# Treasury Engineering Team Lead at Jobgether

> Remote · Switzerland · Staff · Other · open. Source: https://alderhq.app/jobs/lever%3Ajobgether%3A34a69b0b-9fa6-4d58-b749-e2f1acb221a6 (read 2026-11-12).

## Facts (observed)

- Company: [Jobgether](https://alderhq.app/companies/jobgether)
- Location text: Switzerland
- Where it can be done from (inferred): Remote · Switzerland (evidence: "Location: Switzerland")
- Posted: 2026-11-12 (0 days ago)
- First seen by alder: 2026-11-12 · last verified: 2026-11-12
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://jobs.lever.co/jobgether/34a69b0b-9fa6-4d58-b749-e2f1acb221a6
- Skills listed (inferred): TypeScript, JavaScript, Node.js, PostgreSQL, SQL

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (Switzerland, n 82): p25 CHF 88k, median CHF 90k, p75 CHF 90k

## Description (the employer's text)

### Accountabilities

Lead, develop, and grow a multidisciplinary Treasury Engineering team of approximately 10 professionals across backend, frontend, and QA.

Define team structure, hiring priorities, and recruitment processes to attract and retain strong engineering talent.

Coach engineers through regular feedback, individual development plans, and opportunities to strengthen their technical expertise and production ownership.

Establish priorities, coordinate delivery plans with Finance and Engineering stakeholders, and ensure the team focuses on measurable business outcomes.

Oversee the development, maintenance, and scalability of banking integrations, transaction reconciliation systems, and data pipelines supporting money movements, tax payments, and cash management.

Ensure end-to-end visibility of financial transactions, from the initial user request through settlement and final accounting entries.

Develop monitoring and reconciliation mechanisms to identify and prevent financial discrepancies, duplicate transactions, processing delays, mismatched balances, and integration failures.

Lead complex technical investigations across payment service providers, ledgers, wallets, payouts, cards, and cryptocurrency payment infrastructure.

Address technical incidents at their root cause by improving code, data models, and integrations rather than relying solely on temporary fixes.

Ensure financial operations are reliable, observable, idempotent, and safe to retry, translating post-incident findings into preventive controls, automated tests, and monitoring solutions.

Drive the adoption of AI agents and automation tools to support alert triage, investigation, troubleshooting, and resolution verification.

Design safe AI-driven workflows with appropriate human oversight, maker-checker validation, escalation mechanisms, and comprehensive audit trails.

Act as the bridge between Finance and Engineering, translating financial requirements into technical priorities and communicating engineering constraints in business-friendly terms.

Balance operational urgency with long-term engineering quality, ensuring that financial systems remain reliable as transaction volumes and business complexity increase.

Monitor team performance through key indicators, including financial close timelines, reconciliation accuracy, transaction completion rates, and alert quality.

Participate in a shared on-call rotation and help maintain the reliability and availability of critical financial systems.

### Requirements

Significant professional experience in software engineering, including at least 1 year of experience leading engineering teams and managing delivery in complex technical environments.

Mandatory experience building fintech systems or working within the financial technology sector.

Proven experience hiring, mentoring, and developing engineers, providing constructive feedback, and supporting professional growth.

Strong backend engineering expertise, ideally with Node.js and TypeScript. Candidates with other server-side technology backgrounds are welcome, provided they are comfortable working with Node.js and TypeScript.

Solid SQL and database engineering knowledge, including practical experience with PostgreSQL.

Strong understanding of production systems and experience troubleshooting high-volume applications, identifying root causes, and resolving complex technical incidents.

Good knowledge of concurrency, idempotency, retry mechanisms, queues, and eventual consistency.

Experience designing and maintaining reliable, scalable, and observable financial or transactional systems.

An AI-native engineering mindset, with practical experience using AI coding assistants and agent tools such as Claude Code, Cursor, or Codex.

Ability to orchestrate multiple AI agents, create clear technical specifications and reusable agent instructions, and critically review AI-generated outputs while understanding when human intervention is necessary.

Excellent cross-functional communication skills, with the ability to explain complex technical and financial issues to both engineering and finance stakeholders.

### How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

#LI-CL1

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/lever%3Ajobgether%3A34a69b0b-9fa6-4d58-b749-e2f1acb221a6 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.
