Forward Deployed AI Architect (GenAI, AWS)
Embed with enterprise customers to understand their operations, then design and ship production GenAI systems on AWS, owning delivery from problem framing through evaluation and deployment.
GoodData.ai is a cloud-based business intelligence platform revolutionizing the way in which companies provide analytics to their customers and partners. Our mission? To push the boundaries of BI and redefine the analytics experience through the power of AI.
Join us in building a groundbreaking AI-powered data analytics platform, where we focus on delivering real value—AI without the hype.
We’re creating an AI solution and now pushing it into the production phase. Be part of the journey as we shape the future of Analytics Intelligence.
Design and enhance sophisticated AI systems with multiple layers, including routers, agents, evaluation (LLM-as-a-judge), and AI monitoring.
Develop and optimize a multi-layered agentic AI system: routers, tool-calling agents, RAG pipelines, evaluation (LLM-as-a-judge), and AI observability.
Play a key role in shaping the architecture of our groundbreaking AI solution as we transition it into the production phase.
Implement Python-based microservices within Kubernetes, ensuring seamless integration and communication between services in the cloud.
Focus on scalability, performance, and security across our AI infrastructure, contributing to a robust and reliable product.
Work closely with a diverse team of subject-matter experts, including senior engineers, UX designers, and project managers, to bring innovative ideas to life.
Proficiency in Python and experience with building microservices.
Familiarity with generative AI concepts - LLM APIs, tool/function calling, prompting - and an interest in building AI-driven solutions.
Experience with cloud-based back-end systems and distributed architectures (such as Kubernetes, Docker, gRPC, Protobuf, Pulsar, AWS, GCP, Azure...).
Ability to work collaboratively in a dynamic team environment.
You are proactive and self-driven.
Proven ability to quickly learn and understand complex subject matter.
Knowledge of Prompt engineering, LLM Ops, RAG framework.
Hands-on experience building agentic systems.
Experience with CI/CD style of development.
Familiarity with data science concepts or building ML infrastructure.
At GoodData.AI, we’re building the future of agentic AI for data intelligence.
Our full-stack data intelligence platform empowers companies to turn raw data into real business impact — from agentic AI apps to embedded analytics that scale securely and seamlessly. With GoodData.AI, organizations don’t just analyze data, they monetize it.
But what really sets GoodData.AI apart is our mission: to put intelligence wherever decisions are made. That’s why we’ve built a platform that’s AI-native, composable, and built for the way modern enterprises work.
#LI-Hybrid
Embed with enterprise customers to understand their operations, then design and ship production GenAI systems on AWS, owning delivery from problem framing through evaluation and deployment.
Leads the design and delivery of secure, production-ready AI/ML systems, including agentic workflows and RAG capabilities, while guiding architecture and communicating technical recommendations to stakeholders.
Develop and evolve generative AI applications and services using Python and LLMs, designing RAG solutions, integrating existing systems, and improving the scalability, reliability, and observability of AI products.
Build agent-driven and retrieval-augmented AI systems for legal work, improve LLM quality through fine-tuning and evaluation, and develop scalable search and document-processing pipelines.
Develop computer vision and deep learning algorithms for centimeter-level vehicle localization on HD maps, combining multi-camera vision, 3D geometry, and optimization for robust autonomous driving.