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AI Engineer at Blossom. Location Information: . Join Blossom!. We are a U.S.-based company with over 20 years of experience dedicated to enhancing the satisfaction of credit unions and their members. We are building the next-generation technology layer for credit unions. . www.blossom.net. We're looking for a curious and detail-oriented AI Engineer who is eager to grow in the fintech space. If you have hands-on experience building production AI systems and want to own real intelligent products from day one with mentorship and a team that will help you level up this role is for you.. About the Role. We're looking for an AI Engineer who thrives at the intersection of applied machine learning and production software engineering. You will design, build, and operate intelligent systems powered by large language models from agentic workflows and RAG pipelines to multi-step LangGraph agents deployed reliably on AWS.. This is a hands-on engineering role. You will own features end-to-end: collaborating with product and data teams to define requirements, implementing solutions with clean Python, and shipping them to production. You care about observability, cost efficiency, and measurable agent quality not just getting demos to work.. What You'll Do. Design and build production LLM-powered features, including multi-step agentic workflows, RAG pipelines, and tool-augmented assistants.. Develop and maintain LangGraph agents with well-defined state management, checkpointing, and human-in-the-loop patterns.. Integrate AWS Bedrock to invoke foundation models (Claude and others), configure Guardrails, and leverage Knowledge Bases and Agents.. Architect and operate AI workloads on AWS across Lambda, ECS/Fargate, S3, DynamoDB/RDS, and CloudWatch.. Set up and manage MCP (Model Context Protocol) servers and clients to extend agent capabilities with external tools and data sources.. Own prompt engineering and evaluation: define metrics, run experiments in Braintrust, LangSmith, or Promptfoo, and iterate systematically.. Build and maintain RAG architectures: manage embeddings, vector databases (OpenSearch, pgvector, Pinecone), and chunking strategies.. Maintain high engineering standards: write typed, tested Python; enforce CI/CD pipelines; manage infrastructure with CDK, Terraform, or CloudFormation.. Work with Claude Code and comparable agentic coding tools to accelerate development — authoring CLAUDE.md files, custom slash commands, and team workflow integrations.. Monitor cost, latency, and reliability of LLM workloads; propose and implement optimizations.. Minimum Requirements. 3+ years of professional software engineering experience, with at least 1 year focused on building and operating production AI/LLM applications.. Hands-on experience with Claude Code or comparable agentic coding tools: writing CLAUDE.md files, building custom slash commands, configuring MCP servers, and integrating them into team workflows.. Practical experience invoking foundation models via the Bedrock Runtime API, working with Claude models on Bedrock, and understanding Bedrock Guardrails, Knowledge Bases, or Agents.. Solid working knowledge of IAM, Lambda, ECS/Fargate, S3, DynamoDB or RDS, CloudWatch, and VPC networking. Comfortable deploying and operating services in production.. Production experience designing stateful multi-step agents: building graph workflows with nodes and edges, managing state and checkpointing, and handling tool calls and human-in-the-loop patterns.. Engineering Skills. Strong Python skills (typing, async, testing). TypeScript/Node.js is a plus.. Experience with prompt engineering and evaluation frameworks (Braintrust, LangSmith, Promptfoo), iterating on agent behavior with measurable metrics.. Understanding of RAG architectures, embeddings, vector databases (OpenSearch, pgvector, Pinecone), and chunking strategies.. Comfortable with API design, observability, and cost/latency optimization for LLM workloads.. Git, CI/CD, and Infrastructure as Code (CDK, Terraform, or CloudFormation).. Nice to Have. Experience building or integrating MCP (Model Context Protocol) servers and clients.. Fintech or regulated-industry experience (compliance, audit trails, data residency).. Multi-tenant SaaS architecture design and implementation.. Experience fine-tuning or distilling language models.. Perks. 100% Remote Work. Mentorship from experienced product and banking professionals. Multicultural collaboration with teams in Colombia and the U.S.. Real exposure to the American financial market. Growth path into senior product or leadership roles as the product scales. Apply Now!