Applied AI, Data & Automation Engineer | Careers

TYSAPA is looking for an Applied AI, Data & Automation Engineer to build the intelligence layer of its platforms and client solutions. This role is responsible for applying AI where it creates measurable value: extracting information from documents, classifying records, summarizing content, supporting decision-making, detecting anomalies, prioritizing tasks, and making workflows more efficient.

This is not a research-only role. The focus is practical implementation. The successful candidate should understand how to move from model or prototype to a controlled, explainable, human-reviewable workflow. The role requires strong Python/data skills, practical AI knowledge, and the ability to integrate AI outputs into software platforms.

Role & responsibilities

Build AI-assisted workflows for document extraction, classification, summarization, routing, prioritization, and decision support.
Develop pipelines for invoices, forms, contracts, meeting notes, records, reports, customer interactions, and operational documents.
Work with OCR, NLP, LLMs, embeddings, RAG, structured extraction, prediction models, anomaly detection, and analytics workflows.
Create data pipelines that transform unstructured or semi-structured information into usable records, dashboards, and workflow outputs.
Design validation loops, confidence scoring, human-in-the-loop review, exception handling, and quality checks.
Evaluate AI output for accuracy, reliability, usefulness, and operational risk.
Integrate AI and data services with backend systems, APIs, databases, dashboards, and workflow platforms.
Support predictive analytics, forecasting, operational prioritization, and decision intelligence use cases.
Document model assumptions, limitations, performance, data requirements, and governance needs.
Work with product and engineering teams to decide when AI is appropriate and when simpler rules or process logic are better.

Requirements

Strong Python skills and experience with data processing, AI, machine learning, NLP, LLMs, RAG, or automation.
Experience with OCR, document AI, text extraction, classification, summarization, embeddings, or structured information extraction.
Familiarity with APIs, databases, data pipelines, backend integration, and production workflows.
Understanding of model evaluation, validation, accuracy measurement, hallucination risk, confidence thresholds, and human review.
Ability to work with messy operational data and convert it into structured, useful outputs.
Experience with dashboards, forecasting, anomaly detection, decision support, or optimization is a strong advantage.
Familiarity with OpenAI APIs, local LLMs, vector databases, LangChain/LlamaIndex-style tools, or MLOps practices is useful.
Strong documentation skills and practical judgment about when AI should or should not be used.
MSc/PhD or strong applied experience in computer science, data science, engineering, physics, mathematics, AI, or a related field is preferred.

Benefits

Work on applied AI systems connected to real business operations.
Opportunity to combine AI, automation, analytics, document intelligence, and software delivery.
Build systems that support TYSAPA’s core philosophy: selective AI under guardrails.
Exposure to projects across finance workflows, document operations, dashboards, healthcare-adjacent analytics, field systems, and collaboration tools.
Growth path toward AI Lead, Data Lead, Automation Architect, or Decision Intelligence Specialist.
Work in a science-driven environment where quality, evidence, and practical impact matter.

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