Lead Platform Engineer

Salary / Rate Minimum: $220,000

Salary / Rate Maximum: $300,000

The minimum and maximum salary/rate information above includes only base salary or base hourly rate. It does not include any another type of compensation or benefits that may be available.

• Build and lead the global FO engineering success function across New York, London, and APAC users.
• Build trusted relationships with Quants and Strats worldwide, understanding differing desk‑specific needs.
• Prioritize and manage work intake globally based on business impact and urgency.
• Serve as the voice of FO users to influence platform roadmap and feature prioritization.

• Write high‑quality Python code for automation, integrations, internal utilities, and FO tooling.
• Diagnose complex issues across cloud (AWS), distributed systems, Python stacks, notebooks, model pipelines, and APIs.
• Deliver engineering solutions that reduce recurring FO friction and accelerate delivery.

• Guide global front‑office teams on secure and scalable usage of AWS services such as:
  S3, IAM, Lambda, ECS/EKS, Step Functions, Cloud Watch, Glue, and CDK/Cloud Formation.
• Provide hands‑on help with debugging, deployment, permissions, networking, and performance.

• Help global FO teams onboard onto platform AI features such as inference gateways, embeddings, evaluation tools, and tracing.
• Provide guidance on AI/ML concepts:
  model inference, RAG, embeddings, vector stores, latency optimisation, guardrails.
• Support adoption of tools such as LiteLLM, MLflow, Langfuse, Mem0, Databricks, Sage Maker
  , and Observe
  .

• Establish global support processes, workflows, and standards.
• Identify patterns in recurring issues and partner with platform engineering to eliminate them via features or automation.
• Develop and maintain documentation, onboarding guides, and best practices tailored for FO developers.
• Drive proactive monitoring of systems impacting FO teams.

• Lead and mentor a small team of engineers focused on FO success.
• Set strong engineering standards for code quality, reliability, and FO responsiveness.
• Promote a culture of collaboration, empathy, accountability, and excellence.

• Ensure all FO support and deployment workflows comply with governance, model controls, and data privacy requirements.
• Promote secure‑by‑default patterns across global FO usage.
• Help enforce model governance standards and audit requirements.

• Strong Python engineering experience (backend, tooling, automation, debugging).
• Hands‑on expertise with AWS
  : IAM, S3, Lambda, ECS/EKS, Step Functions, Cloud Watch.
• Proven experience working with Quants, Strats, or front‑office engineering teams
  .
• Solid understanding of AI/ML concepts (inference, vector search, embeddings, RAG, evaluation).
• Strong debugging abilities across cloud infra, Python environments, containers, and pipelines.
• Excellent communication and stakeholder management skills in high‑pressure FO environments.
• Experience leading a technical team or owning a global‑facing engineering function.

• Familiarity with tools such as LiteLLM, MLflow, Databricks, Sage Maker, Langfuse, Observe, Mem0
  .
• Understanding of financial markets, derivatives, FO analytics workflows, or pricing/risk models.
• Exposure to model governance, compliance, and data control frameworks.
• Experience with Docker, ECS/EKS, and platform observability tooling.
• Experience improving developer productivity or reliability at scale.

To design, develop and improve software, utilising various engineering methodologies,…