Senior AI Solutions Engineer Job at NTT DATA (Bangalore)

Job Description

The Senior AI Solutions Engineer at NTT DATA is responsible for developing and deploying AI models, ensuring secure integrations with enterprise systems, and optimizing data pipelines. This role requires advanced expertise in AI, machine learning, and cloud computing, along with strong communication skills to engage with stakeholders effectively. A bachelor's degree in a relevant field and 4-6 years of experience in AI solutions are required.

Job Responsibility

Actively participating in identifying high-value use cases, assessing solution feasibility, prototyping innovative ideas, and delivering successful pilot projects
Develop, fine-tune, and deploy AI models, including large language models (LLMs) such as GPT-4 or open-source equivalents
Design and implement effective prompt engineering strategies and optimizations to enhance AI accuracy, consistency, and reliability
Engage with internal stakeholders and clients to understand business needs, translating them into actionable AI solutions
Rapidly prototype, test, and iterate AI applications using advanced Python programming and relevant frameworks
Integrate AI solutions securely with existing enterprise systems (CRM, ERP, HRIS, finance platforms, collaboration software) via API development and integration
Build, maintain, and optimize end-to-end data pipelines to ensure accurate and timely data delivery for AI models
Manage structured and unstructured datasets, leveraging vector databases and semantic search to enhance knowledge management capabilities
Deploy, manage, and scale AI solutions within cloud computing environments (Azure, AWS, GCP), ensuring high availability, performance, and cost efficiency
Implement DevOps and MLOps practices, including automated deployment, testing, monitoring, and version control, to efficiently manage the AI model lifecycle
Ensure AI solutions adhere to industry standards and compliance regulations (GDPR, HIPAA), emphasizing security and privacy best practices
Identify and mitigate risks associated with AI deployments, proactively addressing ethical considerations, biases, and unintended consequences
Collaborate closely with business and functional teams to streamline processes through intelligent automation and deliver measurable business outcomes
Provide clear documentation of technical designs, project plans, and operational procedures
Contribute to the continuous improvement of AI best practices, methodologies, and internal frameworks
Stay abreast of the latest AI and machine learning developments, continuously evaluating emerging technologies and methodologies

Requirements

Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field
Advanced demonstrated experience (typically 4-6 years) developing, deploying, and maintaining AI and machine learning solutions in enterprise environments
Advanced expertise in AI model development, fine-tuning, and optimization using Python and relevant frameworks
Advanced demonstrated experience implementing prompt engineering methodologies and optimizing model performance
Advanced demonstrated experience in API development and secure integration of AI-driven solutions with enterprise systems and platforms
Advanced experience building robust data pipelines, managing structured/unstructured data, and leveraging vector databases
Practical experience deploying and scaling AI applications within cloud platforms (Azure, AWS, or GCP)
Advanced demonstrated success applying DevOps and MLOps best practices to manage AI model lifecycle and deployments efficiently
Advanced proven track record ensuring security, privacy, compliance, and responsible use of AI solutions within regulated environments
Advanced experience engaging directly with clients and stakeholders, translating business requirements into effective technical solutions
Advanced understanding of artificial intelligence, natural language processing (NLP), and machine learning principles
Advanced expertise in selecting, fine-tuning, and deploying large and small language models (LLMs/SLMs), such as OpenAI’s GPT series and open-source alternatives
Advanced proven experience with prompt engineering, prompt optimization, and AI model reliability and accuracy improvements
Advanced proficiency in Python programming
Advanced knowledge of additional programming languages (optional, but valuable): JavaScript / TypeScript
Java / C#
Advanced familiarity with full-stack software development, including frontend and backend integration, user experience considerations, and system interoperability
Robust knowledge of data pipeline development, data engineering concepts, and handling of structured and unstructured data
Advanced proficiency in cloud computing platforms (Azure, AWS, GCP), particularly in deploying, scaling, and managing AI workloads
Advanced knowledge of security, compliance, and risk management practices related to AI solutions
Advanced understanding of ethical AI considerations, bias mitigation, and responsible AI deployment
Demonstrated domain and business acumen, capable of aligning technical solutions with business strategies and processes for measurable impact
Excellent communication skills, ability to clearly articulate technical concepts to non-technical stakeholders
Advanced analytical problem-solving capabilities, organizational skills, and attention to detail
Ability to manage multiple projects simultaneously, prioritize tasks effectively, and meet deadlines in a fast-paced environment
Passionate about continuous learning, innovation, and keeping abreast of industry trends

Nice to have

Microsoft Certified: Azure AI Engineer Associate (preferred)
Microsoft Certified: Azure Solutions Architect Expert (preferred)
Microsoft Certified: Data Scientist Associate (preferred)
Microsoft Certified: Azure Data Engineer Associate (preferred)
Microsoft Certified: Power Platform Fundamentals (preferred)
Relevant certifications or training in Machine Learning, AI development, Data Analytics, and Cloud Computing (advantageous)
Advanced knowledge of additional programming languages (optional, but valuable): JavaScript / TypeScript
Java / C#

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