Shape the Future of AI & Data with Us
Datatonic is Google Cloud's premier AI and data partner, specializing in designing, building, and operating production AI systems. We combine software engineering, machine learning, data engineering, and analytics on Google Cloud Platform (GCP) with top-tier consulting skills to turn complex business requirements into reliable, production-grade products.
Responsibilities
As a Pod Lead, you will bridge high-level technical leadership, hands-on engineering execution, team leadership and consulting. You will lead, mentor, and grow a dedicated pod of AI Engineers while directly designing, deploying, and evaluating cutting-edge AI systems. You will own end-to-end project delivery quality, account growth, and team performance while remaining a key technical architect and direct builder on production workloads.
1. Hands-On Engineering & AI Systems
•Design, deploy, and operate production-grade AI systems, including agentic workflows, Retrieval-Augmented Generation (RAG), orchestration, and foundation model fine-tuning.
•Build evaluation frameworks, define success criteria, and measure system performance using offline metrics, online quality monitoring, human-in-the-loop reviews, and failure-mode analysis.
•Build robust production pipelines, serving architectures, and monitoring for AI and ML workloads on client platforms (primarily GCP).
•Use coding and research agents daily in delivery, and build custom agents for evaluation suites, prompt/tool regression, data labeling, and repeatable team workflows.
2. Team Leadership & Talent Development
•Lead, mentor, and grow a pod of MLEs and Data Scientists, taking ownership of hiring, career development, and performance management.
•Manage pod utilization, identify risks early, drive team certifications, and cultivate a high-trust, inclusive, and innovative engineering culture.
•Set and uphold technical standards, conduct architecture and code reviews, and define best-practice ways of working across the pod.
3. Client & Strategic Leadership
•Build strong client relationships, translating business challenges into AI system designs with explicit constraints and measurable success criteria.
•Articulate complex architectural and technical concepts clearly to both technical teams and senior client executive stakeholders.
•Collaborate with Software, Data, Platform, Analytics, and UX engineers to ensure systems are usable, governable, and operable.
4. Delivery & Commercial Impact
•Own delivery quality, timelines, and scope discipline across pod engagements, surfacing scope creep as strategic expansion opportunities.
•Proactively identify growth opportunities within existing accounts to expand client relationships beyond the initial Statement of Work (SOW).
•Serve as the subject matter expert in pre-sales, leading solution design, SOW scoping, and effort estimation for complex AI initiatives.
•Contribute reusable assets, methodologies, evaluation suites, and public technical content to advance the broader AI practice.
Requirements
•7+ years of experience in machine learning, data science, or applied AI, with at least 2+ years leading technical teams or projects end-to-end.
•Strong software engineering foundations across the modern AI stack:
•Classical ML & Stats: Classical ML techniques (TensorFlow, PyTorch, scikit-learn), forecasting, and feature engineering.
•Generative AI & Agents: RAG, tool-calling, orchestration, guardrails, LLM-based agentic architectures, and fine-tuning.
•Cloud & MLOps: Production deployment on cloud platforms (Google Cloud preferred: Vertex AI, BigQuery ML, Gemini).
•A track record of moving beyond exploratory notebooks to define, measure, and prove system quality with evidence and metrics.
•Experience in client-facing consulting or pre-sales environments, with comfort operating at the intersection of technical execution, delivery management, and account growth.
•Exceptional verbal and written communication skills to convey complex technical paradigms to diverse stakeholders.
Benefits
•25 days holiday plus bank holidays
•Private health insurance (Vitality Health) and Smart Health Services
•50% gym membership discounts (Nuffield Health, Virgin Active, Pure Gym)
•Hybrid model with a WFH allowance
•Access to learning platforms like Udemy
•Pension (auto-enrollment after probation period, 3% employer contributions rising 1% per year of service up to a max of 10%)
•Life insurance (3 x base salary)
•Income protection (up to 75% of base salary, up to 2 years)
•Cycle to Work Scheme
•Tech Scheme
