Senior Artificial Intelligence/Machine Learning Engineer (3460)

Ciklum

Що робити

Agent Development: Design, build, and test production-grade extraction agents that map unstructured document language to a structured target schema, supporting multiple schema variants
Ingestion Engineering: Build a document ingestion pipeline robust to degraded inputs, including low-quality scans, multi-generation photocopies, mixed image and text PDFs, and inconsistent layouts
Confidence & Routing: Develop a per-field confidence model that drives routing, where high-confidence fields flow straight through and low-confidence fields land in the review queue
Knowledge Engineering: Build and configure RAG knowledge bases to provide agents with secure, domain-specific context, controlling grounding and hallucination on documents where a wrong value has real downstream consequences
Safety & Governance: Implement Human-in-the-Loop escalation interfaces, confidence thresholds, and egress controls, where reviewer corrections feed back as training signal

AWS & Bedrock: Deep AWS architecture experience with hands-on Bedrock work, including model selection, prompt and context engineering, evaluation, and cost and latency optimization in production
Document AI: Strong background in OCR on degraded inputs (Textract or equivalent), layout-aware extraction, and handling the gap between what OCR returns and what a schema needs
Structured Extraction: Demonstrated experience extracting structured data from long, unstructured documents into a fixed schema, including confidence estimation and calibration
Agentic Intelligence: Proven track record building multi-step reasoning chains, tool-use protocols, and state management for autonomous agents
Pipeline Engineering: Production RAG or LLM pipeline experience, including chunking, retrieval, and grounding

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