BCG U - Technical Programme Lead — AI Solutions

Role OverviewBCG U — BCG's dedicated capability-building and learning arm — is designing and delivering a national AI acceleration programme in partnership with IMDA. The programme helps Singapore enterprises develop a business-linked digital roadmap and implement a working AI solution — taking cohorts of companies through an 18-week journey from opportunity identification to production deployment with IMDA-appointed tech vendors.

The programme combines in-person bootcamps, 1:1 coaching, structured toolkits, and partnerships with major cloud and AI platform providers. It targets mid-sized non-ICT enterprises across manufacturing, logistics, retail/F&B, professional services, and other sectors — companies with real operational pain points and leadership willing to act.

We are seeking a technically deep practitioner to serve as the technical backbone of the programme — owning solution architecture quality, vendor technical governance, and enterprise-level technical coaching. This role sits within the BCG U programme team and works directly with enterprise leaders and appointed tech vendors.

What You’ll Do1. Programme Design Design the programme's core technical artefacts — AI solution architecture templates, data readiness assessments, integration design frameworks, and technical feasibility checklists that enterprises and vendors work through during bootcamps and coaching Define the technical engagement model with vendors — how solutions are scoped, how architecture is reviewed, how feasibility is validated, and how technical quality is governed throughout delivery Develop reusable reference architectures and solution patterns tailored to common SME use cases (e.g., predictive analytics, process automation, customer intelligence, document processing) 2. Solution Architecture & Technical Coaching Co-facilitate the solution design — making technical concepts (architecture, data, integration, risk) accessible to non-technical enterprise leaders while maintaining technical rigour Coach enterprises on translating business requirements into implementable technical scope — including data requirements, system integration points, and realistic deployment plans Assess technical feasibility of proposed AI solutions against each enterprise's data maturity, existing systems, and operational constraints Ensure solution designs are right-sized for SME contexts — pragmatic, deployable with lean IT teams, and built to deliver business outcomes 3.

Implementation Oversight Oversee AI solution implementation across the cohort — manage the appointed tech vendors, run governance checkpoints, monitor progress against milestones and KPIs, flag risks early, and ensure scope integrity throughout deployment Run technical governance checkpoints — architecture reviews, integration testing milestones, data quality gates, and deployment readiness assessments Manage enterprise-vendor dynamics during the build phase — ensure enterprises provide what vendors need (data, access, decisions) and vendors deliver what they committed to (timeline, quality, business fit Own impact validation — ensuring deployed solutions deliver measurable business results, not just working software Flag technical risks early and escalate where vendor delivery or enterprise readiness falls short 4. Tech Ecosystem Partnerships Support partnerships with major cloud and AI platform providers (e.g., AWS, Azure, GCP) — coordinating on technical enablement, reference architectures, and platform-level support for the programme Evaluate and advise on how market offerings can be leveraged within the programme

You Bring (Experience & Qualifications)Must-Haves8–12 years of experience with a strong technical foundation — solution architecture, enterprise architecture, data architecture, or AI/ML engineering — combined with consulting or advisory experience Demonstrated ability to design AI/digital solution architectures end-to-end: from business problem through data requirements, integration design, cloud deployment, and operational handover Working depth in at least one major cloud ecosystem (AWS, Azure, or GCP) and familiarity with AI/ML platform services, API integration patterns, and data pipeline design Hands-on experience building, deploying, or technically governing AI solutions (e.g., predictive analytics, NLP/LLM applications, process automation, conversational AI, agentic workflows) Experience working with SMEs or mid-market companies — understanding the constraints of limited data estates, lean IT teams, and pragmatic deployment requirements Credible with both audiences: able to explain technical architecture to a non-technical SME owner AND technically interrogate a vendor engineer's solution design Comfortable operating with high autonomy in a fast-moving, ambiguous programme environment

Nice-to-HavesPrior experience working with Singapore government-linked digital initiatives Familiarity with the Singapore SME landscape, particularly in sectors such as manufacturing, logistics, retail, F&B, or professional services Hands-on experience building or deploying AI solutions (e.g., customer service agents, document processing, conversational analytics) Comfort working in a high-autonomy, AI-augmented operating model (we use Claude and Claude Code extensively to build programme assets)

Why This RoleShape a first-of-its-kind national AI acceleration programme for Singapore SMEs Work directly with BCG partners and senior leadership Engage with major tech giants at a strategic level Flexible commitment model suited to independent consultants or portfolio professionals