Lead Platform Engineer

Barclays UK; New York (NY); On-site; USD 220,000 - 300,000; Full time

Job summary

A leading financial services provider is seeking an experienced engineering leader to oversee their global front-office success function. This role involves building trusted relationships with quants, writing quality Python code, and providing AWS support. The ideal candidate has strong knowledge of AI/ML concepts, solid communication skills, and experience leading technical teams. This position is based in New York and offers a competitive salary within the range of $220,000 to $300,000.

Qualifications

• Strong experience in Python engineering, focused on backend development and automation.
• Hands-on expertise with AWS services.
• Excellent communication skills in high-pressure environments.

Responsibilities

• Build and lead the global FO engineering success function.
• Write high-quality Python code for automation and tools.
• Guide teams on secure AWS usage and provide debugging support.

Skills

Python engineering

AWS

AI/ML concepts

Stakeholder management

Debugging

Tools

Docker

LiteLLM

MLflow

Databricks

SageMaker

Job description

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.

Key Responsibilities

Global Front‑Office Success Engineering Leadership

• 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.

Hands‑On Engineering & Troubleshooting

• 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.

AWS Engineering Support

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

AI/ML Enablement

• 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, SageMaker, and Observe.

Developer Experience & Operational Excellence

• 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.

Leadership & Mentorship

• 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.

Governance & Risk Management

• 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.

Required Skills & Experience

• Strong Python engineering experience (backend, tooling, automation, debugging).
• Hands‑on expertise with AWS: IAM, S3, Lambda, ECS/EKS, Step Functions, CloudWatch.
• 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.

Desirable Skills

• Familiarity with tools such as LiteLLM, MLflow, Databricks, SageMaker, 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.

Purpose of the role

To design, develop and improve software, utilising various engineering methodologies, that provides business, platform, and technology capabilities for our customers and colleagues.