AI & Service Transformation / AI & サービス トランスフォーメーション
AI Technical Architect (AIST-223)
【About the team】
AI CoE is a startup group formed to address the Japan market AI needs with professionals consolidated in TCS Japan having deep AI expertise and continuous investment to expand the team (upto 25-member team) thru lateral and in-house training. TCS CEO has launched AI COE as a strategic unit with an initial team of 11 consultants. This team is poised for a big expansion to enable driving the need of AI adoption for TCS Japan customers and TCS Internal.
AI COE has 2 sub-units; AI Lab to solve unique customer problem using AI (PoT/PoC) and customize TCS AI solutions to incorporate Japanese language needs. AI Go To Market (GTM) unit to expand delivering AI use cases in platforms supporting AI.Cloud organization. We are team of researchers, data scientist, architects and consultants will perform the role of AI experts at TCS Japan to enable customers to achieve AI first business, provide strategic solutions for AI Dev & Sec Ops, provide end to end AI services and enable customers to build his AI office/organization. We aim to create a world class AI studio that will showcase AI solutions and co-creation space to work with customers for solving their problems. We are a diverse local team and work with TCS global members in hybrid approach.
We are looking for professionals with experience using AI in the following areas.
Technical Architect: >6 years of practical experience in architecting platform services for AI-related application
【Responsibilities】
・Envision, build, deploy and operationalize an end-to-end machine learning (ML) and AI pipeline
・Build a robust enterprisewide architecture for AI and collaborate with data scientists, data engineers, developers, operations and security
・Perform the following functions,
Requirement analysis: Analyzing what an organization needs and how AI can help.
Solution design: Designing AI solutions that are scalable, cost-effective, and in alignment with the organization’s goals.
Technology selection: Selecting the appropriate technology stack and tools that will be used to build the AI system.
Auditing: Conducting a comprehensive audit of AI tools and practices, including data, models, and software engineering, emphasizing continuous improvement. Establishing a feedback loop to evaluate AI services, facilitate model recalibration, and retrain models as needed.
Implementation: Overseeing the implementation of the AI system and ensuring it meets the organization’s requirements.
Monitoring and maintenance: Monitoring the performance of the AI system, troubleshooting issues, and ensuring the system is maintained and updated regularly.
・Has a holistic understanding of the business landscape, combined with a grasp of AI capabilities, allowing them to guide AI projects towards success
・To work in team collaboration with cross-functional teams, including technical architects, data engineers, and domain experts, to understand business requirements and develop effective AI solutions
・To be diligent in learning / scaling up in the areas of Data Science-AI with self-initiative towards career excellence
■Required
- Bachelor's degree in Computer Science, Software Engineering, or related fields (equivalent practical experience also acceptable)
- 5+ years of practical experience in designing and developing AI platforms (Azure is preferred)
- Ability to communicate at a business level in both English and Japanese, and to collaborate with internal and external stakeholders
■Preferred Qualifications
- Deep understanding and practical experience in AI-related technologies such as machine learning, deep learning, natural language processing, and computer vision
- AI architecture and pipeline planning. Understand the workflow and pipeline architectures of ML and deep learning workloads. An in-depth knowledge of components and architectural trade-offs involved across the data management, governance, model building, deployment and production workflows of AI is a must.
- Software engineering and DevOps principles, including knowledge of DevOps workflows and tools, such as Git, containers, Kubernetes and CI/CD.
- Data science and advanced analytics, including knowledge of advanced analytics tools (such as SAS, R and Python) along with applied mathematics, ML and Deep Learning frameworks (such as TensorFlow), ML techniques (such as random forest and neural networks) and developing large-scale models using AI frameworks such as TensorFlow, PyTorch, and Keras
- Experience in designing and developing AI systems using cloud platforms (Google, AWS, Azure, etc.)
- Knowledge of AI model operations and deployment (model optimization, monitoring, version control, etc.)
- Practical experience in large-scale data processing technologies (BigQuery, Spark, Hadoop, etc.)
- Knowledge of AI ethics and privacy, and ability to incorporate them into AI system design
- Ability to understand business requirements and design scalable and reliable AI platforms accordingly
- Experience in leading development teams and providing technical leadership in AI-related projects
- Effective communication skills with stakeholders
- Willingness to actively learn new AI technology trends and apply them to work
- Excellent communication and leadership skills, and ability to bridge technical and business teams
■雇用形態
正社員
労働時間区分：みなし労働時間制
みなし労働時間制の種類：専門業務型裁量労働制
一日当たりのみなし労働時間：8時間
*管理監督者グレードでの採用可能性あり
■給与
月給：経験・能力など考慮の上、当社規程により決定
裁量労働手当：あり(管理監督者グレードでの採用の場合は無し)
残業手当：なし
昇給：都度
賞与：あり
■勤務時間
9:00〜18:00
■休日/休暇
年次有給休暇（初年度10日 ※入社日によって異なる場合有）、完全週休2日制（土曜日・日曜日）、祝日、年末年始、慶弔休暇、育児・介護休業
■福利厚生
保険：健康・厚生年金・雇用・労災保険
制度：財形貯蓄・確定拠出年金・カフェテリアプラン（選択型法人会員福利厚生サービス）
※財形貯蓄・確定拠出年金は正社員のみ対象
在宅勤務とTCS本社（麻布台オフィス)出社のハイブリッド
*週に2-3回の出社の可能性あり
