AI and Automation Engineer

Summary

Braviant Holdings is a leading provider of tech-enabled consumer credit products, utilizing advanced technology and machine learning to enhance credit accessibility. The AI & Automation Engineer role focuses on designing, deploying, and managing AI-powered automation workflows to improve various business processes, including consumer lending and compliance.

Responsibilities

• Design and build AI agent workflows that automate or accelerate business processes across originations, credit risk, compliance, collections, and operations
• Migrate manual and semi-automated processes into governed, production-grade agent pipelines with appropriate human-in-the-loop checkpoints, approval gates, and escalation patterns
• Build with Strands Agents SDK as the preferred default framework; apply judgment to use CrewAI, LangGraph, AutoGen, LlamaIndex, Haystack, or other frameworks where better suited
• Implement structured outputs, function calling, and tool-use patterns to connect LLMs with internal business logic and data
• Manage, build, and maintain MCP (Model Context Protocol) servers and clients to give agents structured, governed access to internal APIs, databases, and third-party data providers
• Develop skills, plugins, and tool integrations for Claude and other AI platforms used across the organization
• Integrate AI capabilities with existing systems via REST APIs, event queues, and cloud-native AWS services
• Evaluate and implement lightweight automation connectors (n8n, Zapier, Make) for business stakeholder workflows where full agent development is not warranted
• Instrument every workflow you build with logging, tracing, and alerting so teams can audit agent behavior, debug failures, and measure outcomes
• Implement guardrails and usage controls across AI deployments, covering autonomous, semi-autonomous, ad hoc, scheduled, event-driven, manually triggered, and human-review-gated workflows
• Contribute to responsible AI documentation including runbooks, incident response playbooks, and acceptable use standards for AI-assisted processes in a regulated fintech environment, in partnership with the Technology Operations team
• Stay current on agentic AI developments, vulnerability patterns, and compliance requirements relevant to consumer lending
• Work directly with business stakeholders to translate process requirements into agentic workflow specs — you need to understand what the business does, not just what the framework supports
• Contribute to shared frameworks, reusable agent components, and internal engineering standards developed by the Head of AI & Automation
• Participate in design reviews, code reviews, and cross-team knowledge sharing

Skills

• 2 to 4 years of software engineering experience with production Python and SQL; additional languages a plus
• Hands-on experience building and shipping AI/ML or LLM-powered solutions in real production environments, not just coursework or personal projects
• Practical experience with at least one agentic or LLM orchestration framework (Strands, LangGraph, CrewAI, AutoGen, LlamaIndex, or similar)
• Experience integrating AI services via APIs and building tool-use or function-calling patterns with LLMs
• Familiarity with AWS and cloud-native architecture patterns
• Active daily use of AI-assisted development tools such as Claude Code, VS Code with Cline, Cursor, GitHub Copilot, or similar — this is table stakes, not a differentiator
• Experience with prompt engineering and structured outputs; comfort iterating on prompts as a core part of building
• Strong written communication — you can document a workflow clearly enough for a compliance reviewer, not just another engineer
• Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
• Direct experience with Amazon Bedrock, Bedrock AgentCore, or the Strands Agents SDK
• Experience building or consuming MCP servers and clients
• Familiarity with skills and plugin development for Claude, Microsoft Copilot, or similar AI platforms
• Experience with OpenClaw, Hermes Agent, HyperAgent, or similar open-source agent frameworks
• Familiarity with workflow automation platforms such as n8n, Zapier, Make, or similar
• Background in fintech, consumer lending, payments, or another regulated financial services environment
• Familiarity with RAG architectures, vector databases, or knowledge graph approaches
• Working knowledge of application security fundamentals: auth, secrets management, RBAC, and audit logging
• Familiarity with observability and evaluation practices for AI systems: logging, tracing, prompt evaluation, and model monitoring

Qualifications

Must Haves

• 2 to 4 years of software engineering experience with production Python and SQL; additional languages a plus
• Hands-on experience building and shipping AI/ML or LLM-powered solutions in real production environments, not just coursework or personal projects
• Practical experience with at least one agentic or LLM orchestration framework (Strands, LangGraph, CrewAI, AutoGen, LlamaIndex, or similar)
• Experience integrating AI services via APIs and building tool-use or function-calling patterns with LLMs
• Familiarity with AWS and cloud-native architecture patterns
• Active daily use of AI-assisted development tools such as Claude Code, VS Code with Cline, Cursor, GitHub Copilot, or similar — this is table stakes, not a differentiator
• Experience with prompt engineering and structured outputs; comfort iterating on prompts as a core part of building
• Strong written communication — you can document a workflow clearly enough for a compliance reviewer, not just another engineer
• Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience

Nice to Haves

• Direct experience with Amazon Bedrock, Bedrock AgentCore, or the Strands Agents SDK
• Experience building or consuming MCP servers and clients
• Familiarity with skills and plugin development for Claude, Microsoft Copilot, or similar AI platforms
• Experience with OpenClaw, Hermes Agent, HyperAgent, or similar open-source agent frameworks
• Familiarity with workflow automation platforms such as n8n, Zapier, Make, or similar
• Background in fintech, consumer lending, payments, or another regulated financial services environment
• Familiarity with RAG architectures, vector databases, or knowledge graph approaches
• Working knowledge of application security fundamentals: auth, secrets management, RBAC, and audit logging
• Familiarity with observability and evaluation practices for AI systems: logging, tracing, prompt evaluation, and model monitoring

Benefits

• Comprehensive healthcare including medical, dental, and vision coverage
• Generous paid time off, including PTO, sick time, and 13 company holidays
• 401(k) with company contribution
• Participation in annual discretionary bonus plan
• Regular team and company gatherings