operational intelligence at a global clearing firm.
• You'll work with modern, enterprise‑grade AI tooling and solve meaningful engineering challenges around reliability, latency, and governance.
• The position offers significant autonomy, cross‑regional collaboration, and visibility across risk and technology leadership.