Pre-Vetted Machine Learning Talent

Hire Dedicated AI, LLM & Machine Learning Engineers

Scale your engineering squad with senior AI engineers specialized in enterprise RAG pipelines, LangGraph multi-agent systems, vLLM private deployments, and semantic search. Day-1 100% IP ownership with seamless sprint integration.

Hire AI Engineers Now Review Vetting Process ↓

Candidate Vetting Standard

Our 4-Stage AI Engineering Technical Gate

Only the top 2% of AI and machine learning applicants successfully clear our production assessment pipeline.

Stage 01

Python Async & Vector Math

Rigorous screening on asyncio event loops, PyTorch tensor manipulation, matrix cosine similarity calculations, and memory optimization.

Stage 02

Timed RAG Coding Challenge

Candidates build an end-to-end hybrid search pipeline under time pressure: semantic AST chunking, pgvector indexing, and cross-encoder reranking.

Stage 03

Adversarial Defense & Evals

Testing defense against indirect prompt injections, jailbreaks, PII leakage, and building automated regression eval suites with Ragas.

Stage 04

Architectural Defense

Live technical defense with our Principal AI Architects on token budgeting, vLLM quantized deployment, and human-in-the-loop agent graphs.

Role Profiles

AI Engineering Roles & Seniority Matrix

Deploy individual senior specialists or complete cross-functional AI squads configured for your roadmap.

ROLE 1

Senior AI Application Engineer

Focuses on enterprise application integration: FastAPI backends, LangChain/LlamaIndex pipelines, pgvector search, and streaming React/Livewire frontends.

  • ✓ 4+ years production Python experience
  • ✓ Custom RAG pipelines & hybrid search
  • ✓ Pydantic v2 structured JSON validation
ROLE 2

Agent Systems & LangGraph Architect

Specializes in cyclic state machines, multi-agent tool execution, persistent checkpointing, and human-in-the-loop operational authorization.

  • ✓ LangGraph & CrewAI production graph design
  • ✓ Strict tool execution sandboxing & timeouts
  • ✓ State checkpoint persistence with PostgreSQL
ROLE 3

MLOps & Private Inference Engineer

Engineers self-hosted inference clusters: vLLM engine optimization, quantized model serving (AWQ/GPTQ), LoRA fine-tuning, and GPU cluster scaling.

  • ✓ vLLM, TensorRT-LLM & Ray Serve on AWS/GCP
  • ✓ LoRA parameter-efficient fine-tuning
  • ✓ Prometheus token latency & GPU VRAM monitoring

Team Integration

How Your Dedicated AI Engineer Works Daily

Zero friction integration into your existing Git, sprint, and communication tooling.

Daily Standups & Live Chat

Your engineer joins your Slack, Discord, or Microsoft Teams. They participate in daily morning standups, sprint planning, and asynchronous status updates.

Direct GitHub / GitLab Commits

Code is pushed directly to your private repositories under feature branch workflows. Pull requests include automated test coverage and prompt eval benchmarks.

Token Telemetry & Observability

Every pipeline features end-to-end tracing in LangSmith or Langfuse, giving you real-time visibility into token costs, execution latency, and error rates.

Simple & Transparent

Dedicated AI Engineering Rates

Full-time dedicated senior engineers. No hidden agency markups, zero recruitment fees, and a 2-week risk-free trial.

Senior AI Engineer

Dedicated full-time engineer specialized in RAG, FastAPI, and vector databases.

$3,400 / month
₹2,40,000 / month (India)
  • ✓ 160 hours / month dedicated
  • ✓ LangChain, LlamaIndex, pgvector
  • ✓ Full-shift local timezone alignment
  • ✓ 2-Week risk-free trial
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MOST POPULAR

Lead AI Architect

Senior architectural lead for multi-agent systems, private vLLM clusters, and MLOps.

$4,800 / month
₹3,40,000 / month (India)
  • ✓ Multi-agent LangGraph orchestration
  • ✓ Private GPU model serving & vLLM
  • ✓ Custom LoRA fine-tuning pipelines
  • ✓ Daily standups & sprint leadership
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Custom AI Pod

Cross-functional squad with Lead AI Architect, Full-Stack Engineer, and QA specialist.

$9,500 / month
₹6,80,000 / month (India)
  • ✓ Complete turnkey AI engineering squad
  • ✓ Frontend streaming UI + backend APIs
  • ✓ Dedicated Project Manager & QA
  • ✓ Bi-weekly delivery milestones
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Hiring FAQs

Hiring AI Engineers: Questions & Answers

Every AI engineer passes our rigorous 4-stage evaluation: 1) Advanced Python asynchronous programming and vector math screening, 2) A timed 3-hour live coding test implementing hybrid RAG with pgvector and cross-encoder reranking, 3) An adversarial prompt injection and guardrail defense challenge, and 4) A live architectural defense evaluating token budget management and latency trade-offs.
Your dedicated engineer works strictly within your tools. They attend your daily standups in Slack or Microsoft Teams, pick tickets from your Jira or Linear sprint backlog, push code directly to your private GitHub/GitLab repositories, and attach Langfuse or LangSmith tracing reports to every pull request.
Yes. Our engineers specialize in private VPC deployments on AWS, GCP, or on-premise GPU clusters using vLLM, Ollama, and Hugging Face TGI. We implement zero-data-retention enterprise API configurations and enforce local embedding generation with self-hosted open-weights models (Llama 3, DeepSeek, Mistral) so client data never leaves your firewalled infrastructure.
We implement continuous automated eval pipelines using Ragas, DeepEval, and LangSmith. Before any prompt modification or retrieval index change is merged to production, the test suite scores faithfulness, answer relevancy, context precision, and hallucination frequency against a golden benchmark dataset.
We deploy matched senior AI engineers within 3 to 7 business days. We provide a 2-week risk-free trial period: you review their initial code commits, PR documentation, and sprint velocity. If the engineer does not exceed your expectations, you owe nothing or receive an immediate replacement.

Ready to Add Dedicated AI Engineers to Your Team?

Schedule a 30-minute discovery call with our technical recruiter and lead AI architect to review candidate profiles and start your 2-week trial.

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