Applied LLM Engineer
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Key Responsibilities
• Production Deployment: Design and implement a production-ready LLM chatbot using AWS Bedrock.
• Pipeline Development: Develop a RAG pipeline to query pet biometric and behavioral data.
• App Integration: Implement contextual insights within the app interface and build an API layer for secure metric queries.
• Engineering Safety: Design structured prompting frameworks for health-safe responses, including guardrails, uncertainty handling, and escalation logic.
• Optimization: Optimize token usage and LLM cost efficiency.
• Reporting: Implement structured report generation for veterinary use.
• Strategy: Collaborate with the founding team on data strategy and the product roadmap. Qualifications
• Proven experience building production LLM applications and a strong understanding of RAG architecture.
• Proficiency with AWS, specifically Bedrock.
• Expertise in token optimization, inference cost modeling, and designing prompt systems with guardrails.
• Preferred: Familiarity with health-tech AI, regulated AI domains, and integrating AI into mobile or web platforms. Compensation & Benefits
• Equity: 0.5% – 2%, commensurate with experience and role scope.
• Flexibility: Remote position with the option to work as a side commitment or part-time until formal employment is established.
• Impact: Direct input into company direction and the opportunity to build products that make a real difference for pet owners in the APAC market. Culture & Work Arrangements We value innovation, work-life balance, and a genuine passion for animal welfare.
• Meetings: Weekly online meetings during weekday evenings.
• Events: Occasional in-person weekend events and business trips.
• Initiatives: Opportunities to participate in animal welfare initiatives and regular feedback sessions to shape our future.
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