Tom Fleet
Senior Software Engineer
About
Experienced self-taught software engineer with a background in aerospace engineering and materials science. Expertise and experience in Go, Python, AWS Serverless, REST APIs and microservices/distributed systems. I take pride in producing reliable, clean, robust and well-documented software and architectures. I also enjoy mentoring other engineers and sharing knowledge/experience in areas where I'm able to do so. I enjoy learning new things and have a lot of side projects! Everything from command line tools to mini programming languages to build systems, parsers and reusable libraries.
Work Experience
Senior Cloud Engineer
Senior Cloud Engineer in the platform team, designed, implemented and managed crucial parts of the AWS estate as well as other shared infrastructure/services in a more DevOps and DevEx focussed role.
Highlights
- Created and rolled out a suite of 'best practice baked in' copier templates for bootstrapping new service development in the engineering teams. These rapidly became the standard across the organisation and I estimate saved hundreds of engineering hours per year.
- Designed and led the implementation across the organisation of a private PyPI repository in AWS CodeArtifact acting as a cache pull-through, decoupling the estate from public infrastructure, improving the security posture and deployment reliability. Also implemented a pre-emptive vulnerability scanning process on this CodeArtifact repository.
- Rolled out a fully automated and safe solution for teams to self-provision GitHub repositories using GitHub actions and the templates mentioned above with compliance, security and quality standards managed by automated org-wide rulesets deployed with Terraform.
- Leveraged AFT (Account Factory for Terraform) to create an automatic, standards-compliant system for provisioning new AWS accounts, including a suite of composable customisations to tailor account infrastructure as needed.
- Developed a number of reusable CI/CD pipelines and GitHub actions, standardising common actions across the organisation such as continuous integration in Python repositories, and the Terraform plan, review and apply lifecycle.
- Held workshops and wrote user guides to help upskill the engineering teams in infrastructure and DevOps, particularly debugging in AWS and using Terraform for IaC.
- Led the introduction of infrastructure/deployment testing to the Cloud Platform team, improving the quality and reliability of the shared components we developed.
Chetwood Financial Ltd.
Wrexham, UK
Digital-first UK Bank
February 2023 – April 2024
Tech Lead
Promoted to technical lead of a cross-functional pod; setting a technical & strategic direction, designing higher level architectures, acting as a the organisation's SME for our area, and leading a team of several developers and QAs.
Highlights
- Led a newly created cross-functional team building an entirely new easy access savings product, using a new core banking platform.
- Championed and introduced the use of static typing in python code as well as significantly stricter linting via ruff, leading to a measurable reduction in production errors across a number of core services, and an improved developer experience with faster feedback.
- Led a serverless workshop for developers new to the stack, upskilling them in AWS CloudFormation, SAM, Lambdas, API Gateway, DynamoDB and event driven architecture.
- Participated in the interviewing and recruitment of new engineers up to staff level.
- Mentored new team members and helped to foster an attitude of engineering excellence and best practice within the team and across the engineering department.
Chetwood Financial Ltd.
Wrexham, UK
Digital-first UK Bank
April 2022 – February 2023
Software Engineer
Python engineer working in a cross-functional pod focused on the development and maintenance of the custom built, in-house lending decision engine.
Highlights
- Key member of a high performing team responsible for a piece of critical infrastructure
- Coordinated and led the release of a novel dynamic pricing mechanism with a turn around time of just 9 days
- Managed regular releases of critical infrastructure including 3rd party integration layers and the in-house lending decision engine
Junkshon
Manchester, UK
Cloud migration SaaS provider
May 2021 – April 2022
Python Developer
Backend Python/Django developer split between backend development/maintenance and the implementation of machine learning feature sets on a proprietary web-based platform designed to facilitate cloud migrations.
Highlights
- Development and deployment of text classification microservices via Azure Functions and Openfaas. Also created a robust and reusable “cookiecutter” template for such services.
- Maintaining a large Django REST API, addressing bugs, implementing new API endpoints to expose to a react frontend, refactoring as necessary.
Previous Life
Various
Career in Aerospace Engineering and Materials Science, details omitted for brevity.
June 2015 – May 2021
Engineer/scientist focused on advanced materials science, polymer and metallic composites applied to the aerospace industry both in large multinational corporations and smaller research labs.
Highlights
- Coordinated and led a number of research projects in advanced metal matrix composite technology, characterisation and manufacturing techniques.
- Published 2 research papers combining advanced computational techniques and materials science.
- Mixture of production support and R&D activities in polymer composite materials to support production of the Airbus A350-900 and -1000
Contact
Nantwich UK
Education
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2020 2019
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2017 2013
Skills
Languages
Python
Go
Rust
DevOps
CI/CD
GitOps
GitHub Actions
Docker/Compose
Terraform
AWS SAM
CloudFormation
AWS
Lambda
DynamoDB
API Gateway
Step Functions
SQS/SNS
EventBridge
CodePipeline
SAR
Pinpoint
Kinesis/Firehose
AFT
General
Testing/TDD
Packaging/Deployment
Documentation
Git/GitHub
Shell/Command Line
REST/GraphQL
Agile
Publications
Modelling of the Overcasting Reinforcement Process using the LS-DYNA ® ICFD Solver
12th European LS-Dyna Conference 2019
01 October 2019
Innovative use of CFD models combined with liquid metal crystallisation and genetic algorithms in order to predict liquid-solid aluminium bonding to a composite insert.
A Machine Learning Approach to Model Interdependencies between Dynamic Response and Crack Propagation
MDPI Sensors
30 November 2020
Application of machine learning techniques to thermo-mechanical fatigue damage prediction in aerospace materials.
Interests
Open Source
Contributing
Maintenance
Collaboration
Science & Technology
Astronomy
Physics
Materials Science
Spaceflight
Robotics