AI Engineer

AVENSYS CONSULTING PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Benefits offered by this job

Health insurance

Job summary

Avensys Consulting PTE. LTD. in Singapore is seeking an AI Engineer to design and run rapid Gen AI experiments and optimize prompts and retrieval strategies, delivering evidence-based results for POC/POV engagements.

You will work with AWS Bedrock, Vertex AI, or Azure AI Foundry, collaborate with PMs and data scientists, and contribute to production-grade solutions while maintaining rapid iteration cycles. Role offers growth into senior leadership with a focus on experimentation strategy, model

Qualifications

• Experience in AI/ML or Gen AI engineering including hands-on development.
• Familiarity with Gen AI concepts (tokenization, embeddings, RAG, prompting, evaluation).
• Working knowledge of at least one major cloud AI service (AWS Bedrock, Vertex AI, or Azure AI Foundry).
• Knowledge of China AI models (DeepSeek, Qwen, GLM) is a strong plus.
• Exposure to agentic orchestration frameworks for multi-step workflows.
• Proficiency in Python and Gen AI tooling; ability to run rapid experiments.

Responsibilities

• Design and run rapid experiments on Gen AI models and prompts.
• Prepare and clean datasets for experimentation and build simple data pipelines.
• Apply prompt strategies and RAG design to improve retrieval and accuracy.
• Test candidate models and features during FDE engagements for go/no-go decisions.
• Collaborate with PMs, developers, and SMEs to refine data and prompts.

Skills

Gen AI engineering

Experimentation

Prompt engineering

Data wrangling

Python

Cloud AI services

Model evaluation

LMOps basics

Team collaboration

Tools

AWS Bedrock

Vertex AI

Azure AI Foundry

LangGraph

AWS Strands

Vector DBs

Job description

Avensys is a reputed global IT professional services company headquartered in Singapore. Our service spectrum includes enterprise solution consulting, business intelligence, business process automation and managed services. Given our decade of success we have evolved to become one of the top trusted providers in Singapore and service a client base across banking and financial services, insurance, information technology, healthcare, retail, and supply chain.

We are currently looking to hire AI Engineer.

This is an exciting opportunity to expand your skill set, achieve job satisfaction and work-life balance. More details as below.

Job Description

This role sits within organization AI Central's (AIC) Forward Deployed Engineering (FDE) model — the combined capability that takes AI solutions from proof-of-concept through to hardened production systems. As AI Engineer, you design and run rapid experiments on Gen AI models, prompts, and retrieval strategies to give the squad fast, evidence-based answers on model performance — operating primarily within fast-moving FDE engagements (POC/POV, pilot deployments).

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).

Role Levels We Are Hiring For We are hiring at two levels for this role. All responsibilities above apply to both; the distinction is in scope of ownership, years of experience, and seniority of judgement expected. Senior AI Engineer - 6+ years of hands-on experience, including prior ownership of experimentation strategy for complex or ambiguous problem statements. Sets the experimentation approach across multiple engagements and mentors junior AI Engineers. - Advises PMs and stakeholders directly on feasibility and experimentation trade-offs; represents technical experimentation findings in client conversations.

Qualifications

• 4+ years hands-on experience in AI/ML or Gen AI engineering (see Role Levels for the split between AI Engineer and Senior AI Engineer).
• 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).
• Analytical mindset: can quantify subjective output (accuracy, relevance, readability).
• Good data wrangling skills to prepare small datasets quickly.
• Preferred Qualifications - Generative AI Leader or Machine Learning Engineer certification, or equivalent.
• Exposure to LLMOps practices (model monitoring, versioning) for production transition.
• Familiarity with model fine-tuning techniques.
• Exposure to regulated government cloud environments.

Tech Stack (Illustrative)

• Languages: Python
• LLM Runtime: AWS Bedrock, Google Vertex AI, Azure AI Foundry; DeepSeek/Qwen/GLM (China stack)
• Agentic Frameworks: AWS Strands, LangGraph
• Data & Eval: Model SDKs, vector DBs, pandas/Jupyter-style tooling for experimentation

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