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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Data Scientist - AI, MLOps, GenAI Lead - **Company:** Hackajob Ltd - **Location:** London, UK - **Experience:** Expert - **Salary:** £80,000.0 - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Artificial Intelligence, Automation of Tests, BigQuery, Cloud Computing, Cloud Engineering, Code Review, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Data Warehousing, Database Design, Database Queries, Python (Programming Language), Machine Learning, Natural Language Processing, NumPy, Performance Tuning, Software Product Management, Standard Sql, Software Engineering, Google Cloud, Flask (Web Framework), Large Language Models, Multi-Agent Systems, Fastapi, Pandas, Data Lakes, Kubernetes, Information Technology, Machine Learning Operations, Virtual Agents, Software Version Control, Docker - **Published:** September 11, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5878314828 ## About the Role * Expert-level experience building complex LLM-powered systems and multi-agent workflows using frameworks like LangGraph, LangChain, AutoGen, or ADK. * Deep practical understanding of machine learning algorithms, natural language processing techniques, and optimizing large language models for enterprise deployment. * Strong proficiency in designing optimized ELT/ETL pipelines and managing data lake/data warehouse architectures. * Hands-on experience with Google Cloud Platform services including Vertex AI, BigQuery, Cloud SQL, and Google Cloud Storage. * Proven track record of architecting pipelines for model deployment, performance tracking, hyperparameter tuning, and containerized workflows using Docker and Kubernetes. * Extensive experience leading technical delivery, defining engineering milestones, running code reviews, and mentoring junior or intermediate engineering talent. * Advanced, production-grade Python proficiency with Pandas, NumPy, FastAPI, or Flask, with a focus on clean, modular, and highly testable code. * Expert SQL querying, database design, partitioning, and optimization strategies for large-scale BigQuery environments. * Google Cloud Certified Cloud Engineer. * Google Cloud Certified Professional Data Engineer or Cloud AI Engineer. * A Bachelors or Masters degree in Computer Science, Software Engineering, Artificial Intelligence, or a highly quantitative field is desirable, though proven experience in shipping production-grade commercial AI systems may substitute. * IT HNC/HND courses are also accepted. ## Description * Design and scale robust, secure, production-ready multi-agent workflows, orchestrations, and advanced RAG architectures in collaboration with Enterprise Architecture principles. * Drive delivery by designing and building agentic solutions from piloting through full implementation. * Establish strict coding standards, code review processes, testing frameworks, and evaluation metrics for generative AI applications. * Support and enforce the standards set by the Head of Engineering and Technical Architect. * Partner closely with our GCP and Data Engineering teams to build seamless LLMOps/MLOps CI/CD pipelines. * Ensure scalable and cost-effective model deployment via Vertex AI and containerized environments. * Take ownership of building and maintaining robust LLMOps pipelines. * Implement robust evaluation frameworks, latency monitoring, and automated guardrails to ensure enterprise-grade safety, security, and compliance. * Manage engineering workflows, CI/CD pipelines, version control, and evaluation frameworks for internal developer-facing AI assets, including prompt libraries and automated testing agents. * Act as a technical mentor to a team of intermediate and junior AI Engineers, fostering a culture of continuous learning, clean code, and agility. * Collaborate with the AI Product Owner and Business Analysts to translate abstract business use cases into structured, achievable technical sprints. * Shift the teams focus from sandboxed proof-of-concepts to reliable, resilient applications deployed to production for global users. * Support the companys evolving AI strategy by providing an expert voice on use case identification, platform identification, and tool selection. * Advise the AI portfolio lead in scaling impact and AI capability across the company beyond the Group AI Team. * Stay up to date on market trends, new opportunities, and the changing landscape of AI technologies. Technologies: * AI * Architect * BigQuery * CI/CD * Cloud * Data Warehouse * Docker * ETL * FastAPI * Flask * GCP * Support * Kubernetes * LLM * Machine Learning * MLOps * Product Owner * Python * RAG * SQL * Security * numpy * pandas * Agentic AI * ARM ## Related Videos - [Vectorize all the things! 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