Colin Wilkie McLellan
Senior Ai Engineer @Amazon Web Services (AWS)
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WORK HISTORY
Senior Ai Engineer @Amazon Web Services (AWS)
Formally promoted to Senior AI Engineer, with a role title shift to reflect the transition from building demos and proof-of-concept solutions to delivering production-ready agentic AI workloads embedded directly within customer development teams. Collaborated closely with PACE, who provided engagement management while taking full technical ownership - from scoping and solution design through to implementation and evaluation - across approximately 10 embedded projects of 2–4 weeks each. Projects spanned a range of agentic AI applications including hyper-personalisation data pipelines and voice-to-voice contact centre agents.One of the most impactful engagements involved a US Government agency, where a pain point was identified in a process that typically lasted months. Conducted experimental research to design a robust LLM backed approach, then collaborated with a teammate to implement and deploy a solution into the customer\'s account that reduced the longest phase of the process from months to hours. The project had visibility up to state governor level as part of an election pledge to address the underlying problem.Built a contact centre voice agent using the pre-release Nova Sonic model, which led to a featured appearance on the AWS Twitch livestream \"Let\'s Build a Startup,\" bringing the technology to the startup community. Continued to serve as a specialist advisor through the ML/AI Technical Field Community, completing the Agentic AI pathway to bring agentic-specific customer workloads into scope. Mentored teammates on Generative AI through informal knowledge-sharing sessions.
EDUCATION
University of Glasgow
MSci, Computing Science
University of Glasgow
Doctor of Philosophy (Ph.D.), Computing Science
ABOUT COLIN WILKIE MCLELLAN
My work sits at the intersection of deep technical knowledge and practical delivery. I hold a PhD in Computing Science, where I specialised in retrieval bias in information retrieval algorithms, including experimentation with language models and semantic search, and I have spent the years since ensuring that academic depth translates into production systems that solve real problems for real customers.At Siemens Mobility, I built the engineering foundation: scalable data pipelines, optimised SQL, deployment automation, code quality standards, and resilient infrastructure for the UK data team. It sharpened the cloud and software engineering skills that my research background alone would not have given me, and it taught me that rigorous engineering discipline matters as much as theoretical elegance.At AWS, I became the team\'s go-to expert on data analytics, machine learning, and AI, supporting account teams and customers globally across multiple industries. I built demos and proof-of-concept systems to show customers what was achievable, but I also operated routinely as a Forward Deployed Engineer - embedded directly in customer accounts, working alongside their engineers to bring production workloads to life. Early projects centred on data pipelines using AWS pre-trained ML services such as Comprehend and Textract, which naturally gave way to Generative AI workloads as the landscape shifted. I was regularly implementing at the cutting edge, working with services like Bedrock, AgentCore, Nova Sonic, and Titan Multimodal Embeddings before their general release.I am intensely driven by working directly with customers and using my expertise to guide them to the right solution. I am a firm believer in helping build the right thing, not just the cool tech thing.
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