Full-Stack AI Engineer
Are you passionate about building AI-powered solutions that solve real business challenges? We are looking for a Middle AI Engineer to join our fully remote team and contribute to the development of advanced intelligent documentation platforms for the telecommunications domain.
At Sigma Software, we work with global Customers on innovative projects that combine modern engineering practices with cutting-edge AI technologies. In this role, you will participate in the full development lifecycle, from research and architecture discussions to implementation and deployment of scalable AI-enabled solutions.
Why join us? You will have the opportunity to work with modern LLM orchestration frameworks, cloud-native infrastructure, and enterprise-scale AI integrations while growing professionally in a collaborative and flexible environment.
CUSTOMER
Our Customer is a European telecommunications company focused on digital transformation and intelligent content management solutions. Together, we are developing AI-powered tools that optimize documentation workflows, automate content generation, and improve operational efficiency through modern agent-based AI systems and scalable enterprise infrastructure.
PROJECT
The project focuses on developing advanced AI-driven documentation solutions powered by large language models, orchestration frameworks, and cloud-native backend services. The platform integrates AI capabilities with internal and third-party systems while maintaining high standards of scalability, observability, and engineering quality.
This role combines AI engineering, Back-end development, and partial Full-Stack collaboration, giving you the opportunity to contribute across APIs, integrations, frontend features, and AI-enabled workflows in a modern Agile environment.
Job Description
- Participate in research and development activities for AI-driven documentation solutions
- Take ownership of features from concept through implementation and deployment
- Develop and maintain backend services and REST APIs using Python and modern async frameworks
- Integrate AI capabilities and agent-based workflows into existing platforms and services
- Collaborate on frontend functionality using React, TypeScript, and Vite where required
- Work with LLM orchestration frameworks and AI tooling integrations
- Ensure system reliability, scalability, observability, and maintainability
- Collaborate closely with AI engineers, frontend developers, product managers, and designers
- Participate actively in Agile ceremonies including sprint planning, refinements, demos, and stand-ups
- Contribute to CI/CD pipelines, deployment automation, and Kubernetes-based infrastructure
- Troubleshoot and resolve issues across frontend, backend, and infrastructure layers
- Continuously evaluate and adopt emerging AI technologies and engineering best practices
Qualifications
- At least 3 years of commercial software development experience
- Solid experience with Python and async web frameworks such as FastAPI
- Experience with React and TypeScript
- Experience with LangChain, LangGraph, or similar LLM orchestration frameworks
- Familiarity with AI tool integration protocols and agentic workflows
- Experience with cloud infrastructure
- Strong experience building and maintaining REST APIs
- Experience with relational databases and ORMs, preferably PostgreSQL
- Practical experience writing automated tests using frameworks such as pytest or Playwright
- Hands-on experience with Docker and Kubernetes environments
- Understanding of CI/CD pipelines and deployment workflows
- Ability to debug issues across the full application stack
- Strong Git skills and experience working in code-review-driven environments
- Experience working in Agile teams
Upper-Intermediate level of English
WILL BE A PLUS
- Experience with Helm
- Experience with observability tooling such as Grafana, OpenTelemetry, or CloudWatch
- Experience integrating enterprise authentication systems such as OAuth2/OIDC or Keycloak
- Experience developing editor or IDE extensions
- Experience using AI coding assistants in daily development workflows
- Experience with enterprise-scale AI platforms
- Experience with cloud-native distributed systems
- Exposure to AI-assisted developer tooling
- Experience contributing to architecture decisions
- Knowledge of documentation tooling ecosystems