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Services

The work I do.

Not a capability matrix. These are the areas where experience genuinely changes the outcome, so they're the ones I take on.

AI product engineering

LLM features that hold up once strangers are using them. Retrieval, agents, and pipelines you can measure, debug, and keep running.

  • Python
  • TypeScript
  • OpenAI / Anthropic APIs
  • Vector databases
  • Evals & tracing

Sound familiar?

  • The demo was great. The version real users touch is not.
  • Retrieval returns answers that sound right and aren't
  • Your ingestion pipeline works until someone uploads a scanned fax
  • Cost or latency is the reason you haven't launched

What you get

  • Retrieval that cites its sources so answers can be checked
  • Ingestion and parsing that survives messy real-world files
  • Agentic workflows with guardrails around the parts that can go wrong
  • Evals and tracing, so quality is a number instead of a vibe

How I'd approach it

I start with the quality bar you need to hit and the data you actually have, then build the smallest thing that clears it. You get a straight answer early about what's feasible, and an eval harness that outlives the engagement — that's the part that keeps the system honest after I'm gone.

Full-stack product work

Features taken all the way: React on the front, typed APIs behind it, a data model that isn't fighting you. Including the unglamorous last 20%.

  • React
  • TypeScript
  • Node / Python
  • PostgreSQL
  • AWS

Sound familiar?

  • Three features are 80% done and none of them have shipped
  • Your schema made sense two pivots ago
  • Billing, auth, and integrations keep sliding to next sprint
  • The internal tool everyone needs that nobody has time to build

What you get

  • APIs and backend services
  • Postgres schema design and the migrations to get there
  • Auth, billing, and third-party integrations
  • Internal tooling, finished and in use

How I'd approach it

I take features from fuzzy idea to shipped, including the parts contractors usually hand back: edge cases, migrations, tests, and the week after launch when something turns out to be wrong. You keep control of priorities.

Architecture & modernization

For systems that outgrew their original shape. Making them faster and less fragile without betting the company on a rewrite.

  • Distributed systems
  • PostgreSQL / query optimization
  • AWS
  • Caching & queues
  • Observability

Sound familiar?

  • Every change to this service is scary
  • On-call is wearing your team down
  • A legacy codebase is blocking the thing you actually want to build
  • Something is slow and nobody owns finding out why

What you get

  • Profiling, then specific fixes with measured before-and-after
  • Legacy modernization done in increments that ship
  • Reliability work: retries, timeouts, backpressure, the boring wins
  • A debt inventory that's honest about what to ignore

How I'd approach it

Big-bang rewrites mostly fail, and they fail late. I find the changes with the best ratio of risk to payoff and sequence them so the system keeps serving traffic the whole way through. Your team gets the reasoning written down, which is the part that's usually missing.

Embedded engineering

A senior engineer in your standups who owns real work and pushes back in design reviews. Without a headcount req or three months of interviews.

  • Your stack
  • GitHub / GitLab workflows
  • Slack / Linear / Jira
  • Design & architecture reviews

Sound familiar?

  • Your team is underwater and the backlog keeps growing
  • A high-priority project has no owner
  • You want a second opinion before committing to an architecture
  • You need a strong engineer now, not after a hiring cycle

What you get

  • Full ownership of a project or workstream
  • A real voice in planning and design decisions
  • Code review and knowledge transfer to your engineers
  • High-priority work moving at a predictable pace

How I'd approach it

I work like a strong internal hire: in your tools, in your rituals, on the hook for outcomes. The difference is that you can start next week and stop when the work is done, and you don't spend management time on me.

Productized

SOC 2 technical readiness

A fixed-scope sprint that clears the engineering-side findings that surface in readiness reviews — access, logging, change management, backups — before your observation window opens.

Scoped and priced up front, unlike the work above. Starts with a paid diagnostic against your live environment; the remediation sprint is quoted from what it finds.

How the sprint works

Ways to work together.

Pricing depends on the shape of the work, so I quote it after we've talked rather than putting tiers on a page.

Monthly retainer

Ongoing capacity on whatever matters most that month. Priorities shift; I move with them.

Embedded on the team

Your Slack, your standups, your board. I own a workstream and argue about the roadmap like anyone else would.

Fixed project

A defined build with an agreed shape and an end date.

Discovery sprint

Two to three weeks to design a system or pressure-test an idea before you spend real money on it.

When I'm the wrong call.

Better to say this now than three emails in.

  • Marketing sites and template builds.
  • Staff augmentation priced by the seat.
  • Work that needs five developers starting at once.
  • Projects where nobody can make a decision.

None of that is snobbery — I'm only worth hiring where the experience actually moves something. If you're unsure which side of the line you're on, email me at keaton@bytecraftco.com and I'll tell you.

Got something difficult on your plate?

Tell me what you're working on and what's in the way. If I can help, I'll tell you how I'd approach it. If I can't, I'll say that instead of taking the meeting.

Get in touchkeaton@bytecraftco.com