Ai Solutions Engineer

Summary

Join KnowBe4 as an AI Solutions Engineer and design, develop, and deploy AI-powered applications across the full technology stack. You will integrate machine learning models with user-facing applications, ensuring seamless performance. This role combines software engineering and AI expertise, requiring collaboration with cross-functional teams. You will build LLM agents and toolsets, optimize RAG systems, and develop microservices for audio processing. The position offers a competitive salary and a range of benefits, including company-wide bonuses, referral bonuses, adoption assistance, tuition and certification reimbursements, and a relaxed work environment.

Requirements

• Bachelor’s or master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field
• Equivalent work experience in full-stack development and AI/ML technologies may substitute for formal education
• Front-End Development: Proficiency in HTML, CSS, JavaScript, and frameworks like React, Angular, or Vue.js
• Back-End Development: Experience with server-side languages such as Python, Node.js, or Golang
• Database Management: Knowledge of SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, DynamoDB) databases
• AI/ML Expertise: Experience developing, training, and deploying models using TensorFlow, PyTorch, or Scikit-Learn
• Data Engineering: Familiarity with ETL pipelines and data manipulation tools
• Cloud Platforms: Strong knowledge of AWS services, including Bedrock, ECS, Lambda, Kinesis, API Gateway, EventBridge, RDS, DynamoDB, and S3
• Version Control: Proficiency with Git for collaborative development
• Communication and Collaboration: Strong ability to communicate solutions effectively to technical and non-technical stakeholders
• Troubleshooting and Debugging: Ability to identify and resolve production issues quickly
• Agent Workflow/Toolset Design: Experience implementing LLM agents with custom tools
• Agent Guardrails/Validation: Ability to identify edge cases where LLMs struggle and set up automated systems for catching hallucinations/unexpected behavior
• RAG/Search: Strong understanding of best practices for designing/testing search systems for LLM context
• Audio Processing: Experience converting, denoising, and transcribing audio files
• Code/Bug Fix Automation: Experience working with LLM agents to accelerate/automate parts of the development process

Responsibilities

• Develop AI-powered applications by integrating front-end, back-end, and machine learning components
• Design and implement AI/ML models and APIs to meet business and technical requirements
• Build and maintain data pipelines for training, deploying, and monitoring models
• Create front-end interfaces using modern frameworks (e.g., React, Angular, or Vue.js) to provide users with a seamless experience
• Develop and manage back-end services and APIs using Python, Node.js, or Java to support AI solutions
• Implement and optimize SQL and NoSQL databases for storing model data and application states
• Deploy applications and AI models to cloud platforms (e.g., AWS) with CI/CD pipelines for automated builds and releases
• Collaborate with data scientists, product managers, and DevOps teams to ensure alignment between business needs and technical solutions
• Participate in code reviews and technical design discussions to ensure best practices are followed
• Build LLM agents and toolsets to streamline/automate business needs
• Identify edge cases where LLMs struggle and set up automated systems for catching hallucinations/unexpected behavior
• Design, optimize, and test RAG systems for LLM search using embeddings and custom search techniques
• Build microservices for converting, denoising, and transcribing audio files

Benefits

• Company-wide bonuses based on monthly sales targets
• Employee referral bonuses
• Adoption assistance
• Tuition reimbursement
• Certification reimbursement
• Certification completion bonuses
• Relaxed dress code