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Claude & LLM Engineer
Hire engineers specialized in building production LLM applications using Anthropic Claude, OpenAI, and open-source models, from prompt architecture to fine-tuning.
Role Overview
Available in 48 to 72 HoursLLM engineering requires rigorous prompt architecture, context window management, latency control, cost tracking, and output validation. Our engineers have deployed production applications on Anthropic Claude, OpenAI, Gemini, and open-source foundation models, implementing structured outputs, tool use, and custom evaluation harnesses.
What You Receive
- Production LLM integration with schema validation and error fallbacks
- Version-controlled prompt repository with evaluation logs
- Automated benchmark dataset for regression and hallucination testing
- Token cost projections and model selection tradeoff analysis
- Fine-tuning datasets, training scripts, and serving deployment files
Technologies & Supported Stacks
Anthropic Claude 3.5 / 4 APIsOpenAI GPT-4o / o3Google Gemini 2.0 FlashLlama 3.3 / Mistral / Qwen (open-source)LangChain / LlamaIndex / InstructorHugging Face Transformers / PEFT / TRLvLLM / Ollama / SGLangLangSmith / W&B Weave / Helicone
Engagement Process
Step 01
Requirements & Model Selection
We evaluate task complexity, latency requirements, data sensitivity, and cost constraints to select the optimal foundation model.
Step 02
Prompt Architecture
We design and iterate prompt templates, system instructions, few-shot examples, and chain-of-thought reasoning structures.
Step 03
Integration & Evaluation
We integrate the LLM into your application stack and run evaluation benchmarks to measure accuracy, hallucination rate, and latency.
Step 04
Production Monitoring & Optimization
We configure inference observability, establish token cost alerts, and implement caching & routing to optimize production costs.
Business Benefits
- Model choices grounded in concrete latency, accuracy, and cost data
- Strict schema validation preventing malformed LLM responses from breaking UI
- Automated test suites catching prompt regressions before production rollout
- Private model fine-tuning to protect confidential internal data
Ideal For
- Document intelligence, data extraction, and entity classification
- Domain-specific conversational assistants with strict factual boundaries
- Internal code generation and documentation search copilots
- Domain-specialized small models for low-latency batch processing
TALENT ON DEMAND
Hire a Senior Claude & LLM Engineer in 48 Hours
Pre-vetted, senior engineers embedded directly into your team. Flexible engagement models with zero overhead.