About this role
The challenge
As a Senior AI Specialist Engineer, you will play a key role in scaling Jotelulu’s codebase and integrating AI capabilities into our cloud platform. Your mission will be to design and implement scalable, high-performance solutions, including APIs, AI architectures, and generative AI integrations, enhancing both customer experience and internal processes. You will work on building AI-driven features such as recommendation systems, predictive models, RAG pipelines, and AI agents, while ensuring code quality, reliability, and performance.
You will be part of a full-stack development team responsible for building and maintaining customer-facing products at cloud provider scale. The team develops self-service IaaS, PaaS, and SaaS solutions, integrating modern AI capabilities directly into the platform. Working in a fast-paced, collaborative, and agile environment, you will contribute to a growing engineering team focused on scalability, stability, and continuous improvement.
Collaboration will be essential. You will work closely with a multidisciplinary engineering team, as well as product and program management stakeholders, to define requirements and deliver impactful features. You will also interact with internal teams to investigate and resolve issues, ensuring a reliable and secure platform while contributing to engineering best practices and team culture.
Requirements that are important for us
We are looking for a Senior AI Specialist Engineer with strong experience in software development and AI integration, capable of working with complex systems and delivering scalable solutions in a cloud environment.
Hard skills
- Experience in software development with Python frameworks such as FastAPI, Django, or Flask.
- Experience with relational databases (MySQL, PostgreSQL) and vector databases.
- Experience with asynchronous architectures, job queues, caching, and background processes (NATS, RabbitMQ, Redis).
- Experience designing and implementing scalable APIs, AI architectures, and abstraction layers.
- Experience integrating generative AI solutions using tools such as OpenAI, Google GenAI, or similar frameworks (HayStack, Langchain).
- Experience building recommendation systems, predictive models, RAG pipelines, and AI agents.
- Strong knowledge of engineering best practices across the full development lifecycle, including testing, deployment, and production environments.
- Experience working in agile environments and collaborating with product or program management teams.
- Ability to work across the stack, connecting AI microservices with backend and frontend systems.
Soft skills
- Strong communication and collaboration skills, with the ability to work closely with technical teams and stakeholders.
- Ability to tackle complex technical challenges with practical and creative solutions.
- Proactive mindset, with initiative to investigate, resolve issues, and improve systems.
- Ability to set clear goals, track progress, and communicate effectively.
- Willingness to contribute to team culture, collaborate, and support continuous improvement.
Tools
- Python frameworks (FastAPI, Django, Flask).
- Databases: MySQL, PostgreSQL, vector databases.
- Messaging and async tools: NATS, RabbitMQ, Redis.
- AI frameworks and platforms: OpenAI, Google GenAI, HayStack, Langchain.
- Cloud platforms: AWS, GCP, Azure, VMware.
- Development and collaboration tools: Jira, Confluence, Bitbucket, GitLab.
- CI/CD tools and practices.
- Automation and workflow tools such as n8n or Zapier.
