Consulting

Focused engineering delivery and architecture advisory

For small and lower-mid-sized projects, I can architect and deliver a product or enhancement end to end using Python, React, and AWS. For medium and large applications, I work with engineering leaders as an architecture and technical-risk advisor rather than taking ownership of the entire implementation.

I also help teams adopt AI-assisted development and design focused LLM-powered agent capabilities.

Who this is for

• A business with a defined, focused software problem that needs architecture and direct implementation
• A CTO or engineering leader responsible for a medium or large application with an important architecture, modernization, reliability, or scaling challenge
• An engineering team introducing AI-assisted development and needing an operating model that preserves testing, review, and accountability
• A product team building an LLM-powered agent that needs more than prompt experimentation

Problems I take on

• A business requirement with no existing software solution that needs pragmatic architecture and a cost-conscious path to its first production release
• A small or lower-mid-sized product that needs end-to-end backend, frontend, cloud, or integration delivery
• An existing focused product that needs a substantial enhancement across Python, React, and AWS
• A medium or large application facing architecture risks around service boundaries, data, authorization, integrations, reliability, scalability, or cloud cost
• An outdated or constrained system that needs a modernization sequence without an expensive big-bang rewrite
• A consequential architecture decision that needs independent analysis, documented trade-offs, and a practical mitigation plan
• An engineering team adopting AI-assisted development and needing workflows, codebase context, guardrails, testing, review, and human accountability
• An AI-agent capability that needs deliberate engineering across LLM APIs, context, retrieval, tools, state, evaluation, security, and provider boundaries

Ways I can help

Focused delivery

For small and lower-mid-sized projects, we define the business outcome, delivery boundaries, architecture, and milestones. I can then lead or perform the implementation from the first technical decision through a working release.

• Solution architecture and milestone planning
• Python backend and API development
• React frontend development
• AWS infrastructure and deployment
• Data models, integrations, testing, and delivery

Architecture advisory

For medium and large applications, the engagement begins with a focused two-week technical assessment. I work with your engineering counterpart to identify the constraint, evaluate trade-offs, document recommendations, and reduce risk around the most consequential decisions. The work can continue as an 8–12 week advisory partnership or a monthly retainer.

• Architecture and design review
• Technical-risk assessment and mitigation planning
• Modernization sequencing
• Identity, authorization, integration, and service-boundary decisions
• Targeted prototypes or implementation spikes
• Recurring architecture review

AI transformation and agent engineering

I help teams introduce AI-assisted engineering into their existing delivery process and design LLM-powered product capabilities. AI supports the work; engineering ownership remains with the team.

Situations

• Introducing AI-assisted implementation, testing, review, and technical analysis into an existing team
• Using AI to expand architectural analysis while keeping decisions traceable and human-owned
• Deciding whether a focused LLM workflow or an agent is justified
• Designing context, retrieval, tool, state, security, and failure boundaries for an agent workflow

What I can deliver

• An AI-assisted engineering workflow and guardrail assessment
• A practical team-adoption roadmap
• AI-agent architecture and workflow design
• A focused LlamaIndex prototype or implementation
• Evaluation scenarios, provider boundaries, and production-readiness recommendations

What I do not include by default

• End-to-end implementation ownership for an entire medium or large application
• General staff augmentation without a defined technical problem
• Replacing the client’s engineering leadership or delivery team
• 24/7 production operations unless scoped separately
• Business outcomes or delivery dates before the system and constraints have been assessed

A good fit

For focused delivery, you can define the business outcome and accept milestone-based scope decisions. For architecture advisory, you have an engineering counterpart who can provide system context and own implementation with the team. For AI work, you are willing to treat evaluation, review, security, and failure handling as part of the engineering.

The named client case studies are employment work at Brain Station 23; FinMind AI is an independent product. A consulting engagement is a separate agreement with you.