We are looking for a Principal AI Architect to own the design and build of Brightside ’s AI agent platform. This is a senior, hands on role. You will work directly alongside Jacky Chiu and the engineering team to architect and ship production systems, not design from a distance. The core system you will build is a realtime 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.
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Design and own the multi-agent orchestration layer - 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: structured agent prompt standards, runtime domain knowledge injection, and conditional output formatting across delivery surfaces Build and own the eval harness - schema validation, behavioral regression testing, 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: client financial profiles, cases, goals, options, outcomes, and financial impact measurement Architect the CRM sync layer - real-time field writes after FA confirmation, 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 - async invocations, Knowledge Bases, RAG pipelines Design the session state layer: ElastiCache Redis for hot state, DynamoDB for durable session records Define AI governance standards: model evaluation, monitoring, explainability, and compliance in a regulated fintech environment Evaluate and guide decisions on model providers, orchestration frameworks, and platform tooling What We’re Looking For 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 - orchestration patterns, agent handoff, context sharing, structured output validation Strong data architecture foundation - relational modeling, event-driven systems, CRM data patterns Experience in a regulated environment (fintech, financial services, or healthcare) with an understanding of privacy and compliance requirements Comfortable operating in a small, fast-moving team where you design and build - not just review and approve
Experience building voice or conversation intelligence systems (contact center AI, real-time transcription pipelines, live agent coaching tools)