Company Description Company Description  Accesa is a leading technology company headquartered in Cluj-Napoca, with offices in Oradea and 20 years of experience in turning business challenges into opportunities and growth. A value-driven organisation, it has established itself as a partner of choice for major brands in Retail, Manufacturing, Finance, and Banking. It covers the complete digital evolution journey of its customers, from ideation and requirements setup to software development and managed services solutions.
With more than 1,200 IT professionals, Accesa also has a fast-growing footprint, establishing itself as an employer of choice for IT professionals who are passionate about problem-solving through technology. Coming together in strong tech teams with a customer-centric approach, they enable businesses to grow, delivering value for our clients, partners, industry, and community. Job Description The Applied AI Research Engineer joins our internal applied R&D team, whose mission is to define how AI changes the way software is designed, developed, tested, deployed, and operated across the organization.
Rather than academic research or model training, the role centers on hands-on experimentation with emerging AI technologies - agents, LLM integration, evaluation techniques, AI-assisted development - and converting those learnings into the practical engineering standards (the AI SDLC) adopted by our delivery teams.  Because the role's output becomes engineering standards adopted across the organization, it calls for the judgment of an experienced engineer — typically 6+ years of production software delivery as a Senior Engineer or Tech Lead .
Responsibilities    Explore emerging AI technologies and engineering patterns through hands-on experimentation and rapid prototyping Formulate hypotheses, structure experiments, evaluate results against defined criteria, and convert findings into concrete engineering recommendations Contribute to the definition and continuous evolution of the organization-wide AI SDLC Critically assess AI technologies, model outputs, and industry trends; define evaluation criteria and identify failure modes before recommending broader adoption Produce clear documentation, reusable guidance, and recommendations for delivery teams and leadership Move fluidly between research, prototyping, engineering, architecture discussions, consulting, and organizational enablement Collaborate with the delivery-facing AI rollout function in a continuous feedback loop, incorporating recurring challenges and patterns discovered in real project adoption Qualifications Must Have Strong software engineering and architecture fundamentals as a Senior Engineer or Tech Lead: APIs, distributed systems, testing, delivery practices, and maintainability, transferable across languages and technology stacks Hands-on experience with AI agents and agentic workflows Experience with LLM APIs and model integration Practical experience with evaluation and testing of AI systems Awareness of security, privacy, and responsible AI considerations Experience with CI/CD and software delivery practices Experience with observability and monitoring Strong R&D mindset: comfortable operating where established answers do not yet exist, creating structure from ambiguity Critical thinking; systems thinking; strong written and verbal communication; pragmatism balancing experimentation with production realities Nice to Have LLM-based application development Retrieval-Augmented Generation (RAG) Tool/function calling and protocols such as MCP API design and integration Data pipelines and data management Containers and cloud-native development Experience with Python, JavaScript/TypeScript, Java, .NET, or similar (specific languages are not a primary selection criterion) As a people-first organisation, we believe diversity strengthens our teams and drives innovation.
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