Software Engineer responsible for developing, implementing, and supporting application components for KeyBank. Collaborates with teams to ensure system availability and performance standards.
About the role
- Principal Engineering Lead driving Kantar’s AI technology transformation through scalable solutions. Collaborating with teams for AI projects while mentoring engineers to foster innovation.
Responsibilities
- Architecting and delivering scalable AI solutions
- Leading the technical direction of AI projects
- Mentoring engineers and fostering innovation within the team
- Collaborating with Data Science, Product Management, and wider technology groups to translate complex AI concepts into actionable business strategies
Requirements
- Proven experience in AI engineering, including building, deploying, and maintaining machine learning and generative AI solutions (e.g., LLMs, embeddings, RAG, vector search, model fine-tuning).
- Strong knowledge of MLOps practices for continuous integration, deployment, and monitoring of ML/AI models.
- Experience with AI-specific infrastructure, such as model orchestration pipelines, GPU-based compute, and AI model hosting services.
- Understanding of vector databases, semantic search, and scalable data structures for AI applications.
- Familiarity with AI governance, responsible AI principles, and model evaluation techniques.
- Deep expertise in Microsoft .NET Core, C#, and modern back-end technologies, with the ability to code across multiple languages such as Python, Go, or TypeScript.
- Strong understanding of microservices architecture, distributed systems, and cloud-native design patterns.
- Experience with SQL databases (e.g., Microsoft SQL Server, PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB, CosmosDB).
- Proficiency in synchronous and asynchronous APIs, messaging frameworks, and event-driven systems.
- Secure coding practices with a strong grasp of cybersecurity threats, especially in the context of AI and data privacy.
- Experience deploying large-scale AI and software solutions on Azure, AWS, or Google Cloud.
- Familiarity with containerization and orchestration (Docker, Kubernetes).
- Knowledge of cloud-native data pipelines and serverless computing environments.
- 2–4 years in a principal engineer, technical lead, or software architect role, demonstrating strong technical leadership in both AI and software engineering.
- Experience mentoring teams and fostering a culture of continuous learning and technical excellence.
- Ability to translate complex AI concepts into actionable strategies for technical and business stakeholders.
- Strong communication skills with proven success collaborating across diverse teams, including Data Science and Product Management.
- Experience with UI development technologies such as Angular, TypeScript, JavaScript, HTML5, and modern frameworks to build AI-driven user interfaces.
Benefits
- Flexible working hours
- Professional development opportunities
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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