PRODUCT & ENGINEERING TEAMS

Senior AI Engineers, Embedded in Your Team

Grayphite drops senior AI engineers straight into your existing product and engineering teams. We work inside your sprints, your codebase, and your tooling to add velocity and ship AI capability without the long ramp of a new hire.

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Overview

Extra Capacity With Real AI Depth

Most product and engineering teams have more roadmap than runway. Hiring takes months, AI specialists are scarce, and your existing engineers are already at capacity shipping the core product.

We embed senior engineers who think in your stack and work to your rhythm. They join standups, pick up tickets, open pull requests, and ship alongside your team, while also bringing the AI depth most teams do not have in-house.

The result is a team that moves faster and gains an AI capability it can keep building on long after our engagement ends.

Senior by Default

Every embedded engineer is senior and ships production code from week one.

Inside Your Workflow

We work in your repos, sprints, and tools, not in a separate silo.

AI Where You Lack It

We add the LLM, agent, and ML depth your team has not built yet.

Knowledge Stays

We document, pair, and hand off so capability remains after we leave.

Challenges

Team Bottlenecks, Quietly Solved

The friction points that slow product and engineering teams down, and how embedding senior AI engineers clears them.

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Hiring Is Too Slow

AI roles sit open for months while the roadmap stalls and competitors ship.

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No In-House AI Depth

Your engineers are strong, but few have shipped production LLM or agent systems.

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Core Team Is Maxed Out

Everyone is heads-down on the product, leaving no room for AI exploration.

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AI Prototypes Stall

Demos work, but nobody has the bandwidth to harden them into real features.

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Unclear AI Architecture

Teams pick the wrong models, patterns, and tooling and pay for it later.

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Rising AI Costs

Naive integrations burn tokens and budget without anyone owning optimization.

WHAT WE BUILD

Embedded Delivery, On Your Roadmap

Flexible ways to plug senior AI engineers into your team and ship the work that matters.

01

Embedded AI Engineers

Senior engineers join your team full or part time, working inside your sprints and codebase as if they were full-time hires.

02

AI Feature Delivery

We take an AI feature from concept to production, owning the model selection, integration, evaluation, and rollout end to end.

03

AI Workstream Offload

Hand us a complete AI initiative as a parallel track so your core team stays focused on the main product.

04

Prototype to Production

We turn working AI prototypes into reliable, observable, cost-aware features your users can depend on.

05

Capacity Augmentation

Add senior engineering throughput to clear backlog and meet deadlines without the overhead of permanent headcount.

06

Embedded AI Advisory

A senior engineer pairs with your team to shape AI architecture, review designs, and level up your people in the process.

Technology

The Stack We Bring To Your Team

We adapt to your existing stack and bring proven tooling for the AI layer.

Languages

TypeScriptPythonGoJavaRust

AI & LLM

OpenAIAnthropic ClaudeHugging FaceLangChainLlamaIndexVector databases

Frameworks

ReactNext.jsNode.jsFastAPISpring

Data & ML

PostgreSQLRedisSnowflakePyTorchPandas

Cloud & DevOps

AWSGCPAzureDockerKubernetesTerraform

Collaboration

GitHubGitLabJiraLinearSlack
Process

How We Work

A lightweight engagement model that gets engineers contributing quickly and integrates with how your team already operates.

01

Discovery & Fit

  • Goals and scope alignment
  • Stack and workflow review
  • Skill match for embedded engineers
02

Onboarding

  • Repo and environment access
  • Codebase and architecture walkthrough
  • Sprint and ceremony integration
  • First tickets assigned
03

Embedded Delivery

  • Pull requests in your repos
  • Daily standup participation
  • AI feature implementation
  • Code review and pairing
04

Scale & Adjust

  • Velocity and quality tracking
  • Capacity tuning up or down
  • Roadmap re-prioritization
05

Handoff & Continuity

  • Documentation and runbooks
  • Knowledge transfer sessions
  • Maintenance and support plan
  • Capability retained in-house
FAQ

Common questions, answered

How is this different from a typical staffing agency?+
We do not just place bodies. Every engineer is senior, AI-capable, and accountable for shipping production outcomes, not just filling a seat.
Do your engineers work inside our codebase and tools?+
Yes. They use your repos, sprint boards, CI, and chat tools, and follow your code standards and review process just like any team member.
Can we start with a single engineer?+
Absolutely. Many teams begin with one embedded engineer on a focused workstream and scale up once they see the impact.
How quickly can an engineer start contributing?+
Because our engineers are senior, most are opening meaningful pull requests within the first sprint after onboarding.
What if we need to scale the team up or down?+
Capacity is flexible. We adjust the number of embedded engineers as your roadmap and budget change, with clear notice periods.
Do you only work on AI features?+
No. While AI is our core depth, our engineers are full-stack and contribute across your product, from backend services to frontend work.

Let's talk about Product & Engineering Teams.

Grayphite embeds senior AI engineers alongside your product and engineering teams to add velocity, ship AI features, and offload complex AI workstreams.

Schedule a Discovery CallSee our work