1,107 AI Consultant jobs in Indonesia

• Develop and articulate AI strategies aligned with client business goals.
• Identify opportunities for AI implementation to enhance operational efficiency and competitive advantage.
• Assess client readiness for AI adoption and develop change management plans.
• Advise on the selection and implementation of AI technologies and platforms.
• Develop business cases and ROI analyses for AI initiatives.
• Conduct workshops and training sessions on AI concepts and strategy.
• Collaborate with client stakeholders at all levels.
• Stay abreast of the latest advancements and trends in AI and emerging technologies.
• Evaluate AI vendors and provide recommendations.
• Ensure AI solutions are ethical, responsible, and compliant.

• Advanced degree (Master's or Ph.D.) in Computer Science, AI, Data Science, Business, or a related field.
• Minimum of 7 years of experience in technology consulting, strategy, or a related role, with a significant focus on AI.
• Deep understanding of AI/ML concepts, algorithms, and applications.
• Proven experience in developing and implementing AI strategies for businesses.
• Excellent analytical, problem-solving, and strategic thinking skills.
• Exceptional communication, presentation, and interpersonal skills.
• Ability to manage complex projects and client relationships.
• Experience with cloud platforms (AWS, Azure, GCP) and AI/ML tools is a plus.
• Strong business acumen and understanding of various industry landscapes.

About the Team:
The Engineering and Technology team is at the core of the Shopee platform development. The team is made up of a group of passionate engineers from all over the world, striving to build the best systems with the most suitable technologies. Our engineers do not merely solve problems at hand; We build foundations for a long-lasting future. We don't limit ourselves on what we can or can't do; we take matters into our own hands even if it means drilling down to the bottom layer of the computing platform. Shopee's hyper-growing business scale has transformed most "innocent" problems into huge technical challenges, and there is no better place to experience it first-hand if you love technologies as much as we do.

About Team
The AI Solutions team builds and pioneers the future of AI-driven automation at Sea. We are the developers of Smart (Sea Multi-Agent Realization Platform) - the company's flagship AI agents platform that enables teams across the company to automate their workflows using large language model (LLM) agents. But Smart is just the beginning.

Our team is also spearheading a wide range of AI initiatives, especially within the engineering infrastructure domain, from internal developer tooling to intelligent operations. We believe that the future of infrastructure lies in intelligent automation, and we're committed to building it from the ground up.

We thrive in a fast-paced, sharing-first culture, with a strong emphasis on learning, creativity, and experimentation. We work hard and play hard, explore ideas on the cutting edge, and aim to pioneer bold, practical solutions to complex real-world problems. If you want to shape how AI changes engineering at scale - this is the place.

Job Description:

• Design and develop the Smart platform and other AI systems, covering all essential agent platform components - agent runtimes, toolchains, memory, orchestration, logging, planning, and sandboxing.
• Build scalable backend infrastructure to support agent-based workflows across the company.
• Collaborate with teams across departments - both tech and non-tech - to land and scale real-world AI use cases.
• Drive internal agent adoption in engineering infra by replacing traditional operations with intelligent agent workflows.
• Prototype and optimize agent architectures, including Reasoning and Action (ReAct) patterns, multi-step planning, and decision workflows.
• Work on platform reliability and observability to ensure our systems are performant, debuggable, and production-ready.
• Support operations and development work in a healthy balance - you'll gain experience in shipping features and running real services.
• Build full-stack systems (primarily backend, with occasional frontend) that integrate well into internal ecosystems.
• Manage and operate supporting infrastructure, including vector stores, retrieval systems (RAG), and middleware components.
• Continuously experiment, learn, and bring in the latest advancements from the AI/agent ecosystem into production.

Requirements:

• Bachelor's degree or higher in Computer Science, Engineering, or a related field.
• 2+ years of relevant experience in software development - or fresh graduates with strong fundamentals and hunger to learn.
• Strong programming skills in Python (primary) - familiarity with Golang is a plus.
• Solid CS fundamentals - algorithms, data structures, networking, systems, and architecture.
• Backend experience designing cloud-ready services using databases, queues, caching, etc.
• Familiarity with modern AI agent frameworks like LangChain, LangGraph, or strong interest in learning them.
• Strong problem-solving mindset and ability to navigate ambiguity with curiosity and creativity.
• Willingness to work full stack - we prioritize backend but value well-rounded engineers.
• General understanding of distributed systems and cloud-native principles (e.g. the twelve-factor app), including how services are deployed, scaled, and load-balanced in a containerized environment.
• Passion for building AI systems that people actually use.

