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Brightside Health is seeking a Principal Architect (AI) to own the design and build of the company's AI agent platform. This is a senior, hands-on role working directly with the engineering team to architect and ship production systems. The core system you will build is a real-time agent layer that listens to live conversations between Financial Assistants and clients, understands what is happening turn by turn, surfaces intelligent coaching to the FA in under 2 seconds, and writes structured data back to the CRM. As the platform matures, this same agent layer will conduct client conversations autonomously.
This is explicitly NOT a governance, advisory, research, or people-management role—it is an execution-oriented architecture role where you design and help build.
Key Responsibilities:
Real-Time Agent Architecture: Design and own the multi-agent orchestration layer including session supervisor, domain clusters, escalation arbiter, and conversation manager. Define agent routing logic, context sharing, tool use, and latency budgets across 18+ agents. Architect the real-time pipeline: Amazon Connect → Contact Lens → Kinesis → Lambda → Bedrock → WebSocket push to FA panel. Own the dual-mode agent architecture: human-assisted mode (agent coaches the FA) and autonomous mode (agent conducts the client conversation directly).
LLM Systems & Prompt Engineering Governance: Define model selection and routing across low-latency and reasoning-intensive agent tiers. Govern the prompt architecture with structured agent prompt standards, runtime domain knowledge injection, and conditional output formatting. Build and own the eval harness for schema validation, behavioral regression testing, and latency profiling. Design the domain knowledge base structure across the full financial use case library (8 domains, 49 use case types).
Data Architecture & CRM Integration: Own the data model underlying the AI platform including client financial profiles, cases, goals, options, outcomes, and financial impact measurement. Architect the CRM sync layer for real-time field writes after FA confirmation and human correction logging as training signal. Define canonical data models across clients, employers, financial products, and outcomes. Ensure data integrity across Aurora PostgreSQL (new CRM) and Aurora MySQL (existing platform).
AI Infrastructure & Platform: Own the AWS Bedrock-native inference infrastructure including async invocations, Knowledge Bases, and RAG pipelines. Design the session state layer using ElastiCache Redis for hot state and DynamoDB for durable session records. Define AI governance standards for model evaluation, monitoring, explainability, and compliance in a regulated fintech environment. Evaluate and guide decisions on model providers, orchestration frameworks, and platform tooling.
Brightside's mission is to improve the financial health of working families through an employee benefit offering unique solutions for personal finance, combining products, technology, and human care.
REQUIREMENTS:
Required:
- 10+ years in software engineering or systems architecture, with significant hands-on experience in the last 3 years
- Production experience building real-time AI systems, specifically systems that operate on a per-turn, sub-second latency budget
- Hands-on experience with Amazon Bedrock, AWS Lambda, and Kinesis (not just familiarity, but have hit their limits and worked around them)
- Multi-agent system design experience including orchestration patterns, agent handoff, context sharing, and structured output validation
- Strong data architecture foundation in relational modeling, event-driven systems, and CRM data patterns
- Experience in a regulated environment (fintech, financial services, or healthcare) with understanding of privacy and compliance requirements
- Comfortable operating in a small, fast-moving team where you design and build, not just review and approve
Strong Advantage:
- Experience building voice or conversation intelligence systems (contact center AI, real-time transcription pipelines, live agent coaching tools)
- Hands-on experience with Amazon Connect and Contact Lens
- Background in conversational AI product companies (Cresta, Observe.AI, Cogito, Replicant, or similar)
- Experience with LLM prompt engineering at a systems level including eval harnesses, versioned prompt governance, and regression testing
- Prior experience as a lead architect at a Series B-D company where you were one of a small number of senior technical voices
