Early Career Consult Program - Associate AI Engineer

Kyndryl • Dallas, TX

1d • Hybrid

About The Position

The Associate AI Engineer is an entry-level technical role supporting the design, development, deployment, and optimization of artificial intelligence, machine learning, analytics, and data-driven solutions. Working alongside experienced AI Engineers, Data Engineers, Data Scientists, Solution Architects, and business stakeholders, you will develop foundational skills in modern AI technologies, cloud platforms, software engineering, data engineering, analytics, and responsible AI practices.

Join Kyndryl and gain the trust, autonomy and teamwork to help define what comes next.

This role offers two areas of specialization within a common AI Engineering career framework:
AI Engineering Path
Build, test, and deploy AI-powered applications, generative AI solutions, intelligent agents, and machine learning capabilities that help solve business challenges and improve user experiences.
Data Engineering & Analytics Path
Prepare, manage, and optimize the data foundations that power AI, machine learning, analytics, and business intelligence solutions.
Candidates may begin in one focus area but will gain exposure to both disciplines as they develop their careers.

Requirements

• Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, Mathematics, Statistics, or a related discipline, or equivalent practical experience.
• 0-3 years of experience in software engineering, AI, machine learning, data engineering, analytics, or related technical fields.
• Working knowledge of Python or a similar programming language.
• Basic understanding of software development principles and problem-solving techniques.
• Familiarity with data structures, databases, APIs, cloud technologies, or modern development tools.
• Strong analytical, communication, collaboration, and documentation skills.
• Demonstrated curiosity and interest in emerging AI and data technologies.

Nice To Haves

• Exposure to Microsoft Azure, Azure AI Services, Azure OpenAI, AWS, Google Cloud, or similar platforms.
• Familiarity with AI, machine learning, generative AI, large language models, retrieval systems, or intelligent automation.
• Exposure to SQL, data analysis, data preparation, ETL/ELT, or data pipeline concepts.
• Experience with Git, CI/CD, Docker, DevOps, MLOps, or software engineering practices.
• Knowledge of visualization, reporting, or business intelligence tools.
• Relevant certifications in AI, cloud, data, or software engineering technologies.
• Understanding of responsible AI, data privacy, security, and governance principles.

Responsibilities

• Collaborate with technical teams and business stakeholders to understand requirements and support AI-enabled business outcomes.
• Contribute to the design, development, testing, deployment, and support of AI and data solutions.
• Participate in agile development practices, code reviews, troubleshooting, and continuous improvement activities.
• Document technical solutions, data sources, workflows, assumptions, and operational procedures.
• Apply security, governance, privacy, compliance, and responsible AI standards in all work.
• Build expertise in modern cloud, AI, and data technologies through hands-on learning and project experience.
• Support the development of AI, machine learning, and generative AI applications.
• Assist in building intelligent agents, conversational experiences, retrieval-augmented generation (RAG) solutions, and AI-assisted workflows.
• Develop and maintain application components, APIs, integrations, and automation capabilities.
• Help evaluate model performance, response quality, scalability, and user experience.
• Participate in testing, monitoring, and optimization of AI solutions.
• Learn modern AI frameworks, cloud AI services, and software engineering practices.
• Collect, cleanse, transform, validate, and prepare structured and unstructured data for AI and analytics solutions.
• Use SQL, Python, and approved platform tools to query, manipulate, and analyze data.
• Assist with exploratory data analysis to identify patterns, trends, insights, and data quality issues.
• Support the creation of data workflows, reusable scripts, data pipelines, and data preparation processes.
• Help prepare training data, features, and evaluation datasets for machine learning and AI initiatives.
• Contribute to data governance, quality, lineage, and operational excellence practices.

Benefits

• flexible, supportive environment where your well-being is prioritized and your potential can thrive
• trust, autonomy and teamwork
• dynamic, hybrid-friendly culture that supports your well-being and empowers you to grow
• Be Well programs are thoughtfully designed to support your financial, mental, physical, and social health
• impactful work that powers the systems our customers rely on every day
• powerful tools to chart your career path
• personalized development goals aligned with your ambitions
• continuous feedback to keep you inspired and on track
• access to cutting-edge learning opportunities—from certifications with Microsoft, Google, and Amazon to coaching and hands-on experiences

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level