Early Career Consult Program - Associate AI Engineer
Who We Are
The Role
Your role
AI Engineering Path
Data Engineering & Analytics Path
Core Responsibilities (All Associates)
- 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.
AI Engineering Focus
- 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.
Data Engineering & Analytics Focus
- 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.
Required skills and experience
- 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.
Preferred Qualifications
- 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.
Common Skills
- Problem solving and analytical thinking
- Python programming
- Cloud platform fundamentals
- Technical documentation
- Collaboration and communication
- Responsible AI and technology governance
AI Engineering Skills
- Generative AI and large language model fundamentals
- AI application development
- Intelligent agents and automation
- Prompt engineering and AI solution testing
- APIs and system integration
- Machine learning concepts
Data Engineering & Analytics Skills
- SQL and data querying
- Data preparation and transformation
- Data quality and validation
- Exploratory data analysis
- Data pipelines and workflows
- Analytics and business insights generation
What Success Looks Like
As an Associate AI Engineer, you will:
- Deliver high-quality work with increasing independence and technical proficiency.
- Develop practical AI, software, and data engineering capabilities.
- Contribute to solutions that improve business outcomes and user experiences.
- Demonstrate sound judgment, curiosity, and continuous learning.
- Collaborate effectively across multidisciplinary teams.
- Consistently apply security, governance, privacy, and responsible AI practices in your work
The compensation for this position is $77,000 based on a full-time schedule. The pay or salary range is not below any applicable state, city or local minimum wage requirement.
This position will be eligible for Kyndryl's discretionary annual bonus program, based on performance and subject to the terms of Kyndryl's applicable plans. You may also receive a comprehensive benefits package which includes medical and dental coverage, disability, retirement benefits, paid leave, and paid time off. Note: If this is a sales commission eligible role, you will be eligible to participate in a sales commission plan in lieu of the annual discretionary bonus program. Applications will be accepted on a rolling basis.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
Being You
What You Can Expect
Get Referred!
Not included in the source posting: benefits.
Skills
Who can apply
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