Forward Deployed AI Engineer

Tradition; Vaud; On-site; CHF 120,000 - 180,000; Full time

Job summary

Tradition, based in Lausanne, seeks a Forward Deployed AI Engineer to collaborate with business teams, design end-to-end AI solutions, and deploy on-prem LLMs via vLLM. You will own the delivery lifecycle, automate workflows, and ensure cross-region compliance.

The role requires strong Python and software fundamentals, stakeholder management, and experience with CI/CD pipelines and observability tools. immediate start is desirable.

Qualifications

• Degree in Computer Science, Software Engineering, or a related field.
• 2+ years of post-graduation software engineering experience with stakeholder exposure.
• Strong Python and solid software engineering fundamentals.
• Excellent stakeholder management and discovery skills.
• Autonomy to scope and own projects and drive adoption.
• Structured thinking about processes and improving workflows.
• Experience with CI/CD pipelines and deployment automation.
• Familiarity with monitoring/observability tools (Prometheus, Grafana).
• Comfort building against LLM APIs and models served via vLLM.

Responsibilities

• Collaborate with business teams to map workflows and scope end-to-end AI solutions.
• Analyze and redesign processes, automate activities, and deliver measurable improvements.
• Own solutions through discovery, design, build, deployment, and ongoing improvement.
• Build applications, AI agents and agentic workflows using the platform and on-prem LLMs via vLLM.
• Support platform deployment across regions, considering regulatory requirements.
• Establish and maintain deployment pipelines and CI/CD for AI apps.
• Monitor health, model performance and platform usage; drive reliability and scalability.
• Deliver demonstrations, trainings, and documentation to drive adoption.
• Capture learnings and feed back into the core platform.

Skills

Python

Software engineering fundamentals

Stakeholder management

Project ownership

Process analysis

CI/CD pipelines

Observability tools

LLM APIs

Education

CS or Software Engineering degree

Tools

Prometheus

Grafana

vLLM

Hermes Agent

OpenClaw

n8n

Langflow

JavaScript

Job description

Tradition is the interdealer broking arm of Compagnie Financière Tradition and one of the world's largest interdealer brokers in over-the-counter financial and commodity related products. CFT is represented in over 28 countries, employing over 2,500 people.

Tradition’s goal is to provide superior client services. It believes its business success is a direct reflection of its employees and recruits. As such, teamwork, creativity, reliability and integrity are components of a work ethic taken very seriously since the company was founded in 1959.

Tradition is currently seeking to appoint a Forward Deployed AI Engineer to be based within the Lausanne office.

Main responsibilities within the Forward Deployed AI Engineer position include:

• Work closely with teams across the business to understand their workflows, identify opportunities where the platform can add value, and scope solutions end to end.
• Map and analyse existing processes, working collaboratively with process owners to redesign workflows, automate suitable activities, and deliver measurable improvements.
• Own solutions through the full delivery lifecycle, from initial discovery and design through to build, deployment, iteration and ongoing improvement based on real-world feedback.
• Build applications, AI agents and agentic workflows using the platform and on-premises LLMs served via vLLM.
• Support the deployment and adaptation of the platform across multiple regions, taking into account differences in infrastructure, regulatory and compliance requirements.
• Establish and maintain deployment pipelines and CI/CD processes for AI applications, ensuring reliable and repeatable releases.
• Monitor application health, model performance and platform usage, identifying opportunities to improve reliability, performance and scalability.
• Deliver demonstrations, walkthroughs and training sessions, supported by clear and practical documentation to drive adoption across the business.
• Capture learnings and feedback from deployments and feed these back into the core platform, helping to continuously improve the solution and streamline future implementations.

Key skills, experience and competencies required to be successful in this role:

• Degree in Computer Science, Software Engineering, or a related field
• 2+ years of post-graduation experience- as a software engineer, in a role where you worked directly with stakeholders or end users.
• Strong software engineering fundamentals and strong Python. You write code that other people can pick up, run, and maintain
• Strong stakeholder management skills : you can run a discovery conversation, ask the questions that matter, push back on a request that won't work, and translate a vague business problem into a scoped piece of work
• Autonomy in scoping and owning projects. You set your own priorities, drive progress toward broader team goals, and see work through to adoption rather than simply handing it over to others.
• A structured way of thinking about processes: you can take a workflow apart, see which steps carry the value and which are there by habit, and propose a better design rather than automating the existing one as it stands
• Experience with CI/CD pipelines and deployment automation
• Familiarity with application/system monitoring and observability tools (e.g. Prometheus, Grafana or similar)
• Comfortable building against LLM APIs and consuming models served via vLLM (no deployment/ops experience required)

Desirable:

• Experience with AI agent frameworks such as Hermes Agent, OpenClaw, or similar
• Familiarity with visual workflow orchestration platforms (e.g. n8n, Langflow)
• Familiarity with JavaScript and developing small front-end applications
• Available to start immediately

Tradition welcome all suitable applications and are an equal opportunity employer who value diversity. All employment is decided on the basis of qualifications and merit.