At a Glance
- Tasks: Design and build innovative data platforms using Python and AI technologies.
- Company: Join JPMorganChase, a leader in tech innovation and data analytics.
- Benefits: Competitive salary, career growth, and opportunities for upskilling.
- Other info: Collaborative environment with a focus on responsible AI practices.
- Why this job: Shape the future of AI and data integration in a hands-on role.
- Qualifications: Experience in Python, backend services, and cloud infrastructure required.
Are you a senior Python engineer who wants to work at the intersection of data platforms and applied AI? This is your opportunity to join a small, high-impact team building something new from the ground up — where your decisions shape the architecture, not just the backlog. At JPMorganChase, we invest in engineers who are curious, pragmatic, and ready to grow into emerging technology stacks.
As a Senior Lead Software Engineer at JPMorganChase within the Corporate Technology Data and Analytics Services team, you will be a founding contributor to the Context Plane — a greenfield platform that connects the firm's data mesh and knowledge sources to AI agents and large language model tools. You will own components end-to-end, from ingestion pipelines to governed retrieval services, and your engineering instincts will directly influence how the platform evolves. This is a hands-on senior role with real architectural scope, active cross-functional collaboration, and strong support for internal mobility and upskilling.
Job responsibilities
- Design, build, and maintain backend services and data pipelines in Python that load firm knowledge into a knowledge graph and vector store.
- Build and evolve the serving layer — including graph and vector retrieval, GraphRAG, response assembly, and a Model Context Protocol endpoint consumed by downstream agents.
- Extract and promote reusable components into a shared core library, reducing duplication across the platform's repositories.
- Integrate with data sources and services across the firm, including enterprise AI and large language model gateways.
- Own quality across your components: automated testing, code reviews, observability, and resilient, secure service design.
- Partner with Corporate Technology AI, product, and data science colleagues to translate concrete use cases into working, measurable capabilities.
- Contribute to design discussions and agile ceremonies, and actively mentor teammates to raise the engineering bar across the team.
- Drive team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes.
- Apply knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realised by automation.
- Understand responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and advanced applied experience.
- Demonstrated expertise building production-grade backend services and data pipelines in Python.
- Strong command of API design principles (e.g., FastAPI), automated testing, CI/CD practices, and source control workflows.
- Experience designing and building data ingestion or integration pipelines at scale, with attention to data quality and resilience.
- Proficiency working with cloud infrastructure (AWS) and containerized services (Docker/ECS).
- Ability to own technical components end-to-end — from design through deployment and observability.
- Strong collaboration skills with the ability to work across engineering, product, and data science disciplines.
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment.
Preferred qualifications, capabilities, and skills
- Experience with graph databases and Cypher query language (e.g., Neo4j) or a strong interest in graph data modeling.
- Familiarity with vector search, embeddings, or retrieval-augmented generation (RAG) patterns.
- Exposure to large language model serving, agentic patterns, or platforms such as Bedrock or Azure OpenAI.
- Experience with Databricks, MongoDB, or large-scale extract, transform, and load / data integration workflows.
- Knowledge of data governance, lineage, and entitlements concepts in an enterprise environment.
Context Plane Python Engineer in Glasgow employer: Jpmorgan Chase & Co.
JPMorgan Chase & Co. is an exceptional employer, offering a dynamic work environment in Bournemouth where innovation and collaboration thrive. Employees benefit from a strong focus on professional development, inclusive team culture, and the opportunity to work with cutting-edge technology in a supportive atmosphere that values continuous improvement and engineering excellence.
StudySmarter Expert Advice🤫
We think this is how you could land Context Plane Python Engineer in Glasgow
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Jpmorgan Chase & Co. or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Jpmorgan Chase & Co..
✨Tap into Online Developer Communities
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We think you need these skills to ace Context Plane Python Engineer in Glasgow
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Jpmorgan Chase & Co..
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Jpmorgan Chase & Co. and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Jpmorgan Chase & Co.
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Jpmorgan Chase & Co. uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
