4 agentic ai developer jobs found in Washington

Key Accountabilities Design and delivery of AI‑enabled application components and agent workflows Reliability, performance, and operational supportability of deployed solutions Adherence to enterprise engineering standards, security controls, and data governance requirements   Principal Responsibilities Design, build, and test multi‑step agent workflows using established patterns such as ReAct, planner‑executor, and tool‑chaining Integrate LLMs (i.e. Claude and OpenAI) with enterprise APIs and internal systems, including robust handling of retries, edge cases, and degraded states Implement tool calling, function orchestration, and compensating actions to ensure workflows remain stable under failure conditions Design and implement human‑in‑the‑loop controls, including approvals, escalations, and exception handling where required by business logic or risk considerations Collaborate with product managers, domain experts, and technical stakeholders to refine...

You will partner with IT Director and internal client teams to translate complex business requirements into scalable, production-grade architectures — spanning pro-code Azure solutions, low-code Power Platform experiences, and emerging agentic AI frameworks. This role is the keystone that unblocks a high-performing development team by owning end-to-end solution design: from initial client discovery and MVP scoping through to architecture governance, observability strategy, and developer guidance. You will modernize existing AI workloads — including LangChain/LangGraph pipelines and RAG systems — while establishing a forward-looking architecture practice built on the latest AI, integration, and cloud-native patterns. The Role  Client engagement & discovery — Work directly with internal clients to deeply understand their use cases, identify the core problem and success criteria, and translate requirements into a clearly scoped MVP. Act as the technical voice in stakeholder...

Key Accountabilities Definition and execution of testing and quality assurance strategies for AI‑enabled workflows Continuous evaluation and monitoring of system behavior in production environments Contribution to auditability, risk management, and continuous quality improvement Principal Responsibilities Define quality criteria and testing strategies for agent workflows, covering accuracy, latency, safety, compliance, and operational risk Build automated evaluation harnesses to assess agent performance, including hallucination rates, tool misuse, policy violations, and task success Implement continuous production monitoring to detect anomalies, quality degradation, and emerging safety concerns Develop and maintain automated test suites using Playwright for UI testing and custom scripts for API and workflow validation Apply LLM evaluation frameworks to assess output quality, regression, and system drift over time Produce and...

The Role    Design, build and deploy AI-powered agents using low-code platforms such as Microsoft Copilot Studio, Lyzr, or equivalent agentic AI frameworks. Create and configure multi-step agentic workflows that leverage large language models (LLMs) to automate complex, judgment-intensive tasks. Write, test, and iterate on prompts to guide LLM behaviour accurately and reliably. Integrate AI capabilities, including natural language processing, intelligent document processing, and AI-driven decision-making, into business processes. Develop automation solutions on the Power Platform (Power Automate, Power Apps, AI Builder) to complement and extend AI agent capabilities. Support the deployment of automation processes using Power Automate where traditional automation is the right fit. Work with process specialists and business stakeholders to identify opportunities where AI agents can replace or augment manual work. Test, monitor, and continuously improve AI and automation...