Principal AI/ML Full-Stack Engineer (Python & AWS)

Next Frontier Capital

Greater London

On-site

GBP 100,000 - 150,000

Full time

14 days+
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Job summary

J.P. Morgan is seeking a Principal Software Engineer within the Applied Innovation (of AI) Engineering team in the CDAO Technology Group.

You will design, develop, deploy, and maintain advanced AI products, collaborating with software engineers, data engineers, and data scientists to deliver trusted solutions. You will contribute to long-term projects that drive innovation, uphold a culture of inclusion, and maintain technical excellence across enterprise-scale systems.

Qualifications

  • Proven programming/scripting skills in Python, Golang, TypeScript in an AWS/cloud environment.
  • Experience with GPT, LLM, RAG, Gen AI technologies.
  • Experience developing, debugging, and maintaining code in a large corporate environment with modern languages and DB querying.
  • Solid understanding of CI/CD, Applicant Resiliency, and Security.
  • Strong knowledge of APIs, concurrency, and software design patterns.

Responsibilities

  • Collaborates with engineers, data scientists, and product owners to deliver products to production.
  • Builds and maintain data pipelines for analytics, model evaluation, and training (including versioning and validation).
  • Develops secure, high-quality production code and reviews others’ code.
  • Provides guidance to architecture governance and improves software delivery at scale.

Skills

Python
Golang
TypeScript
AWS
GPT/LLM/Gen AI
CI/CD
APIs
Data pipelines

Tools

Git
SQL
Docker

Job description

J.P. Morgan is seeking a Principal Software Engineer within the Applied Innovation (of AI) Engineering team in the CDAO Technology Group.

You will design, develop, deploy, and maintain advanced AI products, collaborating with software engineers, data engineers, and data scientists to deliver trusted solutions. You will contribute to long-term projects that drive innovation, uphold a culture of inclusion, and maintain technical excellence across enterprise-scale systems.

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