Associate Director, AI Engineering

🕒 il y a 24 jours

🇬🇧 Royaume-Uni – Télétravail

⏰ Temps Plein

🟠 Senior

🤖 Ingénieur IA

👻 Score fantôme 20%

Ce que ça veut dire : la probabilité que cette offre reste ouverte sans recrutement actif.Comment le lire : 60 % ou plus, on pense que c'est une offre fantôme. Un score plus bas est moins inquiétant.Comment on la calcule : ancienneté, republications, postes ouverts vs taille de l'équipe, rapidité de clôture, et si le salaire est indiqué.À noter : une estimation à partir de données publiques, pas un jugement sur l'entreprise. De vraies offres peuvent avoir un score élevé, alors prenez-le comme un indice, pas comme un fait.

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Blend360

Site WebLinkedInTous les Emplois

501 - 1000 employés

🏥 Santé

🏨 Hôtellerie

✈️ Tourisme

💰 €100 000 000 Private Equity Round en 2022-08

Healthcare • Hospitality • Travel

Blend360 est une entreprise de services professionnels spécialisée dans l'IA, l'analyse des données et les solutions basées sur les données. Elle collabore avec les entreprises du Fortune 1000 et les grandes marques pour relever des défis majeurs en intégrant l'humain et l'intelligence artificielle. Blend360 se concentre sur plusieurs domaines, notamment la business intelligence, l'ingénierie des données, la data science, MLOps et la gouvernance des données. Leurs secteurs d'expertise comprennent les services financiers, l'énergie, la santé et les sciences de la vie, le commerce de détail, la technologie, les médias et télécommunications, et le tourisme et l'hôtellerie. Blend360 est reconnue pour ses solutions en IA et en données, ayant reçu des distinctions telles que "Solution d'Activation de l'IA de l'Année" et figurant parmi les "Meilleurs Fournisseurs de Services d'IA Générative 2024".

Description

• Set technical direction across AI Engineering, defining architecture principles, engineering standards, delivery practices and technical capabilities • Own the technical quality of major AI engagements, especially those involving architecture, scale, complexity or delivery risk • Lead multiple projects and technical workstreams, setting priorities and direction while enabling team execution • Design and review production AI architectures, including retrieval and knowledge layers, agentic pipelines, evaluation and multilingual systems • Evaluate cost, latency, reliability and scalability trade-offs • Review code, prototype approaches, resolve architectural issues and work directly with engineers on difficult problems • Run rigorous design reviews and raise engineering standards across the practice • Act as senior technical counterpart to clients, including CxO and architecture leadership • Own the technical quality of major AI proposals, including architectures, scopes, delivery models, team structures, estimates and commercial assumptions • Shape technical propositions, identify opportunities and guide AI Engineering practice investments • Develop senior engineers and technical leads and build leadership depth and succession • Shape the AI Engineering capability plan, including hiring priorities, skills development, team composition and senior technical talent standards

🎯 Exigences

• At least 10 years’ experience across AI, data and software engineering • 3+ years leading engineering teams or a substantial technical function within consulting or professional services • Experience beyond individual project leadership, with responsibility for technical direction, engineering quality or capability across multiple teams • Production Python experience with substantial codebases and API-driven systems operating reliably at scale • Recent personal experience architecting and building production AI systems • Ability to discuss retrieval strategy, caching, context economics, serving constraints, evaluation, observability and practical failures • Strong systems thinking and ability to reason through unfamiliar platforms and problems • Experience leading complex programmes or multiple concurrent engineering workstreams with accountability for technical direction, planning, resourcing, risk and delivery outcomes • Judgement to intervene personally when needed and delegate effectively while retaining accountability for technical quality • Experience developing senior engineers and technical leaders and raising engineering standards across an organisation • Commercial awareness to turn technical solutions into realistic scopes, team structures, estimates and delivery plans • Experience contributing to account growth, technical propositions or go-to-market activity within a consulting organisation • Confidence working with senior clients and executives while remaining credible with engineers at code and architecture level • Ability to make difficult technical decisions, create clarity amid ambiguity and take responsibility for outcomes • Strong experience with Databricks and Azure OpenAI • Nice to have: ontology, knowledge graph or semantic layer experience • Nice to have: delivery experience in pharma or CPG • Nice to have: practical experience designing systems around EU AI Act requirements • Nice to have: multilingual AI systems in production • Nice to have: presence in the Databricks or Microsoft partner ecosystem • Nice to have: experience shaping go-to-market and commercial strategy for an AI Engineering practice