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Sr. AI/ML Specialist Solutions Architect Job Opening In Singapore, Singapore – Now Hiring Amazon Web Services (AWS)


Job description

Sr. AI/ML Specialist Solutions Architect

Join to apply for the Sr. AI/ML Specialist Solutions Architect role at Amazon Web Services (AWS)

Description Are you passionate about Machine Learning (ML), Deep Learning, Artificial Intelligence (AI), Generative AI and Agentic AI?

Are you excited by the challenge of driving production usage of ML and AI at scale?

Come join us!

ML and AI, especially Generative AI and Agentic AI, are rapidly growing in importance.

We're witnessing the revolutionary impact of Generative AI creating everything from code to content, while Agentic AI systems are autonomously solving complex business challenges.

From home automation and mobile apps to financial trading and shipping logistics, AI is transforming every industry.

Given the massive computational scale required for developing AI models, particularly large language models and autonomous agents, the cloud is an ideal place to deploy AI models, and Amazon Web Services (AWS) is the leader in the deployment of AI.

We're looking for someone passionate and deeply excited about this space.

Someone who is devoted to helping customers understand how AI can make a big difference to their businesses.

As an AI/ML Specialist Solutions Architect (SA), you will be the Subject Matter Expert (SME) for designing scalable, secure, and cost-effective AI/ML, Generative AI and Agentic AI solutions that leverage AWS services.

Working at the intersection of innovation and enterprise requirements, you'll architect production-grade solutions that are reliable, well-governed, and compliant with industry standards.

Your expertise will be crucial in helping organizations build responsible AI practices, from traditional ML to advanced Generative AI and Agentic AI systems, while implementing robust governance frameworks and secure AI pipelines that scale efficiently.

Part of the Data and AI Specialist Solutions Architecture team, you will guide customers through their AI transformation journey, working closely with other Specialist SAs in Big Data, Databases and Analytics, Storage, Containers, Accelerated Compute and Business Development teams.

You'll help customers establish scalable MLOps practices and create sustainable, enterprise-grade AI architectures that deliver measurable business value.

Your role includes developing technical content, reference implementations, and presentations to enable customers, partners, and ISVs to fully leverage AI/ML and Generative AI on AWS.

Additionally, you will create field enablement materials to help the broader SA population understand and integrate AWS AI/ML and Generative AI solutions into customer architectures.

You must have deep technical experience across the AI spectrum - from traditional ML and deep learning to Generative AI and Agentic AI - backed by a strong mathematics and statistics foundation.

This includes hands-on experience with large language models (LLMs), foundation models, and autonomous agent frameworks, alongside expertise in implementing RAG systems, designing prompt engineering frameworks, and developing multi-agent systems.

You should be proficient with both commercial and open-source technologies, including popular frameworks like LangChain, Hugging Face, and PyTorch, as well as vector databases and embedding models.

Your comprehensive understanding of the AI/ML ecosystem, including leading vendors, emerging startups, and key open-source projects, will be crucial in helping AWS customers create robust ML pipelines, establish effective MLOps practices, and build future-proof AI architectures.

Candidates must have great communication skills and be very technical, with the ability to engage AWS customers at any level, from executives to developers.

Previous experience with AWS is desired but not required, provided you have experience building large scale solutions.

You will get the opportunity to work directly with senior engineers at customers, partners and AWS service teams, influencing their roadmaps and driving innovation.

Key Responsibilities:

  • Build and maintain technical trusted advisor relationships with influential technical decision-makers to drive successful adoption and deployment of AWS services, with particular focus on enterprise-grade AI/ML architectures, Generative AI solutions, and autonomous agent systems.

  • Architect scalable, secure, and cost-effective solutions leveraging AWS's comprehensive AI stack, from traditional ML services to leading Generative AI offerings.

    Work closely with customers to understand their business needs and design solutions that optimize both performance and cost while ensuring robust governance and responsible AI practices.

  • Serve as a thought leader in the AI/ML space by developing compelling technical content and practical implementations showcasing modern AI architectures.

