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AWS Cloud Engineering + AI Consulting for Boston’s Life Science, Biotech, Insurance & Financial Services Companies

I help regulated Boston-area companies combine solid cloud infrastructure with practical AI automation – without the compliance blind spots that generic AI consultants miss, and without the bloated enterprise platforms that most cloud shops default to.

Why This Combination, Specifically

Most AI consultants don’t have real cloud infrastructure experience. Most cloud engineers don’t have hands-on experience deploying AI at enterprise scale inside a regulated environment. I’ve spent my career doing both:

  • AWS Cloud Engineering – architecture, cost optimization, cross-account secrets and encryption management, DevOps automation, and managed services, built for companies that can’t afford to get infrastructure wrong.
  • Enterprise AI deployment, hands-on – I currently apply Claude and AI-assisted automation at enterprise scale inside a financial services environment, building real automation for real teams, inside a company that takes data governance and security seriously by necessity.

That combination is exactly what life science, biotech, insurance, and financial services companies in Boston actually need: someone who understands both the cloud infrastructure their systems run on and how to deploy AI responsibly on top of it, in an industry where “just wire up an AI tool” isn’t a safe answer.

This site itself runs on that combination – AWS Lightsail infrastructure I configured directly, with AI-built tools (like the CRM below) running on top of it.

The Core-First approach

Early in my career, I worked as a Siebel CRM developer – one of the most powerful enterprise CRMs ever built. I watched clients pay enormous licensing fees for platform depth they used maybe 10-30% of. That’s the same lesson behind how I work now: build the lean, compliant core a business actually needs first – whether that’s cloud infrastructure or an AI workflow – and add capability only when there’s a real, specific reason to.

Services

AWS Cloud Engineering

  • Cloud Architecture – scalable, reliable, cost-effective AWS infrastructure design
  • Cost Optimization – reduce spend, eliminate waste, right-size your environment
  • Security & Compliance – cross-account secrets management, encryption/decryption (AWS KMS), and vault migration & management to keep credentials and sensitive data secure across environments
  • DevOps & Automation – faster, safer deployments and continuous integration
  • Managed Services – ongoing monitoring, maintenance, and support

AI Consulting & Automation

  • AI Workflow Consulting – mapping where AI can safely and practically save your team time, with a clear eye toward compliance and data handling from day one
  • Custom Tool & Automation Builds – lean, purpose-built tools and internal automations (not off-the-shelf platforms charging for features you’ll never use)
  • AI Literacy Workshops – practical, hands-on sessions for teams who need to actually understand what AI can and can’t safely do in a regulated environment
  • Ongoing 1:1 Consulting – implementation support and iteration as your needs evolve

Where they intersect

For life science, biotech, insurance, and financial services companies specifically, the real value is in the overlap: AI automation that’s built on properly architected, compliant cloud infrastructure from the start – not bolted on afterward by a consultant who only knows one side of the stack.

See It In Action

I document real builds, not case studies written after the fact.

AI Consulting:

AWS Cloud Engineering:

Read more build logs →

Common Questions

Do you work with companies that have strict security and data-handling requirements?
Yes – that’s specifically who this combined offering is built for. Cross-account secrets management, encryption, and vault-based credential handling are built into the infrastructure from day one, not retrofitted later.

Can AI automation actually be used safely in regulated industries like insurance or financial services?
Yes, with the right approach. The key is treating AI deployment as an infrastructure and governance question, not just a tooling question – which is exactly the gap this combined AWS + AI background is meant to close.

Do you only work with large enterprises?
No. The approach works for companies of any size in these industries – the same “build the compliant core first” principle applies whether you’re a small biotech startup or an established insurance firm.

Are you only available in Boston?
Boston and the surrounding area is where I’m based and where I run in-person workshops, but consulting and project work are available remotely as well.

Need cloud infrastructure and AI automation that actually work together?

If you’re in life science, biotech, insurance, or financial services in the Boston area and looking for someone who understands both the infrastructure and the AI — not just one or the other — let’s talk by book a free 15-minute call with me using Calendly below.