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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and building real-time AI systems, with a strong focus on multi-agent orchestration, data architecture, and compliance in regulated environments. Proficient in leveraging AWS technologies and conversational AI frameworks to deliver production-ready solutions.
Highest-signal resume keywords
Real-Time AI Systems DevelopmentMulti-Agent System DesignAWS Bedrock and Lambda ExperienceData Architecture and Relational ModelingConversational AI Product Background
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Multi-Agent OrchestrationReal-Time Pipeline ArchitecturePrompt EngineeringBehavioral Regression TestingData Integrity ManagementRelational ModelingEvent-Driven SystemsSchema ValidationLatency ProfilingFinancial Impact Measurement
Soft Skills
Technical Opinion FormationCollaboration in Fast-Moving TeamsComfort with Experimentation and Rigor
Tools & Technologies
Amazon ConnectContact LensKinesisAWS LambdaAurora PostgreSQLAurora MySQLElastiCache RedisDynamoDBWebSocketKnowledge Bases
Industry Keywords
FintechFinancial ServicesHealthcarePrivacy ComplianceConversational Intelligence
Tech Stack
Tools & technologiesAWSDynamoDBMySQLPostgresRedis
About the role
Key responsibilities & impact- Own the design and build of Brightside’s AI agent platform
- 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 from Amazon Connect through Contact Lens, Kinesis, Lambda, Bedrock, and WebSocket push to the Financial Assistant panel
- Own dual-mode agent architecture for human-assisted coaching and autonomous client conversations
- Define model selection and routing across low-latency and reasoning-intensive agent tiers
- Govern prompt architecture, including structured agent prompt standards, runtime domain knowledge injection, and conditional output formatting
- Build and own the evaluation harness for schema validation, behavioral regression testing, and latency profiling
- Design the domain knowledge base across 8 domains and 49 use case types
- Own the AI platform data model for client financial profiles, cases, goals, options, outcomes, and financial impact measurement
- Architect the CRM synchronization layer, including real-time field writes after Financial Assistant confirmation and human correction logging
- Define canonical data models across clients, employers, financial products, and outcomes
- Ensure data integrity across Aurora PostgreSQL and Aurora MySQL
- Own AWS Bedrock-native inference infrastructure, including asynchronous invocations, Knowledge Bases, and RAG pipelines
- Design the session state layer using ElastiCache Redis and DynamoDB
- Define AI governance standards for model evaluation, monitoring, explainability, and compliance
- Evaluate and guide decisions on model providers, orchestration frameworks, and platform tooling
- Work directly alongside Jacky Chiu and the engineering team to architect and ship production systems
- Debug Bedrock invocations, profile latency spikes, and review schema changes
Requirements
What you’ll need- 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 operating on a per-turn, sub-second latency budget
- Hands-on experience with Amazon Bedrock, AWS Lambda, and Kinesis
- Multi-agent system design experience, including orchestration patterns, agent handoff, context sharing, and structured output validation
- Strong data architecture foundation, including relational modeling, event-driven systems, and CRM data patterns
- Experience in a regulated environment such as 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
- Experience building voice or conversation intelligence systems
- Hands-on experience with Amazon Connect and Contact Lens
- Background in conversational AI product companies such as 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
- Comfortable forming, explaining, and updating technical opinions
- Oriented toward production outcomes
- Comfortable debugging Bedrock invocations, profiling latency spikes, and reviewing schema changes
- Able to balance experimentation with rigor in a regulated fintech environment
Benefits
Comp & perks- Inspiring careers
- Great life/work balance
- Meaningful work with direct impact on working families
- Opportunity to see a growing start-up from the inside out