At a glance
Automatically prepared from the listing. Check the original description for the full requirements.
Jump to the original descriptionResponsibilities
You will architect and maintain the AI/ML systems that drive real-time conversation, multi-dimensional profiling, and crisis detection. You will integrate and orchestrate LLMs and collaborate with the software engineering team to ship these capabilities as production-grade features.
Requirements
Must have hands-on experience building and deploying ML or LLM-powered systems in production and strong software engineering fundamentals. Familiarity with MLOps, AWS, and real-time streaming architectures is nice to have.
Working hours
40 hours per week
Work arrangement
Remote OK
Skills
- AI
- ML
- Software Engineering
- LLM Orchestration
- Prompt Engineering
- RAG
- Fine-Tuning
- TypeScript
- MLOps
- AWS
- Cloud-Based ML Infrastructure
- Real-Time Streaming
- Event-Driven Architectures
- Healthcare
- Mental Health Tech
- Psychological Frameworks
Remote locations (standardized)
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Healthcare
- Data & Analytics
- Software
Keywords
- AI
- ML
- LLM
- Software Engineering
- TypeScript
- MLOps
- AWS
- Cloud-Based ML
- Real-Time Streaming
- Event-Driven Architectures
- Mental Health
- Psychological Dimensions
- Profiling Engine
- Crisis Detection
- Prompt Engineering
- Fine-Tuning
Original job description
This isn't a typical AI/ML role
BRIIDGE is an AI-powered self-understanding platform. Users talk to Shirin, an AI companion grounded in 10 validated psychological dimensions - and every conversation builds a progressively accurate Living Profile. Mental health apps fail at 4% fifteen-day retention because they treat everysession as disposable. We are building the opposite of that.
We are a team of 5. You will own the AI layer: the LLM orchestration, the profiling engine, the signals that power Shirin's memory and reasoning. This is production AI handling sensitive psychological data - it demands rigor, not just experimentation.
What you'll work on
You will architect and maintain the AI/ML systems that drive real-time conversation, multi-dimensional profiling, and crisis detection. You will integrate and orchestrate LLMs, design evaluation frameworks to measure model quality over time, and collaborate with the software engineering team to ship these capabilities as production-grade features in a TypeScript monorepo.
Must have
Hands-on experience building and deploying ML or LLM-powered systems in production
Strong software engineering fundamentals - you write code that others can maintain
Experience with LLM orchestration, prompt engineering, RAG, or fine-tuning
Comfort working in TypeScript or strong willingness to adopt it as the primary language
Genuine interest in building responsibly in the mental health and self-understanding space
Nice to have
MLOps experience: model versioning, monitoring, evaluation pipelines
Familiarity with AWS and cloud-based ML infrastructure
Experience with real-time streaming and event-driven architectures
Background in healthcare, mental health tech, or therapy-adjacent products
Agentic development workflow experience (Claude Code, Cursor, or similar)
Knowledge of psychological frameworks or structured profiling methodologies
What makes this different
You are not joining a team running ML experiments that never reach users. We have a ratified architecture, deeply specified product requirements, and locked feature specs. You will understand why you are building what you are building. The product is real, the users are real, and the domain - human self-understanding - demands that the AI powering it be thoughtful, precise, and genuinely good.
