Senior Software Engineer (Data & AI)
Delivery Hero1 day ago
Singapore, SingaporeSenior
Responsibilities
- Design, build, and maintain production AI applications, agentic workflows, RAG systems, and integrations with business knowledge, semantic layers, and external tools.
- Build evaluation datasets, automated testing and evaluation harnesses, production observability, and feedback loops to improve AI application performance.
- Partner with analytics and business teams to translate ambiguous workflows into practical, user-focused solutions.
- Own the full software lifecycle, including technical discovery, architecture, implementation, testing, deployment, monitoring, and continuous improvement.
- Design, build, and maintain ingestion, ETL/ELT, and context-retrieval pipelines supporting AI models, semantic layers, and agentic workflows.
- Participate in technical design discussions, architectural decisions, RFCs, code reviews, pair programming, and engineering mentorship.
- Maintain production reliability through observability, incident investigation, performance optimization, and participation in the on-call rotation.
Requirements
- 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 applied AI systems for production.
- Experience building AI evaluation datasets, frameworks, automated harnesses, or observability solutions such as Langfuse.
- Strong judgment regarding LLM use, deterministic software, correctness, complexity, cost, and user experience.
- Ability to work directly with stakeholders, navigate ambiguity, prototype rapidly, and make pragmatic product and engineering decisions.
- Experience with production data pipelines, data integrations, data-intensive systems, data quality, modeling, and operational reliability is preferred.
- Experience with BigQuery, dbt, Apache Airflow, PySpark, lake house architectures, semantic systems such as dbtflow or cube, knowledge graphs, context engineering, retrieval systems, AWS or GCP, Docker, CI/CD pipelines, full-stack product development, or developer platforms is preferred.
Benefits
- Collaborative international engineering team working on data infrastructure and applied AI problems.
- End-to-end ownership of meaningful projects used by business teams.
- Technical learning, experimentation, knowledge sharing, and professional development opportunities.
- Regular company and team events with a commitment to diversity and inclusion.
- Free food, health and dental insurance, and learning and development opportunities.
Tech Stack
Categories
AI ApplicationsData Engineering
About Delivery Hero
Delivery Hero builds a marketplace and logistics platform for online food delivery, groceries, and local commerce, serving consumers, restaurants, and retailers through regional brands. It monetizes via commissions, delivery and service fees, and advertising, and also runs quick‑commerce operations. Founded in 2011 and headquartered in Berlin, the company operates in around 65 countries and has been listed on the Frankfurt Stock Exchange since 2017.