We're hiring a senior AI developer to build and deploy AI solutions for a fintech/credit-union platform. The work spans autonomous banking agents, fraud detection, credit scoring, and bill-pay/invoice automation — at the intersection of LLMs, cloud infrastructure, and financial-domain expertise, with security and compliance built in from the start.
This is a long-term, ongoing engagement.
What you'll do:
AI agents & orchestration
- Design, build, and deploy multi-agent systems using Amazon Bedrock Agents, LangChain, and related frameworks
- Architect agentic workflows for core banking use cases: credit scoring, fraud detection, bill-pay automation, invoice management
- Define agent personas, memory strategies, tool-use patterns, and escalation paths for production banking agents
LLM engineering
- Fine-tune, prompt-engineer, and evaluate LLMs for financial-domain tasks
- Build RAG pipelines over credit-union knowledge bases, policy docs, and member data
- Implement guardrails, content filtering, and compliance checks for safe, regulated outputs
- Monitor performance, hallucination rates, and latency against SLAs
Cloud infrastructure (AWS & Azure)
- Architect and manage AI/ML workloads on AWS (Bedrock, SageMaker, Lambda, S3, IAM, VPC) and Azure (OpenAI Service, Azure ML, AKS)
- Design secure, cost-optimized environments compliant with NCUA, PCI-DSS, and SOC 2
- Implement infrastructure-as-code with Terraform or AWS CDK
DevOps & MLOps
- Build and maintain CI/CD pipelines (GitHub Actions, Jenkins, CodePipeline, Azure DevOps)
- Containerize services with Docker, orchestrate with Kubernetes (EKS/AKS)
- Apply MLOps best practices: model versioning, A/B testing, canary deployments, automated rollback
- Stand up observability with logging, tracing, and alerting
Python development
- Write clean, well-tested Python for AI pipelines, REST APIs, and data workflows
- Build FastAPI/Flask microservices exposing agent capabilities to frontend and core banking systems
- Integrate with financial data sources, core banking APIs, and third-party fintech services
Banking applications
- Build credit-scoring models using alternative data and explainable AI (XAI)
- Develop real-time fraud detection with behavioral analytics, anomaly detection, and auto-decisioning
- Create conversational agents for bill pay, account management, and member self-service
- Automate invoice workflows: extraction, classification, approval routing, reconciliation
- Partner with compliance/risk to keep AI decisions auditable, fair, and regulatory-compliant
What you should have:
- 5+ years software engineering; 3+ years in AI/ML or LLM engineering
- 2+ years building AI for banking, credit unions, or financial services
- Hands-on experience with Amazon Bedrock, LangChain, Python, AWS, and infrastructure-as-code
- Working knowledge of NCUA, PCI-DSS, SOC 2, GLBA, and Fair Lending requirements
- Bachelor's or Master's in Computer Science, Software Engineering, Data Science, or related field
Nice to have:
- AWS or Azure AI/ML certifications
- Open-source LLM experience (Llama, Mistral, Phi) and self-hosted inference (vLLM, Ollama)
- Vector databases (Pinecone, OpenSearch, pgvector)
- Graph-based fraud networks and graph ML
- AI governance / responsible AI framework experience
- Prior work at a credit union, community bank, or fintech lending platform
To apply, please share:
- Your resume highlighting AI and banking project experience
- A brief note on your most impactful AI agent or LLM project in a financial-services context
- Links to GitHub, portfolio, or published papers (optional but encouraged)