AI Engineer
Posted 19 days ago · 26 applicants
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The role in plain words
- 4+ years of professional software engineering experience, including work on AI/ML-powered systems
- Proficiency in Python and experience building production backend services
- Experience working with cloud environments and containerization
- Hands-on experience in building and deploying machine learning or LLM-based systems in real-world settings
- Solid understanding of distributed systems, data pipelines, and system reliability
- Docker and Kubernetes experience
- Experience with agent frameworks (LangGraph, Smolagents, or similar)
- Prior work on developer tools, code intelligence, or AI-driven software systems
- Exposure to MLOps practices (CI/CD for ML, model monitoring, evaluation pipelines)
- Familiarity with frontend or full-stack systems
Extracted from the job description · kept up to date automatically
Who this suits
Full job description
Original listing · kept for referenceRole Overview
We’re looking for an AI Engineer to design, build, and scale the core systems powering our agentic platform, translating advanced AI techniques into robust, production-grade applications.
You’ll work across the stack: from backend infrastructure and APIs to AI model integration, orchestration, and evaluation. The ideal candidate thrives on building high-quality systems end-to-end, and has hands-on experience bringing AI-powered products into real-world use.
What You’ll Do
• Design, build, deploy, and maintain backend services and workflows that integrate LLMs, RAG, and tool-using agents, with built-in guardrails, fallbacks, and evaluation.
• Work closely with the team across research and product to turn prototypes into robust, production-ready systems.
• Play a pivotal role in shaping how we build - technically, operationally, and culturally - as part of an early-stage team.
What You Bring
• 4+ years of professional software engineering experience, including work on AI/ML-powered systems
• Proficiency in Python and experience building production backend services, including working with cloud environments and containerization (Docker, Kubernetes is a plus).
• Hands-on experience in building and deploying machine learning or LLM-based systems in real-world settings.
• Solid understanding of distributed systems, data pipelines, and system reliability.
• Strong ownership and product-minded thinking, able to collaborate effectively, understand user pain points, propose solutions, and operate well in a fast-paced early-stage environment.
Bonus Points If You Also Have
• Experience with agent frameworks (LangGraph, Smolagents, or similar).
• Prior work on developer tools, code intelligence, or AI-driven software systems.
• Exposure to MLOps practices (CI/CD for ML, model monitoring, evaluation pipelines).
• Familiarity with frontend or full-stack systems.
• Experience with NLP.
Questions about this role
- This listing did not state a salary. We only show pay when the employer publishes it.
- 4+ years of professional software engineering experience, including work on AI/ML-powered systems, Proficiency in Python and experience building production backend services, Experience working with cloud environments and containerization, Hands-on experience in building and deploying machine learning or LLM-based systems in real-world settings, Solid understanding of distributed systems, data pipelines, and system reliability