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Appier

Senior Software Engineer, Backend Development (REC)

Appier is hiring a Senior Software Engineer, Backend Development (REC) in Taipei, Taiwan. Level rates it ; you can apply on Appier.

Level's read on this job

  • On Level's scale, this software engineer role is Builds AI ●●●●: the job is building AI systems.
  • The posting mentions Copilot, LangChain and AutoGen among its tools and skills.
  • Level classes it as a senior role.
  • Appier has 66 other open roles on Level.

AI in this role

copilotlangchainautogen
ragai-agents

About Appier

Appier (TSE: 4180) is an AI-native Agentic AI as a Service (AaaS) company that empowers businesses to create value through cutting-edge AdTech and MarTech solutions. Founded in 2012 with the vision of “Making AI Easy by Making Software Intelligent,” Appier helps businesses turn AI into ROI through its Ad Cloud, Personalization Cloud, and Data Cloud—each powered by Agentic AI that enables autonomous, adaptive, and real-time decision-making. Today, Appier operates 17 offices across APAC, the US, and EMEA, and is listed on the Tokyo Stock Exchange. Learn more at www.appier.com.

 

About the Role

We’re on the lookout for an ambitious and technically outstanding Senior Software Engineer, Backend Development to join our Enterprise Solution Engineering Team, Product Recommendation (ES REC). Software engineers at Appier build a wide range of platforms and services that interconnect data and AI with our customers and users. In this role, you will be at the forefront of AI innovation, designing and building scalable backend architecture that delivers personalized experiences.

 

What You’ll Do

  • Key owner of sizable engineering projects and services within the ES REC team.
  • Architect and implement AI Agents and agentic workflows to automate decision-making processes and enhance recommendation delivery.
  • Build and optimize Machine Learning pipelines for large-scale personalization, ensuring efficient data processing, model serving, and low-latency response.
  • Design and operate scalable, cloud-native architectures leveraging managed services (e.g., GKE, BigQuery, or Pub/Sub) to support high-throughput recommendation workflows.
  • Architect and operate resilient ML job execution frameworks covering training, inference, and post-processing workflows to ensure system elasticity.
  • Define and implement CI/CD pipelines with tools like Jenkins or ArgoCD to enable seamless, automated, and reliable deployments.
  • Lead system designs and provide technical guidance to team members.
  • Mentor engineers in cross-team development processes.
  • Lead code reviews to ensure high quality coding standards.
  • Facilitate agile process collaborating with cross-functional teams, including Data Scientists and Product Managers.
  • Continuously improve the system's observability, incident management, DevOps and production operational SOPs.
  • Profiling and performance tuning of critical components to ensure high performance and scalability.
  • Participate in idea brainstorming and contribute ideas to technology, algorithms and products.

 

About you

[Minimum qualifications]

  • 5+ years of experience in software development.
  • Proficient in Python or Go.
  • Ability to build web services on Linux and good knowledge of Network API Design (REST/GraphQL).
  • Proactive, good interpersonal skills, and a strong interest in the MarTech (Marketing Technology) domain and customer-centric product development.
  • Open-minded towards using AI tools (e.g., Copilot) to improve coding efficiency.
  • Good understanding of SQL/NoSQL databases (MySQL, MongoDB, Redis, etc.).

[Preferred qualifications]

  • Hands-on experience with Infrastructure as Code (IaC) tools such as Terraform or Helm to manage cloud resources.
  • AI Agent Development: Experience in building applications related to LLMs, multi-agent systems, or RAG architectures.
  • Machine Learning Engineering: Understanding of the ML lifecycle—from training and prediction to evaluation and feedback loops.
  • Familiarity with LLM orchestration frameworks (e.g., Google ADK, LangChain, AutoGen) and Vector Databases.
  • Experience in designing and architecting large-scale distributed systems and data-intensive applications.
  • Experience with monitoring and alert systems (e.g., Prometheus, Grafana)

 

Why Join Appier?

At Appier, you’ll stand at the frontier of AI innovation, working alongside world-class engineers and researchers to create products that transform entire industries. Here, your engineering expertise will directly impact millions of users and drive revolutionary advances in marketing technology. If you’re ready to tackle challenging ML infrastructure problems with passion and creativity, Appier is your ultimate playground!

 

#LI-TC1

How we rate this

Senior Software Engineer, Backend Development (REC) at Appier rates 96 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGAI agentsCopilotLangChainAutoGen

Also common in software engineer jobs at this level

Pay

Typical software engineer job
$168k

This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How do you decide when an AI agent can act on its own versus asking for approval first?
  3. What are the limits of Copilot that you've run into, and how did you work around them?
  4. What's a project where you used LangChain hands-on?
  5. Walk me through how you've used AutoGen in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: RAG, AI agents, Copilot, LangChain, and AutoGen. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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