Skills below are optional but preferred:

• Experience building AI-powered platforms, assistants, or automation tools.
• Familiarity with agent patterns like ReAct (Reasoning and Action), tool chaining, or multi-agent orchestration.
• Knowledge of RAG systems, vector databases, or prompt tuning.
• Prior experience in developer tools, internal platforms, or large-scale systems.
• Exposure to observability, debugging, incident workflows, or service reliability.

The Engineering and Technology team is at the core of the Shopee platform development. The team is made up of a group of passionate engineers from all over the world, striving to build the best systems with the most suitable technologies. Our engineers do not merely solve problems at hand; We build foundations for a long-lasting future. We don't limit ourselves on what we can or can't do; we take matters into our own hands even if it means drilling down to the bottom layer of the computing platform. Shopee's hyper-growing business scale has transformed most "innocent" problems into huge technical challenges, and there is no better place to experience it first-hand if you love technologies as much as we do.

About Team

The AI Solutions team builds and pioneers the future of AI-driven automation at Sea. We are the developers of Smart (Sea Multi-Agent Realization Platform) - the company's flagship AI agents platform that enables teams across the company to automate their workflows using large language model (LLM) agents. But Smart is just the beginning.

Our team is also spearheading a wide range of AI initiatives, especially within the engineering infrastructure domain, from internal developer tooling to intelligent operations. We believe that the future of infrastructure lies in intelligent automation, and we're committed to building it from the ground up.

We thrive in a fast-paced, sharing-first culture, with a strong emphasis on learning, creativity, and experimentation. We work hard and play hard, explore ideas on the cutting edge, and aim to pioneer bold, practical solutions to complex real-world problems. If you want to shape how AI changes engineering at scale - this is the place.

• Design and develop the Smart platform and other AI systems, covering all essential agent platform components - agent runtimes, toolchains, memory, orchestration, logging, planning, and sandboxing.
• Build scalable backend infrastructure to support agent-based workflows across the company.
• Collaborate with teams across departments - both tech and non-tech - to land and scale real-world AI use cases.
• Drive internal agent adoption in engineering infra by replacing traditional operations with intelligent agent workflows.
• Prototype and optimize agent architectures, including Reasoning and Action (ReAct) patterns, multi-step planning, and decision workflows.
• Work on platform reliability and observability to ensure our systems are performant, debuggable, and production-ready.
• Support operations and development work in a healthy balance - you'll gain experience in shipping features and running real services.
• Build full-stack systems (primarily backend, with occasional frontend) that integrate well into internal ecosystems.
• Manage and operate supporting infrastructure, including vector stores, retrieval systems (RAG), and middleware components.
• Continuously experiment, learn, and bring in the latest advancements from the AI/agent ecosystem into production.

• Bachelor's degree or higher in Computer Science, Engineering, or a related field.
• 2+ years of relevant experience in software development - or fresh graduates with strong fundamentals and hunger to learn.
• Strong programming skills in Python (primary) - familiarity with Golang is a plus.
• Solid CS fundamentals - algorithms, data structures, networking, systems, and architecture.
• Backend experience designing cloud-ready services using databases, queues, caching, etc.
• Familiarity with modern AI agent frameworks like LangChain, LangGraph, or strong interest in learning them.
• Strong problem-solving mindset and ability to navigate ambiguity with curiosity and creativity.
• Willingness to work full stack - we prioritize backend but value well-rounded engineers.
• General understanding of distributed systems and cloud-native principles (e.g. the twelve-factor app), including how services are deployed, scaled, and load-balanced in a containerized environment.
• Passion for building AI systems that people actually use.

Skills below are optional but preferred:

• Experience building AI-powered platforms, assistants, or automation tools.
• Familiarity with agent patterns like ReAct (Reasoning and Action), tool chaining, or multi-agent orchestration.
• Knowledge of RAG systems, vector databases, or prompt tuning.
• Prior experience in developer tools, internal platforms, or large-scale systems.
• Exposure to observability, debugging, incident workflows, or service reliability.

• Design and architect end-to-end AI and Machine Learning solutions for clients.
• Evaluate and recommend appropriate AI technologies, frameworks, and platforms.
• Develop scalable, robust, and efficient AI/ML models and algorithms.
• Guide the development and deployment of AI solutions across various industries.
• Collaborate with data scientists, engineers, and business stakeholders to define requirements.
• Create prototypes and proof-of-concepts for AI applications.
• Conduct feasibility studies and technical assessments for AI initiatives.
• Ensure the ethical and responsible application of AI technologies.
• Develop and document AI solution architectures and implementation plans.
• Provide technical leadership and mentorship to AI/ML development teams.
• Stay abreast of the latest advancements and trends in AI and emerging technologies.
• Troubleshoot and optimize deployed AI systems.

• Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Minimum of 7 years of experience in AI/ML development and solution architecture.
• Proven expertise in designing and implementing complex AI/ML systems.
• Deep understanding of machine learning algorithms, deep learning frameworks, and AI concepts.
• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and their AI services.
• Proficiency in programming languages such as Python, R, or Java.
• Familiarity with big data technologies (e.g., Spark, Hadoop).
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and presentation skills, with the ability to explain complex technical concepts.
• Ability to work independently and lead technical initiatives in a remote environment.
• Experience with MLOps and deployment strategies is a plus.

• Design and architect end-to-end AI and machine learning solutions.
• Evaluate and select appropriate AI/ML tools, frameworks, and platforms.
• Develop and prototype AI models and algorithms for various applications.
• Collaborate with data scientists and engineers to implement AI solutions.
• Ensure scalability, reliability, and performance of AI systems.
• Provide technical leadership and guidance to development teams.
• Identify new opportunities for leveraging AI to solve business challenges.
• Stay current with the latest advancements in AI and machine learning research.
• Develop and document architectural designs and technical specifications.
• Mentor junior team members and foster a culture of innovation.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Extensive experience in designing and implementing AI/ML solutions.
• Deep understanding of machine learning algorithms, NLP, computer vision, and deep learning.
• Proficiency in programming languages such as Python and relevant AI libraries (TensorFlow, PyTorch, scikit-learn).
• Experience with cloud platforms (AWS, Azure, GCP) and their AI services.
• Knowledge of MLOps principles and best practices.
• Strong analytical and problem-solving skills.
• Excellent communication and presentation skills, with the ability to explain complex technical concepts.
• Experience in a hybrid work environment.
• Ability to lead technical initiatives and collaborate effectively.

• Designing end-to-end AI/ML solutions, from data ingestion and preprocessing to model training, deployment, and monitoring.
• Evaluating and recommending AI/ML frameworks, tools, and technologies.
• Collaborating with data scientists to develop and optimize machine learning models.
• Developing proof-of-concepts (POCs) and prototypes to demonstrate the feasibility of AI solutions.
• Providing technical leadership and guidance to development teams.
• Ensuring the scalability, reliability, and performance of AI systems.
• Translating business requirements into technical specifications for AI projects.
• Staying current with advancements in AI, machine learning, and deep learning research.
• Advising on data governance, ethics, and best practices in AI implementation.
• Communicating technical concepts and strategies to both technical and non-technical audiences.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Minimum of 7 years of experience in software development or data science, with at least 4 years focused on AI/ML solutions architecture.
• Extensive experience with Python, R, and common AI/ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong understanding of various machine learning algorithms (e.g., supervised, unsupervised, deep learning) and their applications.
• Experience with cloud platforms (AWS, Azure, GCP) and their AI/ML services.
• Proficiency in data modeling, database technologies, and big data processing frameworks.
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and presentation skills.
• Ability to work effectively in a hybrid environment, collaborating both in-person and remotely.
• Experience in MLOps and deploying models into production is a plus.

• Collaborate with clients and internal stakeholders to understand business requirements and translate them into AI solution designs.
• Architect end-to-end AI and machine learning solutions, considering data, algorithms, infrastructure, and deployment.
• Evaluate and select appropriate AI/ML technologies, platforms, and tools for specific client needs.
• Design scalable and robust cloud-based AI infrastructure, leveraging services from major cloud providers (AWS, Azure, GCP).
• Develop technical roadmaps and strategies for AI adoption and implementation.
• Provide technical leadership and guidance throughout the project lifecycle, from concept to deployment.
• Identify and mitigate technical risks associated with AI solutions.
• Communicate complex technical concepts clearly to both technical and non-technical audiences.
• Stay current with the latest advancements in AI, machine learning, and related technologies.
• Develop proof-of-concepts and prototypes to demonstrate the feasibility of proposed solutions.
• Ensure that AI solutions are designed for security, compliance, and ethical considerations.
• Collaborate with data scientists, engineers, and project managers to ensure successful project delivery.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, or a related field; or equivalent practical experience.
• Significant experience (7+ years) in software architecture, with a specialized focus (5+ years) on AI/ML solutions.
• Deep understanding of various AI/ML algorithms, techniques, and their practical applications.
• Extensive experience with cloud platforms (AWS, Azure, GCP) and their AI/ML services.
• Proficiency in programming languages commonly used in AI development (e.g., Python).
• Strong knowledge of data engineering, data warehousing, and big data technologies.
• Experience designing and implementing scalable, distributed systems.
• Excellent analytical, problem-solving, and critical-thinking skills.
• Exceptional communication, presentation, and stakeholder management skills.
• Ability to work independently and lead technical discussions in a remote environment.
• Experience with MLOps principles and practices is a plus.