Overview
We’re seeking an experienced Dev / LLMOps Engineer to design, deploy, and maintain the infrastructure supporting Large Language Model (LLM) platforms. This role blends DevOps best practices with AI / ML expertise, with a focus on building and scaling agentic AI systems that integrate directly with LLMs. You’ll drive development of intelligent, autonomous agents while ensuring reliability, scalability, and performance across training, fine-tuning, and deployment pipelines.
English fluency is a MUST for this role! Only candidates with level C1 or C2 will be considered :
- A1 Beginner
- A2 Elementary
- B1 Intermediate
- B2 Upper-Intermediate
- C1 Advanced
- C2 Proficient
Responsibilities
- Own strategy and execution of agentic AI systems using LLMs and autonomous decision-making components
- Build prototypes and scale them into MVPs demonstrating real-world AI viability
- Collaborate with engineering and product teams to embed LLM agents into user-facing features
- Design and manage CI / CD pipelines for LLM training and deployment workflows
- Provide technical leadership on DevOps, security, and deployment strategies for AI / ML models
Requirements
- 5+ years building and deploying ML or GenAI systems in production, with strong architectural and systems-level ownership
- 2+ years of proven experience with LLM integration, LLM-based agents, or autonomous reasoning systems
- End-to-end AI / ML delivery : data prep, training, evaluation, deployment, monitoring
- Cloud expertise (AWS, GCP, or Azure) with CI / CD pipelines, multi-tenant deployments, and infrastructure automation
- Experience with Databricks and familiarity with Langchain / GenAI toolkits
- Strong agility and ability to deliver in fast-moving product environments
Nice To Have
- Advanced degree (MS / Ph.D.) in ML, Computer Science, or related field
- Deep expertise in DevOps / MLOps practices and scaling secure, enterprise-grade AI workflows
- Broader data engineering knowledge, especially in Databricks
- Background in aviation industry