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Role Description

We are hiring a Senior AI Engineer to lead the development of our cloud-based (Google Cloud), commercial AI products. You will bridge the gap between experimental data science prototypes and production-grade software. You will architect the robust systems and LLMOps workflows necessary to transform AI models into reliable, enterprise-ready applications. By designing stable backend architectures and seamless integration layers, you will ensure our AI solutions are not just functional, but ethical, efficient, and high-value products that meet the rigorous demands of our commercial clients.

Key Responsibilities

• Define the end-to-end architecture for AI products on Google Cloud Platform (GCP), ensuring high availability, security, and cost-effectiveness.
• Architect and develop high-performance backend services and APIs using Python (FastAPI) to serve large language models at scale.
• Design advanced Retrieval-Augmented Generation (RAG) systems, selecting and managing vector databases and optimizing embedding strategies for accuracy and speed.
• Build robust integration layers that connect AI agents securely to external enterprise systems, CRMs, and legacy databases.
• Conduct code reviews, provide technical guidance, and foster a culture of continuous learning and innovation within the engineering team.
• Collaborate with infrastructure teams to define deployment strategies, ensuring solutions scale dynamically under load.
• Lead the implementation of rigorous evaluation frameworks to monitor model performance, drift, and cost in real-time.
• Develop reusable internal libraries and architectural patterns and standards to accelerate the delivery of AI solutions across multiple client engagements.
• Mentor engineers on best practices for building deterministic software around probabilistic AI models.

Qualifications

• 6+ years of software engineering experience with at least 3 years dedicated to AI/ML application development.
• Expert proficiency in Python AI application development and modern API architecture (REST, GraphQL, gRPC) using enterprise standards like static type checking and data validation.
• Deep experience building production applications with LLM frameworks such as LangChain, LangGraph or LlamaIndex.
• Hands-on expertise with vector databases (Pinecone, Weaviate, PostgreSQL) and search algorithms.
• Strong understanding of LLMOps principles, including model registry, versioning, and serving infrastructure specifically in Google Cloud.
• Experience in Typescript development for prototyping and integrations.
• Proficiency with git workflows and understanding of standard application development processes.

Preferred Qualifications

• Knowledge of advanced prompt engineering and fine-tuning techniques (LoRA, PEFT).
• Experience optimizing inference costs and latency for large-scale deployments.
• Previous experience in a client-facing consulting role, managing diverse stakeholders and navigating complex organizational structures.

Benefits

• Net-zero cost medical option.
• Company contributions to your HSA.
• Fertility support.
• Fully-paid parental leave.
• Monthly stipend for your lifestyle spending account.
• And much more.