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Jobs / Digitain / Lead AI Automation Engineer
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Posted 2026-08-25

Lead AI Automation Engineer

Description

Digitain is seeking a highly skilled and strategic Lead AI Automation Engineer to drive the next generation of intelligent process automation across its enterprise ecosystem. In this role, the engineer will lead the architecture, development, and scaling of end-to-end AI workflows, combining advanced web scraping, entity matching, Natural Language Processing, and Retrieval-Augmented Generation systems to transform unstructured data into actionable business intelligence.

As a technical lead, the individual will bridge domain-specific operational needs with cutting-edge AI architectures. The role involves setting engineering standards for data extraction and automated decision-making pipelines, mentoring team members, and ensuring high reliability for mission-critical automations.

Responsibilities
  • Architect Intelligent Automations: Design and deploy resilient, end-to-end automated pipelines that integrate Large Language Models, RAG architecture, and custom AI tools with core enterprise systems.
  • Data Scraping & Ingestion at Scale: Lead the strategy for large-scale web scraping, API extraction, and document processing, ensuring robust handling of anti-bot protections, changing schemas, and dynamic Web environments.
  • Intelligent Data Matching & Entity Resolution: Build sophisticated algorithms and semantic search solutions to perform high-accuracy data matching, deduplication, and record linkage across disparate datasets.
  • RAG & Knowledge Retrieval: Design, evaluate, and optimize Retrieval-Augmented Generation frameworks to ground LLM responses in proprietary databases, knowledge bases, and live web data.
  • Unstructured Text & Document Processing: Implement custom NLP pipelines to automate complex decision-making and report generation.
  • System Reliability & Monitoring: Establish best practices for exception handling, error recovery, LLM output validation, and latency optimization across all automated workflows.
  • Mentorship & Team Standards: Guide and mentor AI automation specialists, conduct code reviews, and establish standard operating procedures for workflow documentation, API management, and prompt engineering.
  • Stakeholder Alignment: Collaborate with cross-functional leadership to identify high-value automation opportunities, map technical feasibility, and demonstrate ROI.
Requirements
  • 5+ years of total experience in software engineering, data engineering, or process automation, with at least 2–3 years hands-on experience building AI/LLM-powered automation systems (required)
  • Proven track record of leading complex automation projects involving unstructured data, web scraping, and NLP (required)
  • Advanced proficiency in Python (Pandas, Asyncio, Playwright, Selenium, BeautifulSoup, Scrapy, FastHTML/FastAPI) (required)
  • Deep expertise with LangChain, LlamaIndex, OpenAI API, Anthropic, Hugging Face, vector stores (e.g., Qdrant, Chroma, Pinecone, FAISS), and fine-tuning/prompting techniques (required)
  • Solid understanding of fuzzy matching, BM25, semantic search, vector embeddings, and probabilistic record linkage strategies (required)
  • Hands-on experience scaling headless browsers, managing proxy networks, solving CAPTCHAs, and working with complex web scraping frameworks (required)
  • Mastery of workflow automation tools and orchestrators (e.g., Apache Airflow, Prefect, n8n, Make, or temporal workflows) (required)
  • Strong architectural mindset with an obsession for error handling, data accuracy, and pipeline resilience (required)
  • Excellent communication skills to explain AI limitations, confidence scores, and strategic value to non-technical stakeholders (required)
  • Resourceful problem-solver capable of building workarounds for unstable APIs or challenging scraping targets (required)
  • Experience in high-volume, dynamic industries such as iGaming, FinTech, or E-commerce (required)
  • Familiarity with database technologies (SQL, ClickHouse, Redis, document databases) and message brokers (RabbitMQ, Kafka) (required)
  • Exposure to MLOps, LLM monitoring tools (e.g., LangSmith, Phoenix), and CI/CD for automation workflows (required)
About Digitain

Digitain is a business-to-business provider of sportsbook and iGaming platform software, headquartered in Yerevan, Armenia. Founded in 1999, it offers a turnkey and standalone platform spanning sports betting, online and live casino, and games, alongside managed services for operators across regulated and emerging markets. Its portfolio includes the Imagine Live live-casino studios and the Galaxsys games studio, and the group employs a large engineering and operations workforce.

Read more about Digitain →

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