The AI Solutions Engineer is responsible for designing, developing, and deploying AI-powered applications across the full technology stack, including front-end interfaces, back-end services, databases, and AI/ML models. This role combines software engineering and AI expertise, enabling the delivery of scalable, maintainable, and high-performing solutions that leverage advanced technologies to solve business problems. The AI Solutions Engineer collaborates with cross-functional teams to integrate machine learning models with user-facing applications, ensuring seamless performance and alignment with business objectives.
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.
Minimum Qualifications:
- 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.
The base pay for this position ranges from $90,000 - $115,000, which will vary depending on how well an applicant's skills and experience align with the job description listed above.
We will accept applications until 6/14/2025.
