AI & Data Ethics Technical Lead

Posted 7 Days Ago
Be an Early Applicant
4 Locations
In-Office or Remote
Junior
Information Technology
The Role
As the AI & Data Ethics Technical Lead, you will enhance Kainos' AI capabilities, develop demos of Responsible AI techniques, and support data & AI trust in customer projects.
Summary Generated by Built In
Join Kainos and Shape the Future 

At Kainos, we’re problem solvers, innovators, and collaborators - driven by a shared mission to create real impact. Whether we’re transforming digital services for millions, delivering cutting-edge Workday solutions, or pushing the boundaries of technology, we do it together.

We believe in a people-first culture, where your ideas are valued, your growth is supported, and your contributions truly make a difference. Here, you’ll be part of a diverse, ambitious team that celebrates creativity and collaboration.

Ready to make your mark? Join us and be part of something bigger.

As Data & AI Ethics Technical Lead, you will play a critical role in enhancing Kainos’ technical abilities to mitigate AI risks. You will be expected to learn and build demos around key Responsible AI techniques such as post-hoc explainability techniques, bias mitigation techniques, privacy enhancing technologies (PETs) and guardrails for large language models.

A core part of the role will involve bringing Data & AI trust and assurance subject matter expertise to customer projects, sharing best practices as well as directly influencing and delivering the ethical dimensions of data and AI solutions. You will be expected to explore new Responsible AI techniques and share your learnings with the wider Data & AI practice. Constant horizon-scanning for the latest techniques and self-directed learning will be central to this role. In addition, there will be opportunity to engage in industry engagements, pre-sales and marketing support.

You will be part of the Responsible AI team and work together with our team and wider Data Scientists and Data Engineers to evolve our approach. This role is a unique opportunity to have a real positive impact on the development of our technology and to evolve your own skills. We are looking for someone with a strong technical background in data science and a passion for Responsible AI.

MINIMUM (ESSENTIAL) REQUIREMENTS:

· A minimum of a 2.1 degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, Statistics or in a similar highly quantitative field

· Foundational knowledge of Responsible AI in a data & AI context including understanding the definitions and measures of fairness, understanding concepts and principles of bias and how they might apply to AI solutions, considerations for choosing an appropriate definition of fairness, and awareness of libraries and tools available

· Demonstrable experience with dataset feature selection, data management and visualisation, AI/ml, pre-training techniques, explainable models, and post-hoc techniques as well as AI testing and validation experience such as pre-deployment testing, post-deployment monitoring, and real-time testing

· A proven ability to solve complex problems with demonstrable ability to learn new concepts, think critically, and incorporate new perspectives

· Collaborative and growth mindset, along with demonstrable experience of contributing a positive impact to team ethos

DESIRABLE:

· An advanced degree in Computer Science, Machine Learning, Operational Research, Statistics or in a similar highly quantitative field.

· Experience with ML fairness approaches and toolkits

· Experience with risk-based ethics and Responsible AI frameworks or developing Responsible AI policy or ethical data and AI processes and practices

· Experience designing and running tests for algorithmic bias, disparate impact, and performance and using fairness metrics and mitigation techniques

· Experience with creating model guardrails and ethical constraints, such as the ability to implement policy-based guardrails for AI systems and design fail-sale mechanisms

· Experience creating citations and references for RAG systems, as well as cards, data sheets, and decision logs

· Knowledge of Responsible AI practices, trends, and principles in trust, assurance, and ethics and/or experience working in Responsible AI on the customer-delivery side

· Experience creating accelerators, frameworks, decision trees or other tools to scale AI adoption

· Experience contributing to writing proposals, working on bids, or other sales activity where you have helped shape offerings and develop opportunities

Embracing our differences   

At Kainos, we believe in the power of diversity, equity and inclusion. We are committed to building a team that is as diverse as the world we live in, where everyone is valued, respected, and given an equal chance to thrive.   We actively seek out talented people from all backgrounds, regardless of age, race, ethnicity, gender, sexual orientation, religion, disability, or any other characteristic that makes them who they are.   We also believe every candidate deserves a level playing field. 

Our friendly talent acquisition team is here to support you every step of the way, so if you require any accommodations or adjustments, we encourage you to reach out. 

We understand that everyone's journey is different, and by having a private conversation we can ensure that our recruitment process is tailored to your needs.


Top Skills

Ai Testing And Validation
Artificial Intelligence
Data Science
Machine Learning
Responsible Ai Techniques
Statistics
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The Company
HQ: Belfast
2,999 Employees
Year Founded: 1986

What We Do

At Kainos we use technology to solve real problems for our customers, overcome big challenges for businesses, and make people’s lives easier.

We build strong relationships with our customers and go beyond to change the way they work today and the impact they have tomorrow.

Our two specialist business areas, Digital Services and the Workday Practice, work globally for clients across healthcare, commercial and the public sector to make the world a little bit better, day by day.

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