    Create reference architectures, workshops, and demos that highlight integration patterns for LLMs, RAG systems, autonomous agents, and MLOps best practices.

    Share insights through AWS Blogs, public speaking events, and technical communities.

  • Build and nurture an internal AWS community of AI/ML experts, focusing on knowledge-sharing across traditional ML, Generative AI, and Agentic AI domains.

    Establish best practices for emerging technologies and create enablement materials for the broader AWS technical community.

  • Collaborate across AWS teams to accelerate customer success with AI/ML implementations.

    Work with business development, professional services, and support teams to ensure effective adoption of AWS AI services, from proof-of-concept to production deployment.

  • Drive technical excellence as a key member of the Data and AI Specialist team.

    Act as a technical liaison between customers and AWS engineering teams, ensuring successful implementation of AI solutions while maintaining alignment with AWS's well-architected framework and AI best practices.

Basic Qualifications:

  • Bachelor's degree in computer science, engineering, mathematics or equivalent
  • 5+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
  • Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
  • 10+ years of combined experience in AI/ML and related technologies, with deep expertise in traditional machine learning and deep learning.

    Must have experience building production-grade AI systems, complemented by practical knowledge of modern Generative AI technologies (LLMs, foundation models, RAG systems) and autonomous agent frameworks.

    Strong background in AI architecture patterns and MLOps practices, with demonstrated ability to design and deploy enterprise-grade AI solutions at scale.

Preferred Qualifications:

  • Experience in a technical role within a sales organization
  • Cloud Technology Certification (such as Solutions Architecture, Cloud Security Professional or Cloud DevOps Engineering)
  • Advanced degree (MS/PhD) in Computer Science, Machine Learning, or related field, with research or practical experience in emerging AI technologies.

    Published work or significant contributions to AI/ML open-source projects, particularly in Generative AI or autonomous systems, would be highly valued.

Amazon is an equal opportunities employer.

We believe passionately that employing a diverse workforce is central to our success.

We make recruiting decisions based on your experience and skills.

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Required Skill Profession

Professional Services


  • Job Details

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7. Obeying Singapore laws and regulations

What Is the Average Salary Range for Sr. AI/ML Specialist Solutions Architect Positions?

The average salary range for a varies, but the pay scale is rated "Standard" in Singapore. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

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Key qualifications for Sr. AI/ML Specialist Solutions Architect typically include Professional Services and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

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Interview Tips for Sr. AI/ML Specialist Solutions Architect Job Success

Amazon Web Services (AWS) interview tips for Sr. AI/ML Specialist Solutions Architect

Here are some tips to help you prepare for and ace your Sr. AI/ML Specialist Solutions Architect job interview:

Before the Interview:

Research: Learn about the Amazon Web Services (AWS)'s mission, values, products, and the specific job requirements and get further information about

Other Openings

Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

Dress Professionally: Choose attire appropriate for the company culture.

Prepare Questions: Show your interest by having thoughtful questions for the interviewer.

Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.

During the Interview:

Be Punctual: Arrive on time to demonstrate professionalism and respect.

Make a Great First Impression: Greet the interviewer with a handshake, smile, and eye contact.

Confidence and Enthusiasm: Project a positive attitude and show your genuine interest in the opportunity.

Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.

Ask Prepared Questions: Demonstrate curiosity and engagement with the role and company.

Follow Up: Send a thank-you email to the interviewer within 24 hours.

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Be Yourself: Let your personality shine through while maintaining professionalism.

Be Honest: Don't exaggerate your skills or experience.

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Body Language: Maintain good posture, avoid fidgeting, and make eye contact.

Turn Off Phone: Avoid distractions during the interview.

Final Thought:

To prepare for your Sr. AI/ML Specialist Solutions Architect interview at Amazon Web Services (AWS), research the company, understand the job requirements, and practice common interview questions.

Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Amazon Web Services (AWS)'s products or services and be prepared to discuss how you can contribute to their success.

By following these tips, you can increase your chances of making a positive impression and landing the job!

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