Associate Director, AI Engineering
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Job Description
AI engineering leader guiding Blend360, a data consultancy, across production AI architecture and major client engagements. Setting technical standards, developing engineering leaders, and scaling the AI practice.
Responsibilities:
- 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
Requirements:
- 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
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