Responsibilities
- Create autonomous AI agents that address practical business needs, including request processing, natural language querying, data exploration tools, and intelligent search features
- Incorporate large language models into software applications following proven methods such as prompt optimization, tool integration, multi-turn dialogue handling, response validation, and cost efficiency
- Construct semantic data models and schemas that support natural language interaction with enterprise datasets, including platforms like Snowflake Cortex Analyst and custom retrieval-augmented generation systems
- Link AI components to data infrastructure by designing end-to-end data pathways from source systems through transformation layers to semantic models and AI applications, ensuring data accuracy, traceability, and timeliness
- Build complete AI-powered applications using Next.js for interactive frontends with real-time chat interfaces, FastAPI and Python for backend logic, and server-side connections to LLMs and data platforms
- Establish monitoring and assessment frameworks for AI behavior, including structured logs, conversation tracking, benchmark evaluations, and adversarial testing to verify agent reliability
- Utilize modern deployment strategies such as containerized on-demand environments, Snowflake's Secure Data Sharing, automated CI/CD pipelines, and infrastructure defined through code
- Produce robust, production-ready code in Python and TypeScript with strong typing, modular design, comprehensive testing, and clear architectural separation
- Leverage AI tools for software development tasks, including using AI assistants like Claude for generating code, designing system architecture, and reviewing code to improve speed and maintain quality
- Advocate for and refine best practices in AI engineering, including improvements to prompting techniques, evaluation frameworks, data modeling, and system resilience
- Demonstrate strong analytical abilities and adaptability in a fast-changing domain; show curiosity, a willingness to experiment, and comfort navigating uncertainty
- Communicate clearly and work effectively across teams, collaborating with data engineers, product managers, and business stakeholders to turn requirements into functional AI capabilities
- Take initiative in learning and research; actively stay informed about advancements in large language models, prompting strategies, and agent-based systems
Compensation
Competitive salary and benefits package
Work Arrangement
Hybrid or remote options available
Team
Cross-functional team working on AI product development and integration
Requirements
- Bachelor’s or advanced degree in Computer Science, Engineering, or related field
- Proven experience building and deploying AI/ML systems in production environments
- Strong proficiency in Python and TypeScript with experience in full-stack development
- Hands-on experience with LLMs, prompt engineering, and retrieval-augmented generation (RAG)
- Familiarity with data platforms such as Snowflake and modern data stack tools
- Experience with AI orchestration frameworks and agent-based architectures
- Knowledge of CI/CD, containerization (e.g., Docker), and infrastructure-as-code (e.g., Terraform)
- Understanding of data modeling, schema design, and semantic layer development
- Track record of using AI tools to enhance development workflows
- Ability to work independently and drive projects from concept to deployment
Available for qualified candidates
