About the job
Are you driven by a passion for artificial intelligence and eager to foster innovation in a dynamic, impactful setting? If you possess experience in developing AI-enhanced applications and take pleasure in mentoring others, we would love to have you join Nexthink as a Senior AI Engineer!
In this pivotal role within our AI team, you will prototype, refine, and deploy AI-driven functionalities into Nexthink’s cloud platform. You will guide architectural decisions, establish best practices, and ensure that our AI systems are scalable, observable, and production-ready.
Key Responsibilities:
AI Engineering & Architecture
Design, develop, and manage production-grade AI/ML systems, including applications powered by large language models (LLMs), natural language processing (NLP) models, retrieval-augmented generation (RAG) pipelines, and multi-agent systems.
Make critical architectural choices regarding model selection, training methodologies, fine-tuning processes, retrieval frameworks, orchestration layers, and infrastructure.
Integrate external AI services, such as LLM providers, into Nexthink’s cloud ecosystem.
Tackle engineering challenges linked to data collection, retrieval, evaluation, inference, latency, and cost optimization.
AI Done Right – Evaluation & Quality
Establish robust online and offline evaluation frameworks along with success metrics.
Implement dashboards and monitoring systems to gauge quality and identify regressions in production.
Create automated evaluation pipelines for prompts, embeddings, models, and agent workflows.
Ensure the observability and reliability of AI systems at scale.
MLOps & Cloud Engineering
Develop and uphold reproducible machine learning pipelines and CI/CD workflows for AI components.
Oversee the deployment, monitoring, and lifecycle of models and AI artifacts in a production environment.
Enhance systems for scalability, performance, throughput, and cost efficiency.
Utilize AWS or equivalent cloud platforms, Docker, and orchestration frameworks (Kubernetes/ECS).
Product & Cross-Functional Collaboration
Work closely with product managers, designers, software engineers, and data scientists.
Translate ambiguous product requirements into clear, incremental, and testable engineering plans.
Proactively suggest new AI capabilities based on user insights and technological advancements.
Clearly communicate intricate AI concepts to both technical and non-technical stakeholders.
Leadership & Mentorship
Guide and mentor junior AI engineers in best practices for production.
