Bread Financial

Full-stack Engineer

• Design and enhance multi-agent frameworks and LLM-powered autonomous systems using goal schemas, planner-executor patterns, and well-defined policy enforcement points
• Contribute to the definition and implementation of agent state and memory architectures (short-/long-term, episodic, semantic) with strong PII-minimization practices and appropriate TTL strategies
• Implement and refine ReAct, CoT, and ToT reasoning loops, and help standardize their use across agent workflows
• Build offline and online evaluation signals using curated golden datasets
• Contribute to defining and implementing agent-to-agent communication protocols using frameworks like LangGraph, AutoGen, or CrewAI
• Measure and improve agent decision reliability using tools such as LangSmith, Arize Phoenix, and Weights & Biases
• Design deterministic tool-chaining patterns with appropriate fallbacks, and implement safeguards including idempotency, retries, and circuit-breaker logic
• Contribute to integrating grounding techniques to ensure accurate and reliable agent behavior
• Architect and implement safety controls such as scoped tool access, allow/deny actions, validators, red-team hooks, and human-escalation paths
• Use AgentSpec to define and apply Policy Enforcement Points (PEPs) that prevent high-risk or irreversible agent actions
• Operate and scale production agentic AI platforms on Kubernetes by defining agent-centric SLOs, instrumenting deep telemetry (reasoning quality, hallucination rates, tool latency), and supporting on-call through agent-assisted triage, automated rollback/roll-forward, and human-gated controls
• Establish enterprise safety guardrails, ethical guidelines, and compliance standards to ensure agents operate within legal, regulatory, and organizational boundaries, especially in high-risk or financial workflows
• Partner with Product to shape AI strategy and agent user experiences, and collaborate with data and backend teams to ensure agents access high-quality, real-time data across SQL systems, CRMs, SaaS platforms, APIs, and event streams within existing architectures
• Communicate complex agentic concepts—such as CoT, RAG, and safety controls—to non-technical stakeholders to build trust and organizational readiness
• Model resilience around model failures and promote AI-native engineering practices, including prompt design and evaluation techniques, across teams

Senior Staff Software Engineer – Agentic AI

QA Automation Engineer

• Collaborate on the design and implementation of quality engineering practices for financial technology solutions
• Maintain test frameworks to ensure efficient testing across the enterprise
• Work on improving automation frameworks for scalable test automation
• Help define and advocate for testing standards, automation strategies, and best practices in the SDLC
• Support efforts to address performance bottlenecks and quality gaps
• Contribute to the development of tools for managing test data across environments
• Integrate testing tools and frameworks into the CI/CD pipeline
• Develop and maintain automated test environments and data solutions
• Collaborate with quality engineering, product, and business teams on best practices in test-driven development (TDD) and automation

Senior Staff Software Engineer – Agentic AI

Platform Automation Engineer