Software Developer

ES TECH CONSULTANCY PTE. LTD.; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

ES Tech Consultancy PTE. LTD. is seeking a Software Developer for a contract assignment in Singapore. The role focuses on AI/ML engineering, Gen AI concepts, and rapid experimentation across cloud AI platforms.

You will collaborate with SMEs, data scientists, and developers to design experiments, build lightweight pipelines, and evaluate model outputs for quality and alignment with business goals.

Qualifications

• 3+ years hands-on experience in AI/ML or Gen AI engineering.
• Understanding of Gen AI concepts (tokenization, embeddings, RAG, prompting, evaluation).
• Familiar with at least one major cloud AI service (AWS Bedrock, Vertex AI, or Foundry); others a plus.
• Working knowledge of China AI models (DeepSeek, Qwen, GLM).
• Familiarity with agentic orchestration frameworks for multi-step workflows.
• Ability to perform rapid experimentation and iterate quickly.
• Proficiency in Python and Gen AI toolkits.
• Experience integrating OpenAI APIs into workflows and combining with RPA.

Responsibilities

• Experimentation & Evaluation: design experiments and evaluate outputs for quality and alignment.
• Data Preparation & Pipelines: prep data and build simple ingestion/evaluation pipelines.
• Gen AI & Agentic Techniques: work with foundation models via cloud services and agentic frameworks.
• FDE & Development/Maintenance Coverage: test models/prompts and support production-grade tuning.
• Collaboration: work with PM/dev/SMEs to refine data/prompts and document results.

Skills

AI/ML engineering

Gen AI concepts

Cloud AI services

China AI models

Agentic orchestration

Rapid experimentation

Python programming

OpenAI API integration

Gen AI tools

Data wrangling

Analytical mindset

Tools

AWS Bedrock

Google Vertex AI

Azure AI Foundry

Job description

Seeking Software Developer for Contract assignment.

What will you do:

1. Experimentation &Evaluation

   Understand the business problem, POC objectives, and evaluation metrics.

   Design experiments to test different model configurations, prompts, or retrieval strategies.

   Analyse Gen AI outputs for quality, accuracy, and alignment with requirements; identify common failure modes (hallucination, bias, irrelevant answers, factual errors).

   Support SMEs in defining ground truth benchmarks for evaluation.

2. Data Preparation &Pipelines

   Profile and clean sample datasets for experimentation (lightweight data prep).

   Build and test simple pipelines for data ingestion, prompt construction, and output evaluation.

3. Gen AI & Agentic Techniques

   Work with foundation models via AWS Bedrock, Google Vertex AI, or Azure AI Foundry depending on engagement cloud posture.

   Apply working knowledge of China-origin models (DeepSeek, Qwen, GLM) as increasingly relevant, cost-effective alternatives.

   Apply agentic orchestration frameworks such as AWS Strands, LangGraph, or equivalent, for designing and testing multi-step agent workflows.

   Apply prompt strategies, prompt engineering patterns, and RAG design (chunking, embeddings, retrieval evaluation); support ingesting/vectorising content to knowledge bases.

   Provide insights and recommendations to improve model performance in quick iterations, including fine-tuning approaches where applicable.

4. FDE &Development/Maintenance Coverage

   During FDE engagements: rapidly test candidate models, prompts, and retrieval strategies, giving the team fast, evidence-based go/no-go signals.

   During system development & maintenance engagements: support ongoing model/prompt tuning and monitoring as applications move toward production.

5. Collaboration

   Collaborate with developers on integrating models into the POC workflow, and work closely with PM, devs, and SMEs to refine data and prompts.

   Partner with the Data Scientist on evaluation methodology where classical statistical baselines are in play, and with the AI/LLM Specialist when an engagement moves toward production-grade evaluation.

   Document experiments briefly but clearly (hypothesis result conclusion).

What we required from you:

• 3+ years hands-on experience in AI/ML or Gen AI engineering.
• Understanding of Gen AI concepts (tokenization, embeddings, RAG, prompting, evaluation).
• Familiar with at least one major cloud AI service (AWS Bedrock, Google Vertex AI, or Azure AI Foundry); working knowledge of others a plus.
• Working knowledge of the China AI model landscape (DeepSeek, Qwen, GLM) a strong plus.
• Familiarity with agentic orchestration frameworks (AWS Strands, LangGraph, or equivalent), for designing and testing multi-step agent workflows.
• Ability to do rapid experimentation rather than perfect models.
• Basic proficiency in Python and Gen AI tools (e.g., model SDKs, vector DBs).
• Experience integrating OpenAI APIs into HR helpdesk workflows and combining AI with RPA, business applications and enterprise processes.
• Analytical mindset: can quantify subjective output (accuracy, relevance, readability).
• Gooddata wrangling skills to prepare small datasets quickly