AI Agent Architect & Full-Stack Engineer

ABEAM CONSULTING (SINGAPORE) PTE. LTD.

Singapore

On-site

SGD 120,000 - 190,000

Full time

6 days ago

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Job summary

ABeam Consulting (Singapore) PTE. LTD. seeks a senior AI engineer to lead end-to-end AI agent projects for enterprise clients.

You will design, prototype, and deliver AI solutions that translate business needs into actionable technology. You will collaborate with cross-functional teams, mentor juniors, and ensure scalable, secure deployments on cloud platforms. Proficiency in Python, React, and AI frameworks is essential, along with strong communication in English and Japanese.

Qualifications

Bachelor's degree in Computer Science, Information Technology, Engineering or related field required.
3+ years in AI engineering, Generative AI, AI agent development, or related areas.
Hands-on experience designing and developing AI agents, LLM apps, and enterprise AI solutions.
Strong proficiency in Python and JavaScript/TypeScript; experience with React, Next.js, FastAPI or Flask.
Experience with AI agent frameworks such as LangGraph, Semantic Kernel, AutoGen, OpenAI Agents SDK, or Copilot Studio.
Solid understanding of RAG, prompt engineering, vector databases, APIs, and cloud platforms (Azure/AWS/GCP).
Experience with containerization and production deployment of cloud-based apps.
Excellent analytical, problem-solving, and communication skills; able to translate business requirements into technical solutions.
Experience in ML/DS/analytics, consulting or pre-sales is a plus; enterprise AI platform delivery exposure.
English and Japanese communication skills for collaboration with stakeholders and clients.

Responsibilities

Partner with clients to identify AI opportunities delivering measurable business value.
Translate business requirements into technical solutions, plans, and rapid prototypes.
Lead end-to-end delivery from discovery to deployment and adoption.
Facilitate workshops and collaborate with engineering, security, data, and business teams.
Design, develop, and deploy AI agents using enterprise frameworks.
Build AI workflows with tool calling, memory, orchestration, and human-in-the-loop processes.
Integrate AI agents with enterprise apps, APIs, databases, and knowledge repositories.
Implement RAG architectures, guardrails, observability, and cost monitoring.
Optimize agent quality, reliability, scalability, and latency.