Job Description: Role: Generative AI Engineer Duration: Long-Term Contract Location: Hybrid - 4 days/week onsite in SE MI Job Description: We are seeking a hands-on AI Engineer to design, develop, and implement AI-powered applications and intelligent automation solutions. This role will focus heavily on building Generative AI and agentic AI capabilities within a Google Cloud Platform (GCP) environment. The ideal candidate will have strong Python development skills, hands-on GCP experience, and an interest in building AI agents that can interact with enterprise data, perform multi-step reasoning, automate analysis, and deliver explainable insights to end users. This position combines AI development, backend engineering, cloud technologies, and data integration, with a particular focus on integrating Google large language models (LLMs) with BigQuery and enterprise data. Key Responsibilities AI & Generative AI Development - Translate business requirements into AI-powered applications, algorithms, models, and automation solutions. - Design and develop intelligent applications leveraging technologies such as Generative AI, natural language processing, machine learning, and intelligent automation. - Build AI agents capable of interacting with enterprise data and supporting complex analytical and investigation workflows. - Develop multi-step reasoning and tool-using agent workflows. - Integrate Google LLM capabilities with BigQuery and other GCP services. - Design mechanisms to retain relevant investigation context and intelligence across sessions. - Develop AI-powered solutions that provide clear, traceable, and explainable insights to end users. - Conduct experimentation to evaluate and improve AI solution accuracy, reliability, and effectiveness. Backend & API Development - Develop backend services and APIs that enable integration between AI applications, enterprise data, and user-facing experiences. - Build scalable Python-based applications using frameworks such as FastAPI, Flask, or Django. - Develop services that allow AI agents to securely interact with data sources and supporting applications. - Write reusable, maintainable, and testable code following modern software engineering practices. GCP & Data Integration - Build AI solutions within Google Cloud Platform (GCP). - Integrate AI applications and agents with BigQuery data. - Develop solutions leveraging relevant GCP technologies, including Cloud Run. - Build workflows that allow AI agents to generate and execute BigQuery SQL. - Monitor and optimize cloud-based AI applications for performance and reliability. AI Agent Development & Governance - Develop AI agents capable of performing multi-step investigations and root cause analysis. - Create structured investigation memory models, with the ability to incorporate semantic approaches where appropriate. - Implement logging and traceability to support transparency across AI-driven workflows. - Establish appropriate governance mechanisms around AI-generated results and automated actions. - Ensure AI solutions provide understandable and explainable outputs for quality engineering users. DevOps & Engineering Practices Utilize Infrastructure as Code practices with Terraform. Support automated build, testing, and deployment through CI/CD pipelines. Work with CI/CD technologies such as Tekton or Jenkins. Apply Test-Driven Development (TDD), test-first development, MVP, and evolutionary design pr