Lead AI Engineer — Architect Cutting-Edge AI Solutions

Kainos; United States; Remote; USD 150,000 - 210,000; Full time

Job summary

Kainos is seeking a Lead AI Engineer to architect, design and deliver advanced AI solutions, leveraging state-of-the-art machine learning, generative and agentic AI technologies.

You will drive the adoption of modern AI frameworks, implement scalable cloud-native architectures on Azure and AWS, and provide hands-on technical leadership while mentoring junior engineers and collaborating with clients to translate business challenges into trustworthy AI outcomes.

Qualifications

• A 2.1 degree in Computer Science, AI, Data Science, Statistics or related field.
• Proven deployment of modern AI/ML solutions into production with prompt engineering, RAG, evaluation, and drift monitoring.
• Strong Python skills with software engineering best practices (CI/CD, testing, code reviews).
• Experience scaling AI solutions on cloud platforms (Azure & AWS) with Kubernetes and Docker.
• Expertise in AI data engineering handling large-scale, unstructured and multimodal data.
• Understanding of responsible AI, model interpretability and ethics.
• Strong client-facing skills and ability to gather requirements in non-technical language; mentoring juniors.

Responsibilities

• Architect, design and deliver advanced AI solutions leveraging state-of-the-art ML and generative AI.
• Lead technical delivery, drive adoption of modern AI frameworks, and mentor engineers.

Skills

Python

CI/CD

Software engineering practices

Technical leadership

Model evaluation & monitoring

Prompt engineering & RAG

Client collaboration

Education

Bachelor's degree in Computer Science/AI/Data Science/Statistics

Tools

Kubernetes

Docker

Azure

AWS

Job description

Kainos is seeking a Lead AI Engineer to architect, design and deliver advanced AI solutions, leveraging state-of-the-art machine learning, generative and agentic AI technologies.

You will drive the adoption of modern AI frameworks, implement scalable cloud-native architectures on Azure and AWS, and provide hands-on technical leadership while mentoring junior engineers and collaborating with clients to translate business challenges into trustworthy AI outcomes.