Forward Deployed Engineer at Thought Machine
- Location
- New York, United States
- Compensation
- $160k-$220k
Thought Machine is revolutionizing the banking industry with Vault, its cloud-native core platform used by 18 tier-one banks globally. As a Forward Deployed Engineer in New York, you'll embed directly with client engineering teams to architect and deploy mission-critical infrastructure at scale.
If you have deep expertise in Kubernetes, Istio, and Terraform and want to solve complex problems for the world’s largest financial institutions, this is the perfect opportunity to shape the future of global finance.
What's the next step?
Thought Machine are hiring from Jack's network. Talk to Jack for free and get a direct introduction to the team, if a good fit.
Role overview
You will be the primary technical interface for Thought Machine, embedding with client engineering teams to design, deploy, and optimize the Vault platform. Balancing infrastructure depth with production-grade coding, you’ll manage the full project lifecycle from presales to production, ensuring high-availability systems perform at scale for the world’s largest financial institutions.
About Thought Machine
Thought Machine is a financial technology company that builds next-generation, cloud-native core banking and payment platforms for banks and digital banking propositions worldwide.[4][9][13] Its flagship product, Vault Core, is a modern, configurable core banking platform designed to run the full operations of banks according to contemporary software engineering best practices, enabling institutions of all sizes to become cloud-native with minimal disruption.[2][9][13] Thought Machine’s technology allows banks to create, manage, and control any financial product or payment scheme they desire on a flexible, high‑performance, cloud-based architecture, helping to replace legacy infrastructure and eliminate the constraints and risks associated with traditional core systems.[2][5][6][11]
What you will do
- Embed directly with bank engineering teams to architect and deploy Vault on cloud infrastructure, ensuring systems are configured for high availability and disaster recovery.
- Write and ship production-ready Python or Go code to implement business logic and bridge the gap between Thought Machine’s core product and the client’s delivery requirements.
- Act as the connective tissue between product engineering and clients, feeding real-world insights back to internal teams to drive continuous platform improvement and feature development.
Who this is a fit for
- Possesses production-level expertise in Kubernetes, Istio, and Infrastructure-as-Code tools like Terraform, specifically within AWS or GCP environments for mission-critical systems.
- Demonstrates a strong background in software engineering with the ability to write credible production code in Go, Python, or Java within complex enterprise environments.
- Exhibits exceptional communication skills, with the ability to explain intricate technical concepts clearly to both engineering leads and non-technical stakeholders in a client-facing capacity.
Why this role is remarkable
- Join a high-growth Forward Deployed Engineering function established in mid-2025, offering a unique opportunity to shape the team’s operational playbook and consulting standards from the ground up.
- Work with a $2.7B Series E fintech that has already secured 18 tier-one banking clients, providing immense stability alongside the fast-paced nature of a scaling engineering team.
- Tackle deep technical challenges in core banking infrastructure where availability and security are non-negotiable, acting as the most senior technical representative in high-stakes client environments.
How Jack & Jill work together
What happens next?
Jack’s an AI agent for job searching and career coaching. He works for you.
Jill is the AI recruiter working for the company. She recruits from Jack’s network.
If your profile’s a match and Thought Machine wants to meet, Jill will make the intro. In the meantime, Jack will send you excellent alternatives.