Found.dev
Role Highlights
Languages used
Python
Key skills
Vector Database
Computer Science
Integrations
API
Customer Success
Full Stack
LLMs
Forward Deployed Engineer
Cloud
PhD
Security
Reliability
Infrastructure
Embedded
Architecture
Embeddings
Deployment
Research
Servers
Tools, Libraries and Frameworks
Vertex AI
GCP
LOOP
React
Description
This role involves acting as an embedded builder who bridges the gap between frontier AI products and production-grade customer environments. The position requires moving beyond high-level architecture to code, debug, and ship bespoke agentic solutions directly within customer systems. Responsibilities include addressing integration complexities, data readiness issues, and state-management challenges to ensure enterprise-grade maturity. The role also entails building evaluation pipelines and observability frameworks to maintain accuracy, safety, and latency. Additionally, the individual will identify field patterns to inform future product roadmaps and collaborate with customer engineering teams to implement development best practices.
Required Qualifications and Skills
Candidates must possess a Bachelor’s degree in Engineering, Computer Science, or a related field, or have equivalent practical experience. A minimum of three years of experience is required in taking production-grade AI-driven solutions from conception to launch using Python. Applicants must demonstrate experience architecting AI systems on cloud platforms and building data pipelines using vector databases and RAG-like architectures. Preferred qualifications include a Master’s degree or PhD in AI or a related technical field, as well as experience implementing multi-agent systems and knowledge of LLM-native metrics and optimization techniques.
Disclaimer
Disclaimer: Job and company description information and some of the data fields may have been generated via GPT-4 summarisation and could contain inaccuracies. The full external job listing link should always be relied on for authoritative information.
About the company
Description
At gTech's Users and Products team, innovations are focused on enhancing user engagement and solving complex customer needs through technical expertise and a deep understanding of Google's and Alphabet's broad product environments. The team acts as a bridge between Google’s users and its product teams, ensuring that user insights are integrated into product offerings which support numerous annual product launches. The newly formed Machine Learning Data Operations (MLDO) team within gUP Operations plays a critical role in delivering and tuning machine learning and GenAI data operations across Google’s product suite, leveraging extensive global vendor networks. Google's overarching goal is to create impactful products and services, with gTech playing a strategic role in bringing these solutions to fruition through technological and operational expertise.
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