Artificial Intelligence Engineer

Senior AI Application Developer / Integration Engineer

About the Role

• A Senior AI Application Developer / Integration Engineer is required to support the ongoing development and integration of an AI Assisted Validator solution within an established enterprise environment.
• The role focuses on accelerating delivery through parallel development streams, contributing to existing architecture, integration, testing, and enhancement activities.
• The successful candidate will combine strong application development and enterprise integration expertise with practical experience in AI-assisted and agentic application development.
• Rapid onboarding into existing IT processes and architecture is essential.

Contract Details

• Contract Type: B2B contract only (candidates operating through their own s.r.o.)
• Start Date: 01.10.2026
• End Date: 18.12.2026
• Work Setup: Hybrid
• Location: Prague

Key Responsibilities

• The position involves onboarding into the existing AI Assisted Validator solution , enterprise architecture, development processes, and IT environment.
• Responsibilities include developing and integrating AI Assisted Validator capabilities , enhancing agentic validation workflows, and implementing validation logic using contextual enrichment, application data, rules, and AI-driven reasoning.
• The consultant will contribute to Technical Assessment (TA) and Security Assessment (SA) checks, develop rule repository and rule-authoring functionality, and support observability and explainability initiatives to improve transparency of validation outcomes.
• Additional responsibilities include developing integrations between the Validator, portal applications, enterprise data sources, APIs, and supporting systems, as well as building automated testing and evaluation capabilities.
• The role also includes supporting UAT, investigating defects and unexpected AI behaviour, implementing improvements, producing technical documentation, and collaborating with developers, architects, security specialists, ISQ engineers, and project stakeholders.

Project Scope & Deliverables

• The project covers the development and enhancement of selected AI Assisted Validator capabilities.
• Deliverables may include contributions to:
• Agentic validation engine
• Enrichment-backed validation capabilities
• Technical Assessment checks
• Security Assessment checks
• Complex and tool-assisted validation workflows
• Automated testing and evaluation capabilities
• Rule repository and rule-authoring functionality
• Observability and explainability features
• Large-document validation
• Feedback-learning and dynamic rule-improvement mechanisms
• Portal and supporting system integrations
• The expected work result is the successful delivery of assigned tasks.

Required Experience and Skills

• Expert-level experience in Artificial Intelligence.
• Strong hands-on software engineering experience building and maintaining enterprise applications and services.
• Strong Python and backend development skills, including APIs, backend services, automation, and integration components.
• Practical experience integrating LLMs into applications , including prompt design, structured outputs, context management, and AI-assisted workflows.
• Understanding of agentic AI workflows, tool interaction, multi-step processing, and orchestration of AI-driven application logic.
• Strong enterprise integration experience covering REST APIs , authentication and authorisation , application-to-application integration, external data sources, and enterprise systems.
• Experience implementing configurable validation logic, rules, decision workflows, or similar business logic solutions.
• Experience with automated testing, integration testing, debugging, troubleshooting, and root-cause analysis.
• Knowledge of Git-based development, code reviews, CI/CD practices, maintainable coding standards, documentation, and software development lifecycle processes.
• Ability to quickly understand an existing architecture and codebase and contribute effectively with minimal ramp-up time.
• Ability to independently own development components through implementation, integration, testing, and handover.

Nice to Have

• Experience developing enterprise GenAI or AI-assisted applications.
• Experience with agentic AI frameworks or orchestration patterns.
• Experience with RAG, contextual enrichment, document processing, or retrieval-based AI applications.
• Experience implementing AI evaluation, observability, or explainability capabilities.
• Experience with configurable rule engines or rule-authoring solutions.
• Experience integrating applications into complex enterprise environments.
• Familiarity with application security, Technical Assessment, Security Assessment, or similar governance processes.
• Experience working within ELM architecture and related development processes.