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Your day at NTT DATA
The AI Solutions Engineer is a specialist role, responsible for actively participating in identifying high-value use cases, assessing solution feasibility, prototyping innovative ideas, and delivering successful pilot projects.
This role demands specialist technical knowledge, proficiency in software engineering, and capability in data engineering and cloud infrastructure. The AI Solutions Engineer is expected to ensure secure, reliable, and scalable integrations with existing enterprise platforms, systems, and data sources.
Key Responsibilities:
- 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.
To thrive in this role, you need to have:
- Demonstrated understanding of artificial intelligence, natural language processing (NLP), and machine learning principles.
- Expertise in selecting, fine-tuning, and deploying large and small language models (LLMs/SLMs), such as OpenAI’s GPT series and open-source alternatives.
- Specialist proficiency in Python programming, essential for rapid prototyping, integration, and model implementation. Python is the preferred language for AI; strong proficiency in Python is essential due to the extensive use of frameworks, libraries, and models.
- Knowledge of additional programming languages (optional, but valuable):
- JavaScript / TypeScript: Helpful if building frontend interfaces or web integrations.
- Java / C#: Beneficial for integrations with enterprise backend systems (e.g., ERP, CRM).
- 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.
- Proficiency in cloud computing platforms (Azure, AWS, GCP), particularly in deploying, scaling, and managing AI workloads.
- Experience with Microsoft Copilot Studio, Azure AI Foundry, and Semantic Kernel is highly desirable.
- Awareness and application of security, compliance, and risk management practices related to AI solutions.
- 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.
- Strong 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.
Academic Qualifications and Certifications:
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.
- 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)
Required Experience:
- Demonstrated experience (typically 4-6 years) developing, deploying, and maintaining AI and machine learning solutions in enterprise environments.
- Hands-on expertise in AI model development, fine-tuning, and optimization using Python and relevant frameworks.
- Demonstrated experience implementing prompt engineering methodologies and optimizing model performance.
- Demonstrated experience in API development and secure integration of AI-driven solutions with enterprise systems and platforms.
- 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).
- Demonstrated success applying DevOps and MLOps best practices to manage AI model lifecycle and deployments efficiently.
- Proven track record ensuring security, privacy, compliance, and responsible use of AI solutions within regulated environments.
- Experience engaging directly with clients and stakeholders, translating business requirements into effective technical solutions.
Workplace type:
Hybrid Working
Equal Opportunity Employer
NTT DATA is proud to be an Equal Opportunity Employer with a global culture that embraces diversity. We are committed to providing an environment free of unfair discrimination and harassment. We do not discriminate based on age, race, colour, gender, sexual orientation, religion, nationality, disability, pregnancy, marital status, veteran status, or any other protected category. Accelerate your career with us. Apply today