A bit about this role:
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 and you will work directly alongside the CTO and engineering team to architect and ship production systems, not design from a distance. The core system you will build: 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.
What this role isn't... A governance role. An advisory role. A research role. Or a people-management role. It is an execution-oriented architecture role. You will design it and help build it.
The meaningful work you will tackle:
Real-Time Agent Architecture
- 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
Engineering Partnership
- Serve as the CTO’s right-hand technical partner on all AI and platform architecture decisions
- Work alongside the Engineering Lead and team as a co-owner of the architecture - present in design, implementation, and debugging
- Translate business requirements from Client Services and Product into architecture-aligned technical scope
- Lead prototyping and technical discovery to test assumptions and reduce uncertainty before committing investment
Executive & Cross-Functional Partnership
- Partner closely with the CTO, Product leaders, Analytics, and Engineering to:
- Translate business strategy into technical direction
- Align data, AI, and platform investments
- Serve as a trusted technical advisor to executive leadership on data, AI, and platform tradeoffs
How You’ll Work
- Hands-on and opinionated - you form views, explain them clearly, and update them when wrong
- Oriented toward production outcomes, not theoretical elegance
- Comfortable saying no to poor architectural decisions and explaining why
- Willing to be in the weeds - debugging a Bedrock invocation, profiling a latency spike, reviewing a schema change
- Balancing experimentation with rigor in a regulated fintech environment
What we’re looking for in your background & what makes you a success:
- 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
What gives you a 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 - eval harnesses, versioned prompt governance, 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