Senior MLOps / LLM Engineer

Description

We’re seeking an experienced DevOps / LLMOps or MLOps / 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