Senior Software Engineer (Data & AI)

Location: Singapore

Company

hirify.global operates local delivery platforms including foodpanda, serving food and grocery customers across around 65 countries.

What you will do

• 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, observability, and feedback loops to measure and improve AI application correctness and reliability.
• Partner with analytics and business teams to translate ambiguous workflows into practical solutions, rapidly prototype ideas, and refine products using real-world feedback.
• Own the full software lifecycle, including discovery, architecture, implementation, testing, deployment, monitoring, and continuous improvement.
• Design and maintain ingestion, ETL/ELT, and context-retrieval pipelines supporting AI models, semantic layers, and agentic workflows.
• Contribute to architecture discussions, RFCs, code reviews, pair programming, mentoring, incident investigation, performance optimization, and the production 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 systems and taking AI solutions from experimentation into production.
• Experience building evaluation datasets, evaluation frameworks, automated harnesses, or using observability tools such as Langfuse.
• Ability to make sound engineering and product decisions about when to use LLMs versus deterministic software, balancing correctness, complexity, cost, and user experience.
• Awareness of emerging AI research, models, agent architectures, and software engineering practices, with a pragmatic approach to experimentation.
• Ownership mindset, comfort with ambiguity, direct stakeholder collaboration, and focus on the experience of software users.
• Ability to ship quickly while maintaining user trust, reliability, maintainability, evidence-based testing, and continuous improvement.
• Collaborative approach to technical discussions, pair programming, code reviews, and mentorship.

Nice to have

• Hands-on experience building and maintaining production data pipelines, data integrations, or data-intensive systems, including data quality, modeling, and operational reliability.
• Experience with BigQuery, dbt, Apache Airflow, PySpark, or lakehouse architectures.
• Experience integrating LLMs with structured data, semantic layers such as dbtflow or Cube, knowledge graphs, context engineering, or retrieval systems.
• Experience with AWS or GCP, Docker, and automated CI/CD pipelines.
• Experience shipping full-stack product features across frontend, backend, and model integrations.
• Experience building internal platforms, developer tools, or infrastructure that improves how engineers build, test, or operate software.

Culture & Benefits

• Collaborative international engineering environment focused on data infrastructure and applied AI.
• Opportunities to own projects from early ideas through production systems used by business teams.
• Culture of technical learning, experimentation, knowledge sharing, and professional development.
• Regular company and team events with a commitment to diversity and inclusion.
• Free food, health and dental insurance, and learning and development opportunities.