Artificial Intelligence Engineer

Evo Commerce owns a few CPG brands focusing on high quality supplements. We’re currently operating in 3 markets and our team members are based out of Singapore. We have past experience working in big tech companies which includes Grab, Tiktok, Zalora, FoodPanda, Fave, Shopee, etc.

Our hero product, bback (previously known as Bounceback), is currently one of the fastest growing CPG brands in SEA and is loved by bankers, traders, influencers and bartenders with a high efficacy rate against hangover post drinking. Our aim is to become the Redbull of hangover recovery, making hangover remedies accessible to drinkers worldwide. Then came Stryv, our high quality, salon-grade hair tools and product line with an affordable price tag. We believe there’s no need to break your bank to get the hair you want.

We’re big advocates of direct-to-consumer brands, and believe in the new world (Post-COVID), consumers buy directly from global brands through digital native storefront, bypassing distributors, wholesalers and retailers. This means commerce and information are more efficient, and the implication to the end customer is that product quality goes up and cost of goods are reduced drastically. We want to be the catalyst for this paradigm shift within the health and beauty industry.

Find out more: www.withevo.com

We are seeking an AI Engineer to design, build, and deploy AI-powered solutions that drive real business impact. This role sits at the intersection of software engineering, data, and machine learning, with a strong focus on turning AI capabilities into scalable, production-ready applications.

The ideal candidate is both technically strong and product-oriented, capable of translating business needs into practical AI systems that are reliable, efficient, and cost-effective.

Key Responsibilities

1. Develop AI-Powered Applications

• Design and implement AI-driven features such as chatbots, automation tools, recommendation systems, and content generation solutions
• Integrate AI models (e.g., large language models, vision models) into internal and customer-facing applications
• Ensure solutions are scalable, reliable, and performant

2. Design AI Systems & Workflows

• Build end-to-end AI pipelines, including prompt engineering and orchestration workflows
• Develop retrieval-augmented generation (RAG) systems and knowledge-based applications
• Implement memory systems and agent-based architectures that interact with external tools and APIs

3. Data Engineering & Management

• Collect, clean, and structure data for AI applications
• Develop and manage embeddings and vector databases
• Prepare datasets for model training, fine-tuning, and evaluation

4. Optimize Performance & Cost

• Improve model accuracy through prompt tuning, evaluation frameworks, and iterative testing
• Optimize latency and response times for production systems
• Manage and reduce operational costs (e.g., token usage, model selection)

5. Production Deployment & Maintenance

• Deploy AI systems into production environments
• Monitor performance, troubleshoot issues, and handle edge cases
• Ensure system security, data privacy, and compliance standards are met

Requirements:

• 2–5 years of relevant experience in software engineering, machine learning, or AI engineering, with hands-on experience building and deploying AI applications in production.
• Proficiency in Python and/or Node.js, with experience building scalable backend systems
• Hands-on experience with AI/ML models (e.g., OpenAI, Anthropic, or open-source LLMs) and integrating them into applications
• Familiarity with AI frameworks/tools (e.g., LangChain, LlamaIndex), vector databases, and API integrations
• Experience with cloud platforms (e.g., AWS, GCP) and deploying production systems
• Strong understanding of AI system design, including prompt engineering, RAG pipelines, and agent workflows
• Ability to work with data, including preprocessing, embeddings, and dataset preparation
• Strong problem-solving skills with the ability to debug and optimize AI systems for performance, accuracy, and cost
• Product-oriented mindset with a focus on building practical, high-impact solutions