Founding AI Platform Engineer (MLOps / Backend)

Join Whizdom.ai as a Founding AI Platform Engineer (MLOps / Backend). Architect and own the backbone of the ML and GenAI systems - driving reliability, scalability, and seamless deployment from day one.

About the company:

Whizdom AI is an early-stage AI startup building products around recommendation systems, personalisation, and GenAI agents. The company is a small team working directly on real customer problems, shipping quickly, measuring outcomes, and iterating fast. Everyone here is expected to take ownership, improve systems proactively, and help build the engineering foundations the company will scale on.

The Role:

We are looking for a Founding AI Platform Engineer to build and own the engineering foundation behind Whizdom AI’s ML and GenAI products.

You will work at the intersection of backend engineering, infrastructure, and MLOps, ensuring that AI systems are reliable, scalable, observable, and production-ready. You will be responsible for building the platform, services, and workflows that support recommendation systems, GenAI agents, model deployment, experimentation, and customer-facing integrations.

As part of a small early-stage team, you will have a direct impact on engineering decisions, platform architecture, and the systems the company will scale on.

Key Responsibilities:

• Develop and maintain infrastructure and tooling for training, evaluating, deploying, and monitoring ML models and GenAI services;

• Build and maintain backend services, APIs, and production systems powering AI workflows and customer integrations;

• Create and optimise CI/CD pipelines, testing processes, release workflows, and environment management practices;

• Implement observability solutions for service health, model behaviour, agent quality, latency, costs, and system failures;

• Establish and maintain best practices for model, prompt, dataset, configuration, and release lifecycle management;

• Support experimentation and measurement infrastructure to evaluate product and ML improvements;

• Improve system reliability, scalability, security, performance, and cost efficiency;

• Troubleshoot production issues across the full technology stack and implement long-term solutions;

• Collaborate with ML engineers, backend engineers, and product teams to deliver production-ready AI capabilities;

• Contribute to defining engineering standards and platform architecture as the company grows.

Required Skills & Experience:

• 4+ years of experience in software engineering or equivalent hands-on experience building production systems;

• Strong Python programming skills;

• Experience with backend services, APIs, cloud infrastructure, CI/CD, testing, observability, and automation;

• Experience designing reliable and scalable systems;

• Understanding of software reliability, performance optimisation, maintainability, and cost trade-offs;

• Ability to collaborate with ML and product teams and translate ambiguous requirements into technical solutions;

• Strong ownership mindset and ability to work independently in a fast-paced environment;

• Upper-Intermediate English level or higher.

Nice to Have:

• Experience with MLOps workflows, including model training, evaluation, deployment, and monitoring;

• Experience deploying ML models or LLM-based applications in production;

• Experience with recommendation systems, personalisation systems, or AI agents;

• Experience with experimentation platforms, analytics pipelines, or event-driven architectures;

• Experience with prompt versioning, retrieval-augmented generation (RAG), vector databases, or search infrastructure;

• Experience working in early-stage startups or building products from the ground up.

Gross monthly compensation: EUR 5,000–10,000 (B2B contract).

The final offer depends on:

• Relevant professional experience;

• Technical assessment results;

• Interview performance;

• Overall alignment with the role requirements.

Benefits:

• Direct access to the founders and the opportunity to influence platform and engineering decisions;

• High-ownership role with the opportunity to build production foundations from the early stages of the company;

• Opportunity to work on recommendation systems and GenAI products used by real customers;

• Flexible remote environment with strong overlap with European time zones preferred;

• Small team environment with low bureaucracy and significant impact on product development.

Interview Process:

• A 30-minute interview with a member of our HR team to get to know you and your experience;

• A 1-hour technical interview;

• A final interview to gauge your fit with our culture and working style.

Equal Opportunity Statement:

Employment decisions are based on qualifications, skills, experience, and business needs without regard to gender, age, ethnicity, religion, disability, sexual orientation, or any other protected characteristic.

Data Privacy:

Personal data submitted during the recruitment process will be processed solely for recruitment purposes and in accordance with applicable data protection legislation, including the General Data Protection Regulation (GDPR).

If you find this opportunity right for you, don't hesitate to apply or get in touch with us if you have any questions!