AI Lead Engineer (Prompt Engineering, RAG and LLM's)

• Good understanding of AWS services.

• Bedrock Integration: Replace the current claude.ai deep-link (cosmetic "Ask AI" button) with a real Amazon Bedrock (Claude) integration for both Canopy and Trellis

• Context Injection: Build context-aware prompts that pull in real portfolio data, rather than the current no-context implementation

• Prompt Engineering: Design and maintain AI prompt templates (per-app, built twice) and expand the prompt library during Phase 2 feature refinement

• Model Selection & Inference-Cost Management: Implement configuration-driven model selection — routing routine work to smaller/cheaper models and complex analysis to frontier models — as the primary cost lever for Bedrock spend

• Audit Logging: Enable and route prompt/response audit logging to centralized logging and satisfy the audit-trail requirement

• Collaborate with product managers, data scientists, and software engineers to identify AI/ML opportunities and develop innovative solutions.

• Implement and deploy AI/ML algorithms and models into production environments.

• Optimize and fine-tune AI/ML models to improve accuracy and efficiency.

• Conduct experiments, perform data analysis, and present findings to stakeholders.

• Develop and maintain documentation for AI/ML algorithms, models, and solutions.

• Stay up-to-date with the latest AI/ML research and technologies and apply them to improve our platform.

• Mentor and provide technical guidance to junior AI/ML engineers or team members.

• Bachelors or Masters degree in Computer Science, Engineering, Mathematics, or related fields.

• ideally 5+ years of experience in building AI models with ML, NLP and deep learning.

• Strong experience in Prompt Engineering

• Strong interest in AI and strong desire to do AI research.

• Python and Python ecosystem for AI/ML development

• Familiarity with LLM concepts, information retrieval, recommendation engines and predictive AI

• Data engineering skills. Ability to help write scripts to move data, clean data, and shape data for usage with LLMs.

• Familiarity with tooling and APIs using inference engines hosted elsewhere, e.g. on openai.com

Additional Experience Desired:

• Good Software Engineering Background.

• Experience in working with huge datasets in a production environment is a plus

• Strong analytical and problem-solving skills, with attention to detail.

• Excellent communication skills, with the ability to present complex technical concepts to both technical and non-technical audiences.

• Familiarity with Python libraries such as PyTorch, TensorFlow, and Scikit-Learn.

• Proven ability to work independently and with a team.