[Hiring] Senior Applied AI Research Engineer @Accesa

Role 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.

• 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

• 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.

Requirements

• 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).

Benefits

• Enjoy our holistic benefits program that covers the four pillars that we believe come together to support our wellbeing, covering social, physical, emotional wellbeing, as well as work-life fusion.
• Physical Wellbeing: Our wellbeing program includes medical benefits, gym support, and personalised fitness options for an active lifestyle, complemented by team events and the Healthy Habits Club.
• Work-Life Fusion: In very dynamic industries such as IT, the line between our professional and personal lives can quickly become blurred. Having a one-size-fits-one approach gives us the flexibility to define the work-life dynamic that works for us.
• Emotional Wellbeing: We believe that to maintain our overall health, we need to invest in our mental wellbeing just as much as we do in our physical health, social connections or in achieving work-life balance.
• Social Wellbeing: As a growing community in a hybrid environment, we want to ensure we remain connected not just by the great work we do every day but through our passions and interests.