Artificial Intelligence Engineer

Role: Agentic AI EngineerDuration: 6 month contract (likely extension)We are seeking a genuinely hands-on, strategic AI First/Mindset Engineer who takes full ownership of work, thrives in a fast-paced environment, continuously experiments, leveraging modern AI-assisted development tools - GitHub Copilot, Codex, and Claude. Core Languages & FrameworksPython — strong production experience; primary languageTypeScript / JavaScript — good to haveAgent & LLM EcosystemGoogle Agent Development Kit (ADK)LangChain & LangGraph — agent orchestrationModel Context Protocol (MCP) — FastMCP or similar connector developmentA2A / ACP inter-agent communication protocolsLLM streaming APIs — Vertex AI / Gemini, Bedrock, OpenAIOASF (Open Agentic Schema Framework) — agent schema and registry patternsAPIs, Services & IntegrationFastAPI / AsyncIO — REST API design, webhooks, event-driven servicesOpenAPI / AsyncAPI / Protobuf — API contract designApache Kafka, GCP Pub/Sub — event streaming and async agent pushTesting & Quality EngineeringAutomated Test-Driven Development (TDD) — designing systems with test-first disciplineRegression testing — ensuring behavioral stability across rapid iterationsEnd-to-End (E2E) testing — validating agent workflows across services and integrationsTest automation for APIs, agents, and event-driven systemsSecurity, Identity & GovernanceOpen Policy Agent (OPA) — policy enforcement in agent workflowsSPIFFE / Workload Identity — non-human identity and mTLSObservability & ReliabilityOpenTelemetry — tracing, spans, structured observabilityGrafana — dashboards and SLO visualizationDORA metrics & SLO engineeringPlatform, Infrastructure & DataKubernetes; Google Cloud Run / Cloud Run Jobs — hands-on operational depthDocker containerizationGitHub Actions, Cloud Build — CI/CD pipelinesVectorDBFirestore, MongoDB, or equivalent NoSQLPostgreSQL / SQL — relational databasesGoogle Cloud Storage (GCS) — artifact and deployment package managementRedis — caching