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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Platform Engineer - **Company:** Blue Ribbon Global Technologies - **Location:** St. Louis, MO, United States - **Experience:** Expert - **Contract:** Temporary to permanent - **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, Architectural Patterns, Automation of Tests, Code Review, Continuous Integration, Python (Programming Language), Microsoft Software, Search Technologies, Secure Coding, Software Engineering, Systems Integration, Enterprise Software Applications, Microsoft Power Automate, Large Language Models, Grafana, Multi-Agent Systems, Prompt Engineering, Git, AI Platforms, Machine Learning Operations, Restful APIs, Terraform, Automation Anywhere, Databricks - **Published:** August 27, 2026 - **Apply:** https://www.careerjet.com/jobad/us4c1115a6b4c3f05970eb7889aa191123 ## About the Role 5+ years of software engineering experience. Proven track record of delivering enterprise-grade production software. Strong Python development skills. Experience building, deploying, and operating production AI systems. Experience designing and implementing RAG solutions. Experience with Databricks. Hands-on experience with LangGraph or similar agent orchestration frameworks. Experience building AI workflows that leverage tools, APIs, and external systems. Experience with AI evaluation frameworks and quality measurement. Experience implementing AI observability and tracing solutions. Understanding of agent architecture patterns, prompt engineering, and LLM evaluation techniques. Experience with AWS in production environments. Experience designing and consuming REST APIs. Experience with Git, CI/CD, and modern software engineering practices. Knowledge of secure coding principles and responsible AI practices. Experience collaborating within Agile software development teams Nice to Have Experience with AgentBricks. Experience with Microsoft Copilot extensibility and agent development. Experience with LangChain and related frameworks. Experience with MCP integrations. Experience with vector databases and semantic search. Experience with AWS Bedrock. Experience with OpenTelemetry, LangSmith, Grafana, MLflow, DeepEval, or similar tooling. Experience deploying multi-agent systems. Experience with Terraform. AWS, Databricks, Microsoft, or AI-related certifications. Mindset Delivers AI solutions that create measurable business value. Treats evaluation and observability as first-class engineering disciplines. Balances innovation with reliability, scalability, and governance. Takes ownership of production systems and outcomes. Thinks holistically about data, architecture, monitoring, and continuous improvement. Collaborates effectively across technical and business teams. ## Description Design, build, deploy, and support production AI solutions. Develop agentic workflows, tool integrations, and orchestration pipelines. Build and evolve RAG and agent-based architectures. Create evaluation frameworks to improve quality, groundedness, and reliability. Implement AI observability, tracing, and monitoring capabilities. Develop automated testing and regression validation processes. Integrate AI solutions with APIs, enterprise applications, and data sources. Design reusable AI patterns, frameworks, and components that increase platform scalability and team productivity. Establish engineering best practices and contribute to code reviews. Research and adopt emerging AI technologies where they provide business value. Partner with stakeholders to translate business problems into AI solutions, Duration: 06 Months Contract (Conversion to permanent is the goal) Job Summary: You will work closely with the lead AI platform engineer to develop production-ready AI capabilit… + 15 hours ago + Apply easily ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [5 steps for running a Kubernetes environment at scale](https://www.wearedevelopers.com/videos/88-5-steps-for-running-a-kubernetes-environment-at-scale) - [Infrastructure as Code: The Developer's Secret Weapon](https://www.wearedevelopers.com/videos/1221-infrastructure-as-code-the-developer-s-secret-weapon) - [Agentic AI - From Theory to Practice: Developing Multi-Agent AI Systems on Azure](https://www.wearedevelopers.com/videos/1532-agentic-ai-from-theory-to-practice-developing-multi-agent-ai-systems-on-azure) - [Implementing Feature Environments with AWS and Terraform](https://www.wearedevelopers.com/videos/531-implementing-feature-environments-with-aws-and-terraform) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) ## Related Articles - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)