AI Engineer; Hybrid

Overview

As a Senior AI Engineer, you will help lead the evolution of modern workplace productivity through AI-driven experiences and services across core business applications. The team builds the foundational platforms and experiences that bring large language models (LLMs) and real-time intelligence into everyday tools, combining the power of advanced AI with enterprise data and deep application integration to streamline content creation, navigation, and comprehension.

We are looking for a creative Senior AI Engineer who will collaborate with software engineers, researchers, and product managers to translate product needs into well-defined machine learning problems, push the state of the art in LLM capabilities, and take solutions from prototype to large-scale production. You will help drive an AI-first engineering culture while mentoring junior engineers on the team.

In this role, you will build the systems that make AI reliable in production: developing APIs, platforms, and services around AI features; designing data pipelines and feedback loops; deploying and fine-tuning state-of-the-art deep learning models; orchestrating prompts and tools; and monitoring AI-specific signals—such as drift, hallucinations, safety, and cost—alongside traditional service reliability metrics.

Join us in empowering people through AI by bringing cutting-edge deep learning into everyday work  operate with a growth mindset, value innovation and collaboration, and are committed to building an inclusive environment rooted in respect, integrity, and accountability. If you are passionate about applying advanced AI to create meaningful impact for millions of users, this role is for you.

Responsibilities

• Leadership & cross-functional collaboration
  Partner with product management and engineering teams to define the technical vision and roadmap, co-own scenario goals, and translate complex product requirements into scientific plans and production-ready AI solutions. Lead technical design reviews and drive alignment around quality, latency, scalability, and cost objectives.
• Generative AI & advanced technologies
  Apply deep expertise in generative AI, large language models (LLMs), and modern AI frameworks to design and deliver intelligent features and automation within the platform.
• Architecture & cloud integration
  Design and implement scalable, reliable, and secure AI services in a cloud environment, optimizing performance, cost efficiency, and compliance while ensuring production-grade resilience.
• Technical innovation & AI strategy
  Identify and evaluate emerging AI technologies, frameworks, and methodologies. Pioneer new approaches in retrieval-augmented generation (RAG), prompt orchestration, and continuous learning to deliver adaptive and resilient AI systems.
• Mentorship & inclusive engineering culture
  Provide technical mentorship, guidance, and peer coaching to other engineers. Foster a culture of innovation, continuous learning, and inclusion while promoting best practices in code quality, security, and responsible AI.

Required Qualifications

• Bachelors degree in Computer Science, Software Engineering, or a related technical field.

Preferred Qualifications

• Masters degree in Computer Science or a related technical field AND 6+ years of technical engineering experience
• OR Bachelors degree in Computer Science or a related technical field AND 8+ years of technical engineering experience
• OR equivalent practical experience.
• 7+ years of technical leadership with a proven track record of delivering mission-critical AI/ML solutions in production, including model deployment, evaluation, monitoring, and lifecycle management in large-scale environments.
• Hands-on experience with modern generative AI and machine learning frameworks (such as PyTorch, Tensor Flow, or Hugging Face) and deep understanding of large language models, embeddings, prompt engineering, and model fine-tuning.
• Proven ability to design, build, and operate scalable, fault-tolerant microservices and distributed data platforms in a cloud environment. Experience developing APIs and services, designing data pipelines and feedback loops, and implementing secure and compliant AI solutions.
• Demonstrated experience leading complex AI/ML initiatives from concept to production, mentoring engineers, and driving technical decision-making in cross-functional environments.
• Experience ensuring AI systems meet enterprise-grade security, privacy, and responsible AI standards, including working in regulated or high-compliance environments.
• Experience with retrieval-augmented generation (RAG), multimodal systems, prompt orchestration, model alignment, safety evaluation, and emerging AI methodologies.
• Hands-on experience with MLOps practices, model experimentation and deployment pipelines, large-scale data processing (e.g., Spark, data lakes), and establishing robust telemetry, evaluation, and observability frameworks.
• Demonstrated passion for mentoring engineers, fostering an…