Principal AI Engineer
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Job Description
Principal AI Engineer leading production AI architecture, technical quality, and engineering capability at Blend data consultancy. Designing scalable AI systems and guiding major client engagements.
Responsibilities:
- Set technical direction across AI Engineering, including architecture principles, engineering standards, delivery practices and technical capabilities
- Own the technical quality of major AI engagements involving architecture, scale, complexity and delivery risk
- Lead multiple projects and technical workstreams, setting priorities and direction
- Design and review production AI architectures, including retrieval and knowledge layers, agentic pipelines, evaluation and multilingual systems
- Manage 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 technical quality of major AI proposals, translating concepts into architectures, scopes, delivery models, team structures, estimates and commercial assumptions
- Work with commercial and account leadership to shape technical propositions and identify opportunities
- Develop senior engineers and technical leads
- 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 operating beyond individual project leadership, with responsibility for technical direction, engineering quality or capability across multiple teams
- Production Python experience
- Experience with substantial codebases and API-driven systems that perform reliably at scale
- Recent, personal experience architecting and building production AI systems
- Experience with retrieval strategy, caching, context economics, serving constraints, evaluation, observability and practical production issues
- Strong systems thinking and ability to reason through unfamiliar platforms and problems
- Experience leading complex programmes or multiple concurrent engineering workstreams
- Accountability for technical direction, planning, resourcing, risk and delivery outcomes
- Judgement to know when to intervene personally and when to lead through others
- Experience developing senior engineers and technical leaders
- Experience shaping team capability and raising the engineering bar across a wider organisation
- Commercial awareness to turn technical solutions into realistic scopes, team shapes, estimates and delivery plans
- Experience contributing to account growth, technical propositions or go-to-market activity within a consulting organisation
- Confidence operating with senior clients and executives while remaining credible with engineers at code and architecture level
- Ability to make difficult technical calls, create clarity amid ambiguity and take responsibility for outcomes
- Strong experience with Databricks and Azure OpenAI
Benefits:
- Employees can work remotely
- Great Place To Work accreditation across office locations
- Focus on DEI initiatives and championing representation
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