Gen AI Developer - Generative & Agentic AI Systems (Contract)

ST Engineering; Singapore; Hybrid; SGD 90,000 - 130,000; Full time

Job summary

A leading technology firm in Singapore is looking for a Gen AI Developer to design and productionize intelligent agentic systems powered by LLMs. You will build autonomous agents that reason and act, working closely with software and AI engineers. The ideal candidate has over 6 years of experience in software or AI development and expertise in LLM APIs and agent design. This position offers a startup feel with big company resources and a hybrid work setup.

Benefits

Agile team environment

Direct collaboration with AI researchers

Experimentation and self-development culture

Qualifications

• 6+ years in software/AI development, including 2+ years building LLM-driven applications.
• Strong experience with LLM APIs and reusable agent stacks.
• Knowledge of Model Context Protocol (MCP) or similar standards.

Responsibilities

• Design and improve LLM-powered agents for task planning and execution.
• Build modular agent stacks using frameworks like LangChain.
• Collaborate with engineers to productionize agents.

Skills

Python

LLM APIs

RAG pipelines

Multi-agent orchestration

Tools

Docker

Kubernetes

Weaviate

FAISS

Job description

Gen AI Developer - Generative & Agentic AI Systems (Contract)

We’re looking for a hands-on GenAI Developer to design and productionize intelligent agentic systems powered by LLMs, computer vision, and vector databases. You’ll build autonomous agents that reason, retrieve, and act - driving real-world GenAI applications from prototype to production. This is a true builder role for someone who enjoys taking ideas from notebooks to live users. You’ll work closely with Software and AI Engineers to integrate workflows into production and shape how our agents interact with tools, memory, data, and humans.

Responsibilities

• Design and improve LLM-powered agents for task planning, execution, retrieval, and memory.
• Build modular agent stacks using frameworks like LangChain, CrewAI, AutoGen, or custom orchestrators.
• Develop workflows that connect agents to APIs, computer vision models, and vector databases.
• Lead prompt engineering, RAG pipelines, and multi-agent coordination strategies.
• Collaborate with engineers to productionize agents with proper observability and debuggability.
• Evaluate agent behavior through logging, telemetry, and custom evaluation tools.
• Contribute to architecture patterns such as task workflows, tool interfaces, memory optimization, and feedback handling.
• Work with infrastructure teams to deploy agentic systems to production, ensuring monitoring, scaling, and rollback safety.
• Ensure compliance with Model Context Protocol (MCP) standards for structured context and execution.

Must-Have Skills

• 6+ years in software/AI development, including 2+ years building LLM-driven applications.
• Strong Python skills with experience in reusable agent stacks or RAG pipelines.
• Hands-on with LLM APIs (OpenAI, Anthropic, HuggingFace, etc.) and building prompt/tool workflows.
• Experience integrating vector databases (Weaviate, FAISS, pgvector, Pinecone).
• Familiarity with multi-agent orchestration (CrewAI, AutoGen, LangGraph, or custom).
• Experience shipping AI tools or services into production with containerization and cloud platforms (Docker, Kubernetes, GCP/AWS).
• Understanding of agent design (memory management, context management, tool contracts).
• Knowledge of Model Context Protocol (MCP) or similar standards.

Bonus Skills

• Experience with agent evaluation, prompt testing, and reducing hallucinations/latency.
• Exposure to hybrid workflows combining LLMs with computer vision.
• Knowledge of event-driven or streaming agents (Kafka, LCEL, reactive frameworks).
• Experience building simple interfaces with Streamlit, Gradio, or browser automation.
• Familiarity with fine-tuning techniques (LoRA/QLoRA) or multi-modal agent training.

What We Offer

• Small, agile team (5–6 engineers + interns) with autonomy and real ownership.
• Startup feel with a big company resources:
• International environment where the majority of the team and leadership is from startups or big international corporations and from various countries.
• Low-bureaucracy, high-impact startup environment where your code directly supports next-gen AI deployment.
• Experimentation and self-development are in our culture
• Knowledge sharing and collaboration
• Direct collaboration with top AI researchers and computer vision scientists.
• Hybrid work setup: ~2–3 days in office per week.

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