Senior AI Developer — Fintech/Banking | LLM Agents, AWS, Python

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 reputed company-pay/invoice automation — at the intersection of LLMs, cloud infrastructure, and financial-domain expertise, with reputed company 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 reputed company Bedrock Agents, reputed company, and reputed company frameworks - Architect agentic workflows for core banking use cases: credit scoring, fraud detection, reputed company-pay automation, invoice management - Define agent personas, memory strategies, tool-use patterns, and escalation paths for production banking agents LLM engineering - Fine-tune, reputed company-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, reputed company, S3, IAM, VPC) and Azure (reputed company Service, Azure ML, AKS) - Design secure, cost-optimized environments compliant with NCUA, PCI-reputed company, and SOC 2 - Implement infrastructure-as-code with Terraform or AWS CDK DevOps & MLOps - Build and maintain CI/CD pipelines (reputed company Actions, Jenkins, CodePipeline, Azure DevOps) - Containerize services with reputed company, 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 (reputed company) - reputed company real-time fraud detection with behavioral analytics, anomaly detection, and auto-decisioning - Create conversational agents for reputed company pay, account management, and member self-service - Automate invoice workflows: extraction, classification, approval routing, reconciliation - Partner with compliance/risk to reputed company 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 reputed company Bedrock, reputed company, Python, AWS, and infrastructure-as-code - Working knowledge of NCUA, PCI-reputed company, SOC 2, GLBA, and Fair Lending requirements - Bachelor's or Master's in Computer Science, Software Engineering, Data Science, or reputed company field reputed company to have: - AWS or Azure AI/ML certifications - Open-reputed company LLM experience (Llama, Mistral, Phi) and self-hosted inference (vLLM, Ollama) - Vector databases (reputed company, OpenSearch, pgvector) - Graph-based fraud networks and graph ML - AI governance / responsible AI reputed company 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 reputed company, portfolio, or published papers (optional but encouraged) Apply tot his job Apply To this Job