Senior AI Engineer
Listed on 2026-07-12
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Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer, AI Reliability/ Performance Engineer
Job Description
Are you passionate about AI and eager to drive innovation in a fast‑paced, impact‑driven environment? Do you have experience developing AI‑powered applications and enjoy mentoring others? If so, we invite you to join Nexthink as a Senior AI Engineer!
As a senior member of the AI team, you will prototype, mature, and ship AI‑powered capabilities into Nexthink’s cloud platform. You will lead architectural decisions, establish best practices, and ensure AI systems are scalable, observable, and production‑grade.
ResponsibilitiesAI Engineering & Architecture
Design, develop, and operate production‑grade AI/ML systems, including LLM‑powered applications, NLP models, RAG pipelines, and multi‑agent systems.
Make key architectural decisions across model selection, training strategies, fine‑tuning, retrieval mechanisms, orchestration layers, and infrastructure.
Integrate external AI services (e.g., LLM providers) into Nexthink’s cloud platform.
Solve engineering challenges related to data collection, retrieval, evaluation, inference, latency, and cost optimization.
AI Done Right – Evaluation & Quality
Define robust online and offline evaluation frameworks and success metrics.
Instrument dashboards and monitoring systems to track quality and detect regressions in production.
Design automated evaluation pipelines for prompts, embeddings, models, and agent workflows.
Ensure observability and reliability of AI systems at scale.
Implement and maintain reproducible ML pipelines and CI/CD workflows for AI components.
Manage deployment, monitoring, and lifecycle of models and AI artifacts in production.
Optimize systems for scalability, performance, throughput, and cost.
Work with AWS (or equivalent cloud platforms), Docker, and orchestration frameworks (Kubernetes/ECS).
Product & Cross‑Functional Collaboration
Collaborate closely with product managers, designers, software engineers, and data scientists.
Translate ambiguous product requirements into incremental, testable engineering plans.
Proactively propose new AI capabilities based on user insights and technology advancements.
Communicate complex AI concepts clearly to both technical and non‑technical stakeholders.
Mentor and coach junior AI engineers in production best practices.
Establish engineering standards and AI best practices within the team.
Foster a culture of experimentation, learning, and knowledge sharing.
QualificationsBsc/Master’s degree in Computer Science, Machine Learning, Data Science, or related field.
5+ years of professional software engineering experience, including shipping and operating cloud services in production.
Hands‑on experience in LLM‑powered production applications or ML/NLP applications.
Strong proficiency in Python and AI frameworks.
Strong understanding of machine learning fundamentals (supervised/unsupervised learning, optimization, model evaluation).
Solid understanding of machine learning fundamentals (training, optimization, evaluation).
Experience with NLP systems (embeddings, semantic search, retrieval systems, text classification, etc.).
Experience integrating and operating LLMs (prompting, evaluation, observability, RAG, agentic workflows).
Hands‑on MLOps experience: reproducible pipelines, experiment tracking, automated evaluation, CI/CD for models and prompts.
Knowledge of reinforcement learning, retrieval‑augmented generation (RAG), and multi‑agent AI architectures.
Strong data intuition: ability to inspect logs, design metrics, and quickly identify regressions.
Proven experience with AWS and cloud‑based AI deployments.
Strong communication skills in English, capable of explaining complex AI concepts to technical and non‑technical stakeholders.
Excellent problem‑solving skills and ability to work in a fast‑paced, collaborative environment.
Strong plus:
Strong AWS (or equivalent cloud platform) experience for scalable AI infrastructure.
Experience optimizing models for latency, throughput, and cost.
Experience fine‑tuning large language models.
Familiarity with multi‑agent systems and orchestration frameworks.
Experience designing AI systems in enterprise or B2B environments.
We’re excited about pushing the boundaries of AI and…
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