About the Role
We are looking for an Applied AI Systems Engineer to design and build intelligent systems where machine learning and software engineering come together.
This role focuses on creating end-to-end AI systems, not just models. You will work on data ingestion, model integration, orchestration, and production deployment, ensuring that AI solutions are reliable, scalable, and aligned with real product needs.
If you enjoy thinking in systems, care about clean architecture, and want to apply AI in practical, high-impact ways, this role is for you.
Responsibilities
- Design and implement end-to-end AI systems used in production.
- Integrate machine learning and LLM-based components into existing platforms.
- Build orchestration layers for AI workflows and pipelines.
- Develop APIs and services that expose AI capabilities.
- Ensure system reliability, scalability, and observability.
- Collaborate with product and engineering teams to translate requirements into AI solutions.
- Continuously improve system architecture and performance.
Technical Stack
You will work with technologies such as:
AI and Machine Learning
- Python as the primary development language
- Integration of LLMs and generative AI systems
- Prompt engineering and structured outputs
- Embeddings and semantic search
Systems and Backend
- Service-oriented and microservice architectures
- RESTful APIs
- Async processing and job orchestration
Infrastructure and Data
- Containerized deployments with Docker
- Cloud platforms (AWS, GCP, or similar)
- SQL and NoSQL databases
- Monitoring, logging, and system observability
Requirements
- Strong software engineering background.
- Hands-on experience building AI-enabled systems.
- Understanding of machine learning concepts and trade-offs.
- Experience deploying and maintaining production systems.
- Ability to work in ambiguous problem spaces.
- Strong ownership and communication skills.
Nice to Have
- Experience with RAG architectures or AI agents.
- Familiarity with vector databases and search systems.
- Exposure to MLOps or AI system monitoring.
- Experience working in product-led or startup environments.
What We Offer
- Work on real-world AI systems with measurable impact.
- High autonomy and technical ownership.
- A strong engineering culture focused on quality and clarity.
- Competitive compensation and growth opportunities.
- Flexible, remote-friendly working environment.
- Continuous learning in a fast-evolving field.
Apply
If you are excited about building AI systems that actually run in production, we would love to hear from you.
Apply and help us build intelligent systems that scale.