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Open nowPosted 15 days ago

Senior GenAI Engineer

MyCareersFuture94,028 open roles

Pay
SGD 7,000 – SGD 10,000 a month
Where
Singapore
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Your applicationOpen nowSenior GenAI EngineerMyCareersFuture · Singapore

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  2. CV RocketCV written for this posting.

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The clock on this job

Early applications get read.

7.7% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 1.6%1 day
  2. 3.3%3 days
  3. 7.7%7 days
  4. 14.0%14 days
  5. 33.7%30 days
This job: posted 15 days ago

The posting

Dear Applicant,

If you or someone you know is interested, please send the CV directly to [email protected] (most preferred, as I may overlook some CVs due to the high volume).

Please note that visa sponsorship is not available at this time.

Key Responsibilities

  • Design, build, and enhance production-grade Generative AI applications for real-world enterprise use cases.
  • Develop GenAI applications using LangGraph, LangChain, or similar orchestration frameworks.
  • Build and implement agentic workflows, Retrieval-Augmented Generation (RAG), tool calling, prompt orchestration, and context management.
  • Work with open-weight models and hosted LLMs, including model integration and serving patterns.
  • Integrate GenAI solutions with enterprise systems, APIs, backend services, data sources, and operational platforms.
  • Design and implement reliable and scalable backend services supporting GenAI applications.
  • Engineer solutions for production readiness, including logging, tracing, monitoring, evaluation, fallback mechanisms, error handling, and troubleshooting.
  • Develop clean, maintainable, scalable, and testable code following strong software engineering practices.
  • Evaluate existing technical designs, challenge weak approaches, and recommend practical and effective alternatives.
  • Collaborate closely with application, data, platform, infrastructure, security, and business teams to deliver end-to-end GenAI solutions.
  • Troubleshoot complex application, integration, model, and production issues and drive them through to resolution.
  • Contribute to the continuous improvement of GenAI applications, architecture, engineering practices, and delivery processes.
  • Work effectively in a fast-moving environment with evolving requirements and incomplete information.
  • Take ownership of delivery and demonstrate a pragmatic, hands-on approach focused on building useful and reliable AI products rather than over-engineering or hype.

Key Requirements

  • 10+ years of software engineering experience, with recent hands-on experience in Generative AI application development.
  • Proven experience building and delivering production-grade GenAI applications, beyond prototypes, experiments, or demos.
  • Strong hands-on experience with LangGraph, LangChain, or similar GenAI orchestration frameworks.

Practical experience with:

o RAG (Retrieval-Augmented Generation)

o Agentic workflows

o Tool calling

o Prompt orchestration

o Context management

  • Experience integrating LLMs into real-world applications through APIs, backend services, and enterprise data sources.
  • Experience working with open-weight models, or strong hands-on experimentation and understanding of open-weight model deployment.
  • Strong backend development skills using Python, Java, or similar programming languages.
  • Good understanding of API design, distributed systems, scalability, and production resilience patterns.
  • Experience with logging, tracing, observability, monitoring, evaluation, and troubleshooting for GenAI or backend applications.
  • Familiarity with containerised deployment environments such as Kubernetes or OpenShift.
  • Strong software engineering discipline with the ability to write clean, maintainable, scalable, and testable code.
  • Strong analytical, debugging, and problem-solving skills.
  • Ability to assess technical designs critically and propose practical improvements.
  • Strong communication and stakeholder management skills, with the ability to collaborate across business, application, data, infrastructure, platform, and security teams.
  • High level of ownership, curiosity, enthusiasm, and willingness to get hands-on with technical details.
  • Comfortable working in a fast-paced environment with evolving requirements and ambiguity.
  • Pragmatic delivery mindset, with a focus on building reliable and useful solutions rather than over-engineering.

Nice to Have:

  • Experience with DeepAgent or similar agent frameworks.
  • Experience with Langfuse, Elastic, or similar observability/search platforms.
  • Experience using Redis for caching, conversation state, rate limiting, or queue-backed workflows.
  • Experience with vLLM or similar inference-serving frameworks for open-weight models.
  • Experience deploying GenAI workloads across cloud or containerised environments.
  • Experience in financial services or banking is not required.
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