Senior Software Engineer (Data & AI)

About the role

foodpanda is looking for a Senior Software Engineer (Data & AI) to design, build and scale production AI applications and agentic systems that solve complex operational and analytical challenges across its footprint in APAC and Europe. The role focuses on agentic workflows, advanced RAG systems and intelligent automations, while also designing and maintaining the data pipelines that feed them. It sits within an agentic analytics platform initiative that connects AI agents with enterprise business logic, semantic layers and context engines.

Key responsibilities

• Design, build and maintain production AI applications, including agentic workflows, RAG systems and integrations with business knowledge, semantic layers and external tools.
• Build and maintain evaluations to measure the correctness, reliability and effectiveness of AI applications, using datasets, automated testing, observability and user feedback.
• Work closely with analytics and business teams to turn ambiguous problems into practical solutions, prototyping and validating ideas rapidly.
• Own the software end-to-end, from architecture and implementation to testing, deployment, monitoring and continuous improvement.
• Use modern tools, including AI coding agents, while keeping high standards for design, security and maintainability.
• Contribute to architecture decisions, RFCs, code reviews and pair programming, and mentor other engineers.
• Take responsibility for production reliability, including observability, incident investigation and performance optimization, and join the team's on-call rotation.
• Build and maintain ingestion, ETL/ELT and context-retrieval pipelines, owning their reliability, data freshness and incident response.

Required profile

• 7+ years of software engineering experience, with strong proficiency in Python, SQL, system design and automated testing.
• Experience developing LLM-powered applications, agentic workflows or related systems, and moving AI solutions from experimentation to production.
• Experience building evaluation datasets, frameworks or automated harnesses, or using observability tools such as Langfuse.
• Good judgment on how AI systems should behave, and awareness of emerging AI research, models and agent architectures.
• Comfortable working with stakeholders, navigating ambiguity and shipping quickly without compromising reliability.
• Collaborative, with a willingness to share knowledge and mentor others.

Required skills

• Python, SQL, system design and automated testing
• Good to have: production data pipelines and data engineering (BigQuery, dbt, Apache Airflow, PySpark, lakehouse)
• Good to have: semantic layers (dbtflow, cube), knowledge graphs, context engineering and retrieval systems
• Good to have: AWS or GCP, Docker, CI/CD pipelines, full-stack product development, developer tools

What we offer

• A collaborative, international engineering team with end-to-end ownership of meaningful projects.
• Culture of technical learning, experimentation and professional development.
• Regular company and team events, with a commitment to diversity and inclusion.
• Benefits including free food, health and dental insurance, and learning and development opportunities.