AI Engineer

VueData is hiring a Senior AI Engineer to build production-ready agentic AI and LLM platform capabilities, with AWS Bedrock, RAG, guardrails, and MCP-based tool integration. Responsibilities Design, develop, and deploy agentic and multi-agent AI systems for production use cases Create agent workflows that include reasoning, planning, routing, delegation, tool execution , memory, state management, checkpointing, parallel execution, and human-in-the-loop patterns Work with frontier LLMs and make practical decisions across model selection, prompting, structured outputs, context management, latency, token usage, quality, and cost Build and integrate MCP servers , reusable tools , and function/tool-calling workflows connecting agents to APIs, databases, enterprise systems, and internal applications Orchestrate production-grade agent workflows and multi-agent systems Develop AI applications using AWS Bedrock , including foundation models, Knowledge Bases/RAG , Guardrails , and related services Build RAG and enterprise retrieval pipelines covering ingestion, embeddings, vector search, reranking, metadata filtering, and grounding Design multi-model architectures based on task complexity, quality, latency, and cost Implement LLM observability and evaluation , including tracing, tool execution monitoring, response quality, grounding, hallucination signals, latency, token consumption, and task completion Implement AI security patterns such as guardrails, prompt-injection defenses , tool permissioning, credential management, and safe agent execution Build reusable agent platforms and frameworks (beyond standalone chatbots) Use AI coding assistants and coding agents for development, debugging, testing, refactoring, and code analysis while maintaining ownership of code quality and architecture Partner with product and engineering teams to move AI use cases from POC to production Requirements Python skills with experience building production APIs and backend services Hands-on experience with Generative AI, LLMs, agentic architectures , and multi-agent orchestration Experience with frontier models such as OpenAI GPT , Anthropic Claude , Google Gemini , Meta Llama , or equivalent Hands-on experience with MCP , tool/function calling, structured outputs , and agent-to-tool integration Experience with AWS Bedrock and building AI/LLM applications on AWS Experience with one or more agentic AI frameworks: LangGraph , LangChain , LlamaIndex , CrewAI , AutoGen , or equivalent Strong understanding of RAG , embeddings, vector databases, semantic search, and reranking Experience with LLM observability, tracing, evaluation, and production monitoring using tools like Langsmith or equivalent Working knowledge of AWS services: Lambda , ECS/EKS , API Gateway , S3 , DynamoDB/RDS , OpenSearch , SQS/SNS , CloudWatch Comfortable with AI-assisted development using tools such as GitHub Copilot , Cursor , Claude Code , Codex , or similar coding agents What We Are Looking For Not a traditional data science or model-training role Comfort moving between an LLM, agent workflow, MCP tool , Python service , RAG pipeline , and AWS Bedrock , with understanding of how these pieces work together in a reliable production system AI-native approach to software development using AI coding tools extensively while retaining ownership of architecture, code quality, testing, security, and the final implementation Technologies Python; Generative AI; LLMs; agentic architectures; multi-agent orchestration Frontier LLMs: OpenAI GPT; Anthropic Claude; Google Gemini; Meta Llama MCP; tool/function calling; structured outputs AWS Bedrock; Knowledge Bases/RAG; Guardrails; RAG; embeddings; vector search; reranking; metadata filtering; grounding LLM observability: Langsmith AWS: Lambda; ECS/EKS; API Gateway; S3; DynamoDB/RDS; OpenSearch; SQS/SNS; CloudWatch Agentic frameworks: LangGraph; LangChain; LlamaIndex; CrewAI; AutoGen AI coding assistants and coding agents: GitHub Copilot; Cursor; Claude Code; Codex Location and Salary Location: Kirkland, WA (onsite) Salary: USD 80,000 - 110,000 per yearly Experience 5+ years overall software engineering experience, preferably across backend, cloud, or distributed applications 2+ years hands-on experience with Generative AI, LLM applications, and agentic AI frameworks Experience taking AI/LLM applications from prototype through production Benefits Health insurance Paid time off #J-18808-Ljbffr