{
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  "job_title": "Artificial Intelligence Engineer ( M&A )",
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  "job_description": "Role: Senior AI Engineer – M&A & Platform Modernisation\n\nLocation: London (Hybrid)\n\nEmployment Type: Permanent\n\nLevel: Senior / Lead\n\nReporting to: Head of AI / Engineering Director\n\nRole Overview\n\nWe are looking for a Senior AI Engineer with deep experience operating in M&A environments and delivering AI‑enabled application and platform modernisation (“ACP‑isation”) initiatives.\n\nThis role sits at the intersection of AI engineering, cloud platforms, and enterprise transformation, supporting acquisitions, carve‑outs, and post‑merger integration through scalable, production‑grade AI solutions.\n\nYou will work closely with architecture, cloud, data, and business stakeholders to accelerate value realisation across complex technology estates.\n\nKey Responsibilities\n\nAI Engineering & Delivery\n• Design, build, and deploy production‑grade AI/ML solutions, including:\n• LLM‑enabled applications (RAG, agents, copilots)\n• Predictive models and intelligent automation\n• AI services embedded into modernised platforms\n• Own end‑to‑end AI lifecycle: discovery, PoC, productionisation, monitoring, and optimisation\n• Implement MLOps / LLMOps pipelines (CI/CD, model versioning, observability)\n\nMergers & Acquisitions\n• Support technology due diligence from an AI, data, and architecture perspective\n• Analyse and rationalise overlapping application stacks, data estates, and AI capabilities\n• Design AI‑led approaches for:\n• Post‑merger integration\n• Carve‑outs and separations\n• Rapid capability uplift in acquired entities\n• Partner with legal, risk, and security teams to ensure compliance and responsible AI usage\n\nACP‑isation / Platform Modernisation\n• Lead AI components of application modernisation and platformisation programs\n• Migrate legacy or fragmented AI workloads to cloud‑native, containerised platforms\n• Embed AI into modern architectures:\n• Event‑driven systems\n• Microservices\n• Data platforms and control planes\n• Drive reuse through shared AI services, feature stores, and model registries\n\nArchitecture & Collaboration\n• Work with cloud and enterprise architects to define target AI architectures\n• Collaborate with product owners, data engineers, and platform teams\n• Provide technical leadership and mentorship to junior engineers\n\nRequired Experience & Skills\n\nCore Technical Skills\n• Strong hands‑on experience with Python, and at least one of:\n• TensorFlow, PyTorch, scikit‑learn\n• Practical experience with LLMs and Generative AI, including:\n• Prompt engineering\n• Retrieval‑Augmented Generation (RAG)\n• Agentic workflows\n• Experience deploying AI on cloud platforms (Azure, AWS or GCP)\n• Containerisation and orchestration (Docker, Kubernetes)\n\nM&A & Enterprise Transformation\n• Proven experience working in M&A, carve‑out, or post‑merger integration contexts\n• Comfortable operating in ambiguous, high‑pressure transformation environments\n• Experience rationalising and integrating multiple data and application landscapes\n\nPlatform & ACP‑isation Experience\n• Application and platform modernisation (legacy → cloud‑native)\n• AI embedded into enterprise platforms, control planes, or shared services\n• Strong understanding of data architecture, governance, and security\n\nProfessional Skills\n• Strong stakeholder communication and documentation skills\n• Ability to balance speed vs. risk in commercial M&A situations\n• Consulting mindset: outcome‑driven, pragmatic, commercially aware\n\nDesirable Experience\n• Experience in regulated environments (financial services, healthcare, energy)\n• Exposure to Responsible AI, model governance, and AI risk management\n• Knowledge of integration patterns for multiple ERP, CRM, or core systems\n• Previous experience in consulting, PE‑backed organisations, or scale‑ups",
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  "employer_website": "https://www.experis.com",
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  "job_employment_type": "Full–time",
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  "job_posted_at_timestamp": 1773619200,
  "job_posted_at_datetime_utc": "2026-03-16T00:00:00.000Z"
}