Staff AI Engineer

This is a fully remote position, open to applicants in United Kingdom, +5 more countries.

📋 Description

• Define the technical trajectory of Research Flow and broader AI systems.

• Collaborate with Product and Engineering leaders to establish technical direction and set delivery priorities.

• Direct the architecture for AI-assisted study design, adaptive conversations, and research synthesis.

• Tackle complex AI engineering challenges through exploration, implementation, and production delivery.

• Develop generative AI applications utilizing LLMs, RAG, vector search, tool use, and agentic systems.

• Create reusable AI services and APIs.

• Steer machine learning service and workflow architecture leveraging Python, Docker, Kubernetes, and AWS.

• Design batch and real-time processing pipelines using technologies such as Kafka and Airflow.

• Establish patterns for retrieval, vector search, model orchestration, experimentation, deployment, and data handling.

• Define evaluation strategies, benchmarks, release criteria, monitoring, security, privacy, and safeguards for AI systems.

• Set reusable engineering standards encompassing testing, observability, security, incident response, and deployment.

• Mentor engineers and assist technical leads.

• Prioritize AI investments based on customer requirements, feasibility, and business impact.

• Convey technical risks and trade-offs to both technical and non-technical stakeholders.

⛳️ Requirements

• Extensive experience in building and operating machine learning or AI systems in production, with technical leadership extending beyond individual projects.

• Proven history of leading intricate cross-team engineering initiatives from vague requirements to quantifiable production outcomes.

• Proficient in Python and software engineering; capable of directly contributing to production code.

• Experience in designing production services and APIs using frameworks like FastAPI.

• Hands-on experience in developing generative AI applications utilizing LLMs, RAG, tool use, or agentic systems.

• Strong grasp of enterprise RAG systems, including retrieval architecture, chunking, embeddings, reranking, evaluation, and monitoring.

• Experience in defining evaluation methodologies and employing evidence for model, architecture, and release decisions.

• Familiarity with PyTorch, LangChain, LangGraph, or similar technologies.

• Significant experience with AWS, Docker, Kubernetes, Terraform, and CI/CD practices.

• Knowledge of AWS SageMaker or AWS Bedrock.

• Experience with event-driven processing, vector databases, and ML lifecycle tools such as Kafka and MLflow, or equivalent technologies.

• Proficiency in observability and troubleshooting production issues using Datadog or OpenSearch.

• Sound judgment in balancing delivery speed, quality, reliability, scalability, security, and cost.

• Ability to influence technical decisions across teams and achieve alignment without formal authority.

• Experience mentoring engineers and enhancing team effectiveness.

• Eligibility to work in the UK, Ireland, Germany, Portugal, Spain, or the Netherlands.

🏝️ Benefits

• 5–10% bonus based on level and performance.

• Fully remote work arrangement.

• An equal-opportunity workplace dedicated to diversity, respect, transparency, and trust.