About Us:As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers.Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values different voices and lifts each other up. Here, we believe your unique perspective is important, and you'll build relationships by being authentic and respectful.Team Overview:The Thinktank Agent Platform Team is building Target’s enterprise platform for developing, evaluating, deploying, and operating intelligent AI agents at scale. The platform provides reusable capabilities for agent orchestration, tool integration, evaluation, observability, governance, and optimization, enabling teams across Target to build reliable and secure agentic solutions.The platform empowers engineering and product teams to rapidly create, test, monitor, and scale GenAI-powered agents while meeting enterprise standards for security, reliability, governance, and operational excellence.Position Overview:As a Senior Engineer on the Thinktank Agent Platform Team, you will design and build core platform capabilities that support agent development, orchestration, evaluation, observability, and production execution. You will work at the intersection of distributed systems, platform engineering, and GenAI to create reliable, scalable, and enterprise-grade agentic solutions.Key ResponsibilitiesDesign and develop scalable backend and platform services for agent orchestration, execution, evaluation, and monitoringBuild reusable capabilities for agent lifecycle management, tool integration, prompt and model configuration, and workflow executionIntegrate LLMs, AI agents, enterprise tools, and external systems into production-grade solutions with strong reliability and guardrailsDevelop APIs, SDKs, and platform services that enable teams to build, test, deploy, and manage intelligent agentsBuild and enhance evaluation capabilities, including offline and online evaluations, test suites, quality metrics, and agent optimizationDevelop observability capabilities for tracing, monitoring, dashboards, alerts, and debugging agent behaviorEnsure platform capabilities meet enterprise standards for security, governance, privacy, reliability, and auditabilityCollaborate with product, data science, application engineering, and enterprise architecture teams to define and deliver platform featuresOptimize system performance, scalability, resiliency, and cost efficiency in a cloud-native environmentContribute to engineering standards and best practices for building GenAI and agentic systemsRequired QualificationsBachelor’s or Master’s degree in Computer Science or a related field4+ years of experience in backend, platform, or distributed systems engineeringStrong programming skills in Java, Kotlin, Go or PythonExperience building scalable distributed systems, APIs, and microservices architecturesFamiliarity with REST APIs, event-driven systems, asynchronous processing, and cloud-native technologiesUnderstanding of system design, scalability, reliability, security, and observability principlesExperience with containers, Kubernetes, CI/CD pipelines, and modern software delivery practicesExperience working in agile, cross-functional engineering teamsPreferred QualificationsExperience with AI/ML or GenAI systems, including LLM integrations and agent-based applicationsFamiliarity with agent orchestration frameworks, tool calling, prompt management, and multi-agent systemsExperience building evaluation frameworks for LLMs or AI agentsKnowledge of tracing, observability, monitoring, dashboards, and alerting for distributed or AI systemsExperience developing platform APIs, SDKs, or reusable developer toolsUnderstanding of AI safety, governance, guardrails, and responsible AI practicesExperience with vector databases, retrieval-augmented generation, model gateways, or semantic searchFrontend experience with React is a plusExperience with cloud platforms, GCP, AWS or Azure