JK
Jordan K.
Senior AI-Native Full-Stack Engineer
Ships production agentic workflows end-to-end. Specializes in RAG-backed internal tools and Anthropic SDK integrations.
- TypeScript
- React
- Next.js
- AWS
- Claude Code
- RAG pipelines
AI-Native Staff Augmentation — shipping with agentic workflows
Meta.Dev embeds vetted, AI-native engineers into your team — engineers who build with AI agents, RAG pipelines, and agentic workflows as standard practice. Onboarded in 7 days, shipping from day one.
250+
AI-Native Engineers
7 days
Avg. Onboarding Time
40+
Client Engagements
What we doSee all services
Three ways to embed AI-native engineering
Embedded Engineers
Drop a vetted AI-native engineer into your team in 7 days.
Project Pods
A complete delivery pod for a defined scope.
AI Discovery Sprints
Two weeks to scope, prototype, and de-risk an agentic workflow.
AI-Native Tech Stack
The Technologies Our Engineers Ship With
Meta.Dev engineers are proficient across the full AI and full-stack development stack — LLM integration, agent frameworks, RAG pipelines, and production delivery. Every engineer is vetted for hands-on, production-level experience with agentic workflows.
Blockchain
Platforms
Specialized Blockchain Infrastructure
Ethereum
Polygon
Solana
BNB Chain
Avalanche
Cosmos
Polkadot
Near Protocol
Arbitrum
Optimism
AI & Machine
Learning
AI Agents, LLMs & Agentic Workflows
OpenAI GPT
Claude
Meta
LangChain
Auto GPT
TensorFlow
PyTorch
Vector Databases
RAG Systems
Agent Orchestration Platforms
Development
Frameworks
Shipping Production AI Applications
Hardhat
Truffle Suite
Cloud Foundry
Web3.js
Ethers.js
React
Next.js
Node.js
Python
Rust
Go
TypeScript
Meet the engineers
AI-native talent, ready to embed
A glimpse of the pool. Every engineer is vetted for production depth and ships with Claude Code, Cursor, and agentic workflows as standard practice.
LM
Lucas M.
Staff AI-Native Full-Stack Engineer
Architects agentic systems. Strong on workflow orchestration and reliability for long-running LLM pipelines.
- TypeScript
- Next.js
- Go
- Temporal
- MCP
- Claude Code
MR
Maya R.
AI-Native Backend Engineer
Builds retrieval pipelines and agent runtimes. Deep on vector stores and embedding workflows.
- Python
- FastAPI
- PostgreSQL
- Pinecone
- LangGraph
RA
Ravi A.
Senior Web3 Engineer
Ships production Solidity contracts and the AI-assisted tooling around them. Comfortable with audits and gas optimization.
- Solidity
- Hardhat
- Ethers.js
- TypeScript
- React
- Anthropic SDK
RD
Rohan D.
Senior AI-Native Project Manager
Embeds in client teams, runs the rituals, surfaces risk early. Has shipped 6+ AI-Native projects.
- Linear
- Notion
- GitHub Actions
ST
Sam T.
AI-Native QA Engineer
Writes E2E suites that hold up. Comfortable testing non-deterministic LLM output with golden-set fixtures.
- Playwright
- TypeScript
- GitHub Actions
How It Works
AI-Native. Embedded and shipping in days.
Every Meta.Dev engineer is AI-native — trained to work with agentic workflows, not just write code. We match you with a vetted engineer, handle onboarding, and have them shipping inside your team — typically within a week.
Scoping Call
- 30-Minute Session
- Define Role & Tech Stack
- Identify Best-Fit Engineers
Engineer Matching
- Vetted for AI-Native & Agentic Skills
- Live AI & Agentic Workflow Assessment
- Flexible Coverage Across Your Working Hours
Onboarding & Integration
- Onboarded Within One Week
- Tools, Access & Workflow Setup
- Shipping From Day One
Ongoing Performance
- Dedicated AI Delivery Manager
- Weekly AI Delivery Check-ins
- Scale Your AI Team as Needed
Discovery
Call
- Priority Scheduling
- Deep Dive into Requirements
- Strategic Talent Mapping
Engineer Matching
- AI-Powered Priority Selection
- Rigorous Technical Screening
- Cultural Fit Assessment
Onboarding & Integration
- Rapid Onboarding Process
- Dedicated Project Kickoff
- Effortless Integration
Ongoing Performance
- Exclusive Project Management Oversight
- Continuous Performance Monitoring
- Adaptive Scaling
LATEST
Insights & Case Studies
What we're writing and shipping
INSIGHTS
Testing non-deterministic LLM output without losing your mind
Traditional assert-equals testing falls apart when the output is a paragraph the model wrote. Here's the pattern that actually scales.
Jun 19, 2026 · Meta.Dev
CASE STUDY
Riverbend Bank
Built a compliance-review assistant in 6 weeks that triaged 89% of communications automatically; the remaining 11% routed to humans with model-generated rationale.
Jun 8, 2026 · Enterprise / regional bank
Hire from Meta.Dev
Ready to ship faster?
Stop waiting 3 months to hire. Meta.Dev embeds a vetted, AI-native engineer into your team — onboarded in 7 days and shipping with agentic workflows from day one.