Hire an AI Engineer who has shipped systems users actually use.
Most AI engineers build demos. Few have run a production AI system long enough to know what breaks at month six. Our AI bench includes engineers who built the AI engine behind Microvest's live Bitcoin investment platform and the LLM-embedded data pipelines inside Clust. The difference between a notebook and a production system is operational rigour — and that is what we hire for.
AI engineers who have survived month six in production.
Production track record in regulated fintech (Microvest) and platform-scale data infrastructure (Clust).
Strong on the unglamorous parts — eval harnesses, prompt versioning, output validation, cost monitoring, drift detection.
Pragmatic about tooling — OpenAI, Anthropic, open-source, self-hosted — picked per use case, not per vendor preference.
Comfortable building privacy-first AI architectures for clients with strong legal and infrastructure boundaries.
The depth our AI engineers bring to your team.
RAG & Retrieval
- Document ingestion / chunking
- Embedding model selection
- Hybrid search (vector + BM25)
- Re-ranking strategies
- Pinecone, Qdrant, Weaviate, pgvector
LLM Engineering
- Fine-tuning (LoRA / QLoRA)
- Prompt engineering & versioning
- Function-calling / tool use
- Multi-model routing
- Self-hosted deployments
Agents
- LangGraph / CrewAI
- Memory architectures
- Multi-agent coordination
- Tool integration
- Production-safe autonomy
MLOps
- Eval harnesses (LLM-as-judge)
- Cost monitoring
- Drift detection
- A/B testing prompts and models
- Output safety / content filtering
Classical ML
- Forecasting & time-series
- Anomaly detection
- Recommendation systems
- Feature engineering
- Model serving
Languages & Frameworks
- Python
- PyTorch / Transformers
- LangChain / LlamaIndex
- Hugging Face
- FastAPI / Triton serving
From request to engineer-on-keys, fast.
Brief Call
A 30-minute call to understand your stack, your problem, and the seniority you actually need (versus what the JD says).
Engineer Match
We propose 1–2 engineers from the bench who fit the brief — with portfolio links to real shipped work, not pitch slides.
Technical Interview
You interview the engineer directly. Pass or fail is your call. We re-match if needed at no cost.
Onboard
Engineer joins your team within 1 week of offer. Monthly retainer, no hidden fees, replacement guaranteed.
Production AI shipped to live users — not pilots, not demos.
Microvest AI Bitcoin engine. AlgoCoder built the AI engine behind Microvest's live Bitcoin investment platform — analyses real-time market data and sentiment signals to power data-backed investment intelligence inside the live custodian system.
Clust LLM-embedded data pipelines. Production-grade language models embedded directly into the data layer for classification, semantic enrichment, unstructured-to-structured conversion, and anomaly detection at platform volume — delivered inside the same operational discipline that runs our blockchain infrastructure.
- Microvest AI engine — analyses real-time Bitcoin market data and sentiment signals for data-backed investment intelligence.
- LLMs embedded directly inside Clust's production data pipelines for classification, semantic enrichment, and anomaly detection.
- Privacy-first AI architectures available for clients with strong data boundaries — self-hosted models, on-prem inference, encrypted pipelines.
- Production rigour — eval harnesses, prompt versioning, output validation, cost monitoring, drift detection treated as first-class engineering, not afterthoughts.