Gemini Agent Platform AI Engineer

Overview

Hands-on engineering role helping accelerate adoption of Google Cloud, Gemini and agent-based artificial intelligence across Unilever, with a strong product engagement dimension.

What you'll do

• Partner with product and engineering teams to understand existing applications, technical requirements and modernisation needs, and identify opportunities to adopt Google Cloud technologies.
• Support the migration and modernisation of applications onto Google Cloud, working with product teams and architects to define target architectures and practical engineering approaches.
• Design, develop and deploy artificial intelligence applications and intelligent agent solutions using Google Gemini and Google Cloud technologies.
• Take solutions through the complete engineering lifecycle, from experimentation and technical design through development, testing, deployment, monitoring and continuous improvement.
• Build reusable components, frameworks and engineering patterns that accelerate future artificial intelligence and Google Cloud implementations.
• Develop integrations between intelligent agents, enterprise applications, application programming interfaces and data sources.
• Design solutions that securely connect artificial intelligence models with trusted enterprise information and services.
• Build and orchestrate workflows involving artificial intelligence models, software tools, business applications and cloud services.
• Evaluate technical approaches based on engineering feasibility, scalability, reliability, security, operational readiness and cost.
• Apply strong software engineering practices across source control, automated testing, deployment automation, version management and release processes.
• Implement appropriate security, identity and access management, monitoring, observability and responsible artificial intelligence practices.
• Evaluate and improve the quality, reliability and technical performance of artificial intelligence and agent-based solutions.
• Work closely with architects, product teams and engineering partners to convert business requirements and early prototypes into production-ready solutions.
• Create clear technical documentation, reusable implementation guidance and engineering standards that enable other teams to adopt proven solutions and patterns.
• Support rapid experimentation and proof-of-concept development while ensuring successful solutions have a clear path towards production and scale.

What you'll need

• Strong software engineering experience with the ability to design, develop and productionise cloud-based applications.
• Hands-on experience designing, developing and deploying solutions on Google Cloud.
• Strong understanding of the software development lifecycle, covering solution design, development, testing, deployment, monitoring and production operations.
• Experience developing applications using generative artificial intelligence or large language models.
• Understanding of intelligent agent concepts, including tool use, orchestration, grounding and context management.
• Experience with cloud-native application architectures, application programming interfaces and integration patterns.
• Experience with modern software engineering practices, including source control, automated testing, continuous integration and automated deployment.
• Ability to understand existing application architectures and define appropriate approaches for migration and modernisation onto Google Cloud.
• Ability to engage effectively with product, architecture and engineering teams and translate business and technical requirements into practical engineering solutions.
• Ability to take prototypes and early-stage solutions through engineering into secure, scalable, reliable and production-ready solutions.

Nice to have

• Hands-on development experience with Google Gemini and Vertex AI.
• Experience developing cloud or artificial intelligence solutions using Python.
• Experience with Google technologies and frameworks for building intelligent agents.
• Experience with retrieval-augmented generation, embeddings, semantic retrieval and vector search.
• Experience with artificial intelligence evaluation, monitoring, observability and responsible artificial intelligence controls.
• Experience creating reusable artificial intelligence components, engineering frameworks or platform capabilities.
• Experience with application migration and modernisation on Google Cloud.
• Experience with cloud-native technologies, including containers and serverless architectures.
• Experience with enterprise application integration and application programming interfaces.
• Experience working across global, cross-functional product and engineering teams.
• Experience working with external technology or delivery partners.

Details

• Location: Bangalore, India.
• Full-time, permanent.
• Applicants must have the right to work in India.
• Reports to: Senior Manager, HAP.
• Global scope, with close collaboration across product teams, architects, platform teams and engineering partners.