Boundev AI
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Hire LLM engineers

Senior LLM engineering.
Output-priced, in your stack.

Production LLM work isn’t “add an API call.” It’s prompt engineering at scale, eval pipelines in CI, cost-aware provider routing, and the discipline to know when to fine-tune versus when to prompt better. Boundev is a senior LLM-engineering subscription: drop your task in Slack, we ship a clean GitHub PR with code, eval suite, telemetry hooks, and a deploy guide in 5–7 days.

OpenAI · Anthropic · OSS·Eval suite on every PR·First task free if > 7 days
40+
LLM features shipped to production
$3,500/mo
Pilot tier — one task
60%
Avg LLM cost cut on audit engagements
5.4 d
Median time to first PR
Where LLM work breaks in production

The gap between “GPT API call” and “production LLM feature” is huge.

Most LLM features ship without evals, without cost telemetry, without fallback routing. They work for a quarter, then break in expensive ways. Senior LLM engineering is the discipline to ship them right the first time.

01
Hiring an LLM engineer takes ~90 days
The talent pool is shallower than "AI engineer" overall. Senior production LLM experience is rare and expensive — $280K+ TC, multiple competing offers, long ramp.
02
Generic full-stack devs ship working LLM code with broken economics
It functions in the demo. In production, it's $40K/mo on tokens, no eval coverage, no fallback routing, no caching. Quality without cost discipline isn't shippable.
03
Eval pipelines almost never get built
Most teams ship LLM code with manual spot-check QA. Without an eval suite running on every PR, model drift and regression catch you in prod, not in CI.
04
Provider lock-in is the default
OpenAI-only stacks with no fallback are one rate limit away from a P1. Boundev integrations always include provider abstraction so swapping Claude / Gemini / OSS is a config change, not a rewrite.
What we ship

Eight LLM tasks we open PRs on every week.

OpenAI / Anthropic / Gemini / open-source. Production-grade with eval suite, cost telemetry, and provider abstraction folded in by default.

GPT
OpenAI integration
GPT-4, GPT-4o, structured outputs, function calling, streaming, retry / backoff, cost telemetry. Production-grade, with an eval harness.
↳ Onboarding assistant w/ 8K daily calls
ANT
Anthropic / Claude integration
Claude 3.5 / 3.7 with prompt caching, vision, tool use, fallback to OpenAI on provider outage, telemetry into Langfuse / Braintrust.
↳ Code-review copilot for DevTools customer
RAG
RAG pipelines on real docs
Chunking strategy, embedding model selection, hybrid search (BM25 + vector), grounded answers with citations and an eval suite.
↳ 12K-page legal archive · 40% faster support
MCP
MCP servers for your SaaS
Production Model Context Protocol servers — auth, rate limits, tool discovery, eval harness. Drops Claude into your product as a first-class action.
↳ In-product Claude assistant · DevTools
EVL
Eval pipelines in CI
LLM-as-judge + golden datasets aligned with real production traffic. Catches regressions on every PR, not in customer Slack.
↳ RAG eval suite blocking merges on regressions
$$$
Cost audit + optimization
Audit your LLM bill: prompt caching, smaller models for the 80% case, cheaper providers for the 20% case, fallback routing, batch jobs.
↳ $48K/mo → $19K/mo · 60% cost cut
AGT
Agentic workflows
Multi-step agents with tool use, planning, self-correction. Constrained scope, eval coverage, graceful failure modes — not LangChain demoware.
↳ Daily competitor research → Slack briefing
FT
Fine-tuning + distillation
When prompting plateaus: SFT, DPO, or distilling a smaller model from a frontier one. Includes eval suite + cost-vs-quality tradeoff analysis.
↳ GPT-4o → custom 8B · 90% cost cut, equal eval
How a task ships

3 steps. 7 days.
Production LLM code.

No briefs, no SOWs, no kickoff calls. Subscribe, drop your task in Slack, a senior LLM engineer ships it as a clean GitHub PR within the week.

See full process
01T+0 minutes
Talk to sales in 20 minutes

Book a scoping call. We confirm fit, recommend a tier, and reply with a written scope + provider strategy in 4 business hours — no payment to start.

02T+24 hours
Senior engineer in your Slack

Once you green-light scope, we Slack-invite you, assign a senior LLM engineer matched to your stack, and send the first-month invoice. Engineer is in your channel within 24 hours.

03T+5–7 days
Ship via GitHub PR

Senior LLM engineer + Cursor + Claude Code. Daily Slack updates. PR includes tests, eval suite, telemetry hooks, and a deploy guide.

Pricing

Three tiers. Cancel any month.

Output-priced. No setup fee, no hidden charges, no contract to redline. First task free if not shipped in 7 business days.

Pilot
$3,500/mo
One LLM task. First-time buyers.
  • ✓1 LLM task / month
  • ✓Async Slack
  • ✓GitHub PR + 1 revision
  • ✓Cancel anytime
Talk to sales · Pilot
POPULAR
Growth
$6,500/mo
Active SaaS teams shipping LLM features regularly.
  • ✓2–3 LLM tasks / month
  • ✓Daily Slack updates
  • ✓Unlimited revisions
  • ✓Eval suite on every task
Talk to sales · Growth
Scale
$12,000/mo
Series A+ with embedded LLM roadmap.
  • ✓Unlimited within capacity
  • ✓Dedicated LLM engineer
  • ✓Private Slack channel
  • ✓Weekly sync
Talk to sales · Scale
LLM-specific FAQ

What buyers ask before scoping their first LLM task.

Average 8+ years of engineering experience, with at least 2 years of production LLM work — not just GPT API calls, but production retrieval, evals, cost optimisation, prompt-engineering at scale, and provider abstraction. Background mix: ex-FAANG, ex-AI lab, deep SaaS. We hire for production AI judgement, not coding-test theatre.
Stop vetting. Start shipping.

Your next LLM feature, shipped this week.

Free 20-minute scoping call. We tell you if we're a fit, what tier you'd need, and how fast we can ship. We can also audit an existing LLM bill on the call if you bring rough usage numbers.

WHAT YOU GET
  • ✓Senior LLM engineer assigned in 2 hours
  • ✓GitHub PR shipped in 5–7 business days
  • ✓Eval suite + cost telemetry on every task
  • ✓Provider-agnostic by default (no lock-in)
  • ✓Full IP, code, prompts, and evals to your repo