AI Engineer (P840)

About Us:

As a Senior AI Engineer at Kenility, you’ll join a tight-knit family of creative developers, engineers, and designers who strive to develop and deliver the highest quality products into the market.

Technical Requirements:

• Bachelor’s degree in Computer Science, Software Engineering, or a related field.
• Over a decade of experience in full-stack development, with a strong focus on building large-scale products.
• In-depth proficiency in backend programming languages such as Python, Java, or C#.
• Demonstrated experience integrating AI functionalities into SaaS platforms.
• Strong understanding of vector databases like Pinecone or Weaviate, hybrid search mechanisms, and Retrieval-Augmented Generation (RAG) pipelines.
• Skilled in creating effective prompt templates and developing semantic agents.
• Knowledge of Langchain frameworks and best practices in MLOps.
• Familiarity with monitoring and debugging tools such as DataDog and LangSmith is advantageous.
• Keen interest in staying current with AI innovations and leveraging them creatively in applied settings.
• Exposure to high-security, regulatory, or GovTech environments is a plus.
• Understanding of automation workflows in legal or court-related platforms is valued.
• Background in document pipeline development, including parsing, chunking, and vectorization.
• Experience in MLOps practices such as CI/CD pipelines, model monitoring, and retraining.
• Familiar with deploying scalable AI solutions on cloud platforms such as AWS, GCP, or Azure.
• Product-oriented mindset and collaborative approach with design and product teams.
• Minimum Upper Intermediate English (B2) or Proficient (C1).

Tasks and Responsibilities:

• Develop and implement AI features such as RAG systems, semantic search components, and agentic architectures within SaaS products.
• Deploy and manage large and small language models in live production environments.
• Work closely with engineering and architecture teams to build and expose microservices via APIs.
• Design and manage schemas for vector storage, embedding workflows, and prompt engineering strategies.
• Guarantee the scalability, security, and performance of AI-powered services in line with enterprise standards.
• Support agile development practices through thorough documentation and effective communication.

Soft Skills:

• Responsibility
• Proactivity
• Flexibility
• Great communication skills