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At a glance
Compensation
No compensation found
Location
Work From HomeRemote
Work Authorization
Not specified
Requirements
Credentials this posting asks for.
Bachelor's degree
Job overview
The Technical Leader will integrate Amazon Bedrock, develop context-aware prompts, manage model selection and cost, implement audit logging, and collaborate with cross‑functional teams to deploy and optimize AI/ML models, while staying current with research and mentoring junior engineers.
Skills & qualifications
RequiredNice to have
Skills
Deep LearningRecommender SystemsPythonNatural Language ProcessingInformation RetrievalMachine LearningResearchAmazon Web ServicesArtificial IntelligenceData EngineeringPrompt EngineeringLLM ConceptsRecommendation EnginesPredictive AIAWS Services
Qualifications
Bachelor's Degree in Computer Science or Engineering or Mathematics or Related Field6+ Years Experience Building AI Models With ML NLP and Deep LearningStrong Interest in AI and Strong Desire to Do AI Research
Full job description
Responsibilities:
- Bedrock Integration: Replace the currentclaude.aideep -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 and 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 centralised 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.
- Optimise 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.
Requirements:
- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or related fields.
- Ideally 6+ years of experience in building AI models with ML, NLP and deep learning.
- Strong interest in AI and strong desire to do AI research.
- Should have strong experience in Prompt Engineering.
- 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 .
- Good understanding of AWS services.
You've read the whole posting — now see how you match it.