Preserving Engineering Craft While Building AI-Native Teams

Engineering Leadership Roundtable | Burns Sheehan

About the event

At Burns Sheehan, our Engineering Leadership Roundtables are designed to bring together senior technology leaders for honest, peer-led conversations around the challenges shaping modern software engineering teams.

As AI continues to reshape engineering workflows, hiring strategies, software delivery, team structures and technical leadership, we wanted to create a space for engineering leaders to openly discuss what this shift actually looks like in practice.

This latest session focused on a key question many organisations are now facing:

How do you embrace AI-native engineering without losing engineering craft, quality, accountability and deep technical understanding?

Hosted by Grace Duffy alongside Manogna Machiraju, we were joined by:

• Manogna Machiraju, Head of Engineering @ ATG Entertainment (moderator)
• Rahat Khan, Senior Engineering Manager @ DeepL
• Pete Tsamouris, Former CTO & Founder Software Engineer @ Covecta
• Meng Muk, SVP Software Engineering @ Dexory
• Kimani Mbugua, VP, Head of Engineering @ Revantage UK
• Irene Guasch, Engineering Director @ Signal AI
• Ke Ren, Head of Engineering @ M-XR
• Colin Rouse, Engineering Director @ Currencycloud

Rather than presentations or panels, the discussion was intentionally small, interactive and discussion-led, allowing leaders to share real examples, practical challenges and honest experiences around AI adoption in engineering teams.

Read the full summary sheet here

Why we run these events

The technology landscape is evolving faster than ever, particularly across AI engineering, software architecture, platform engineering and technical leadership.

Whilst there’s no shortage of AI content online, many engineering leaders told us they wanted more opportunities for honest, practical conversations with peers facing the same challenges.

Our roundtables are designed to create exactly that.

We bring together senior leaders across Software Engineering, Product, Data & AI, Platform Engineering and Technology Leadership to discuss:

• AI adoption in software engineering teams

• Scaling engineering organisations

• Leadership and hiring challenges

• Engineering culture and productivity

• Software quality, resilience and security

• Team design and capability building

• Emerging technology trends shaping the future of engineering

The goal is simple:

Create valuable peer-to-peer conversations where technology leaders can learn from each other, challenge ideas and leave with practical insight they can apply inside their own organisations.

Key discussion themes and takeaways

AI is accelerating engineering output, but quality remains the challenge

One of the biggest themes from the room was that increased code generation does not automatically equal better engineering outcomes.

Leaders discussed the growing tension between:

• Speed vs quality

• Quantity vs maintainability

• AI-assisted productivity vs engineering understanding

A recurring point was that engineers still need to fully understand the systems and code they push into production, even when AI generates large parts of it.

Human judgment and accountability remain non-negotiable

Whilst AI tooling is becoming embedded into engineering workflows, the room was aligned on one point:

Accountability still sits with humans.

• Engineering oversight and governance

• Security and QA guardrails

• Human approval processes for AI-generated changes

• Critical thinking as a core engineering competency

• Maintaining strong engineering fundamentals in AI-native teams

The role of engineers is evolving rapidly

The roundtable explored how AI is reshaping expectations across different engineering levels.

Key themes included:

• Junior engineers often adapting fastest to AI-native workflows

• Senior engineers taking on more oversight and architectural responsibility

• Principal and Staff Engineers shifting further toward strategy, resilience, governance and business alignment

Hiring for adaptability, curiosity and problem-solving

The hiring discussion focused less on specific AI tools and more on underlying behaviours and competencies.

Many leaders highlighted the importance of:

• Curiosity and willingness to learn

• Strong engineering fundamentals

• Problem-solving ability

• Adaptability

• Communication and judgment

• Transparency around AI usage during interviews

Download the 2026 Technology Salary Guide

Alongside the discussion, we also shared insights from the Burns Sheehan 2026 Technology Salary Guide.

The guide covers:

• Software Engineering salary benchmarks

• AI and Machine Learning hiring trends

• Emerging AI-native engineering roles

• Product Engineering and Platform Engineering salaries

• Hiring market insights across London and the North

• How AI is reshaping engineering team structures and hiring priorities

Download your free copy here:

2026 Technology Salary Guide

Interested in future Engineering Leadership events?

We regularly host roundtables, networking events and leadership discussions across:

• Software Engineering

• Product & Agile Delivery

• Data & AI

• Platform Engineering & Infrastructure

• Technology Leadership

If you’d be interested in joining a future session, register your interest below or reach out to Grace Duffy for more information.