Some of the key responsibilities of this group include:

• Driving the adoption of emerging technologies to optimize and automate various business functions, keeping an AI-first approach with a digital experience.
• Enable best in class IT with enhanced cybersecurity measures to protect sensitive information and maintain regulatory compliance.
• Modernizing legacy systems and integrating disparate applications to improve interoperability and reduce technical debt.
• Collaborating with other departments and teams to align technology efforts with broader corporate objectives.
• Providing guidance and expertise on technology trends, best practices, and standards.

This team comprises professionals with diverse backgrounds in software engineering, data science, network architecture, and security. By fostering a culture of innovation and continuous improvement, the team strives to achieve its mission of making IBM the most productive company in the world.

Your role and responsibilities

Role Overview:

As an AI Engineer/SW Developer, you will be in a unique position to combine your strategic thinking with your technical skills in AI, machine learning, and data analytics.  You will apply your skills to help implement data-driven solutions that align with business goals. You will steer enterprise projects that improve decision-making, solve complex problems, and drive business growth. This role involves working with team members and stakeholders to translate data insights into actionable recommendations that deliver meaningful business impact.   

Key Responsibilities:

1. Implement AI, Data Science, and Technical Execution: 

• Support the design, implementation and optimization of AI-driven strategies per business stakeholder requirements.
• Design and implement machine learning solutions and statistical models, from problem formulation through deployment, to analyze complex datasets and generate actionable insights.
• Apply GenAI, traditional AI, ML, NLP, computer vision, or predictive analytics where applicable.
• Collect, clean, and preprocess structured and unstructured datasets.
• Help refine data-driven methodologies for transformation projects. 
• Learn and utilize cloud platforms to ensure the scalability of AI solutions. 
• Leverage reusable assets and apply IBM standards for data science and development.
• Apply ML Ops and AI ethics.

2. Strategic Planning & Execution

• Translate business requirements into technical strategies.
• Ensure alignment to stakeholders’ strategic direction and tactical needs.
• Apply business acumen to analyze business problems and develop solutions.
• Collaborate with stakeholders and team to prioritize work.

3. Project Management and Delivering Business Outcomes: 

• Manage and contribute to various stages of AI and data science projects, from data exploration to model development to solution implementation and deployment.
• Use agile strategies to manage and execute work.
• Monitor project timelines and help resolve technical challenges. 
• Design and implement measurement frameworks to benchmark AI solutions, quantifying business impact through KPIs. 

4. Communication and Collaboration: 

• Communicate regularly and present findings to collaborators and stakeholders, including technical and non-technical audiences.
• Create compelling data visualizations and dashboards.
• Work with data engineers, software developers, and other team members to integrate AI solutions into existing systems.

Required education

Bachelor's Degree

Required technical and professional expertise

Experience:

Hands-on Experience with AI/ML technologies and statistical modelling through coursework, projects, or past internships or full-time positions. Participation in AI/Data-related summits will be an added advantage ( eg. Kaggle/Hackathons)
 

• Experience with prompt engineering or fine-tuning LLMs. 
• Familiarity with tools like Lang Chain, Hugging Face Transformers, or OpenAI APIs. 
• Understanding of model evaluation metrics specific to LLMs

Technical Skills: 

• Proficiency in SQL and Python for performing data analysis and developing machine learning models.
• Experience and/or coursework in statistics, machine learning, generative and traditional AI.
• Knowledge of common machine learning algorithms and frameworks: linear regression, decision trees, Official notification