Ai engineering lead Work, Jobs in Tulse Hill, Gtl (with Salaries)

AI Engineering Lead
Normal Computing Corporation —London
- £250,000 - £340,000 a year
- Full-time
- Hybrid work
- Mentoring
- AI
- Leadership
AI Engineering Lead
TP ICAP —London
- Full-time
- AWS
- Analysis skills
- APIs
AI-First Engineering Transformation Lead
Hansen Technologies —London
- Full-time
- Microsoft Powerpoint
- DevOps
- Software development
5d
AI Transformation Leader (All Levels) - UK Wide
Concept AI Ltd —London
- £90,000 - £220,000 a year
- Full-time
- Hybrid work
- Management
- Supervising experience
- Machine learning
- Work from home
Quick apply
10d
Product Lead, AI Product Engineering - Capital Markets
Citi —London
- Full-time
- Project management
- Product management
- AI
- Employee assistance programme
- Employee discount
Tech Lead Manager (Software Engineering)
Which? —London
- £84,000 - £97,000 a year
- Hybrid work
- Management
- Engineering
- Leadership
Lead/Senior Lead Software Engineer - Agentic AI Engineering (Enterprise Asset Management)
IFS —London
- Full-time
- Hybrid work
- Azure
- Computer Science
- Engineering
Quick apply
5d
AI Product Lead
Quilter —London
- Full-time
- Doctoral degree
- Master's degree
- Project management
Applied AI Engineer
Revolut —London
- SQL
- Machine learning
- AI
Staff Software Engineer, AI Reliability Engineering
Anthropic —London
- £325,000 - £390,000 a year
- Hybrid work
- Bachelor's degree
- APIs
- AI
- Flexible schedule
IM&W Technical Delivery Lead, Technology Programme Delivery, Engineering, Technology & Transformation
Deloitte —London
- Hybrid work
- Azure
- PMP
- AWS
Technical Delivery Lead, Technology Programme Delivery, Engineering, Technology & Transformation
Deloitte —London
- Hybrid work
- Azure
- Java
- SQL
AI Adoption Lead
IFS —Staines-upon-Thames
- £150,000 - £175,000 a year
- Full-time
- Remote
- AI
- Leadership
- Annual leave
- Life insurance
Quick apply
7d
Member of Technical Staff - Applied AI Lead, Health
Microsoft —London
- £93,500 - £161,800 a year
- Full-time
- Management
- Computer Science
- Engineering
11d
Chief Technology Officer
OFGEM —London
- £81,000 - £117,800 a year
- Full-time
- Hybrid work
- Azure
- Presentation skills
- IT
- Flexible schedule
AI Engineering Lead
Substrate Bio —London
- Full-time
- Hybrid work
- Doctoral degree
- Master's degree
- APIs
- Annual leave
Quick apply
AI Tech Lead Developer
Elance India —London
- £300 - £400 a day
- Full-time
- Hybrid work
- DevOps
- Java
- Master's degree
Quick apply
Head of Product Engineering (Retail)
ClearCourse —London
- £80,000 - £100,000 a year
- Full-time
- Hybrid work
- Software development
- AI
- Employee discount
Quick apply
Machine Learning Engineering & Applied AI ML Lead - Vice President
JPMorganChase —London
- Full-time
- Computer Science
- Engineering
- AWS
Senior Manager, Insurance, AI Delivery Lead, Engineering AI & Data, Technology and Transformation
Deloitte —London
- Hybrid work
- Java
- Project management
- Agile

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AI Engineering Lead

Normal Computing Corporation
London

Apply Now

Job details

Full-time
£250,000 - £340,000 a year

Qualifications

Mentoring
AI
Leadership
Debugging

Full job description

About Normal Computing

Normal Computing builds silicon that turns thermal noise from an obstacle into a computational resource. Conventional chips spend most of their energy forcing determinism onto physics; ours compute with it. Stochastic, in-memory, asynchronous: the result is 10-100× more AI inference per dollar, per watt.

We co-design the full stack: AI-native EDA systems in production with the world's largest semiconductor companies, and the advanced ASICs they make possible. Backed by $85M+ from the world's leading deep-tech investors and built by scientists, engineers, and operators from the labs that built modern computing.

Normal works as one team across New York, Silicon Valley, London, Copenhagen, and Seoul. We hire people who want the hardest version of their craft, across every discipline, at every seniority.

The Role

As our AI Engineering Lead, you will lead a team of engineers building systems for AI-native EDA and advanced hardware workflows. This work sits at the intersection of applied AI, ML systems, agents, model evaluation, software engineering, and semiconductor domain complexity.

You will be responsible for setting technical direction, managing execution, developing engineers, and staying close to the implementation details that determine whether these systems work in practice. The team is building AI systems where correctness, traceability, and reliability matter, especially when agents are operating against formal or highly structured engineering problems.

This is a hands-on leadership role for someone who has grown from strong individual contribution into technical leadership or management. You should be comfortable moving between architecture, model behavior, evaluation, implementation tradeoffs, hiring, and team development. The strongest candidates will have built meaningful AI systems in technical domains where models need to operate against real constraints.

What You'll Own

Team Leadership: Lead and manage a team of AI engineers; hire, mentor, and develop strong engineers as the team scales.
Technical Direction: Set direction for applied AI and ML engineering work across Normal's product and platform areas.
Hands-On Depth: Stay hands-on with architecture, implementation decisions, code review, debugging, evaluation, and system design; contribute directly to critical technical work when needed.
Structured AI Systems: Build AI systems that operate against structured engineering workflows, formal specifications, and objective correctness signals.
Cross-Functional Translation: Partner with product, engineering, research, and leadership to translate ambiguous goals into clear technical plans.
Execution Model: Help define the operating rhythm, engineering standards, and execution model for the AI team; identify technical risks early and balance model quality, reliability, product impact, and velocity.

What Makes You a Great Fit

Direct experience across AI engineering, ML engineering, applied AI, production ML systems, or AI infrastructure
Experience as a technical lead, staff-level IC, engineering manager, or hybrid lead/manager for AI/ML engineering teams
Track record of building and shipping meaningful AI systems in production or high-impact technical environments
Strong hands-on technical ability, with comfort reviewing designs, debugging systems, and contributing directly when needed
Experience working with LLMs, RL, agents, model evaluation, inference systems, optimization, or ML infrastructure
Ability to create clarity in ambiguous technical areas and help teams move quickly without losing rigor
Experience managing or mentoring engineers while maintaining close technical involvement
Strong ownership mindset and ability to operate in a small, high-caliber team

Bonus Points

Experience applying agentic systems and AI to EDA, semiconductor workflows, circuits, hardware design, verification, or other advanced engineering domains
Experience leading AI work in a startup, research-heavy, or zero-to-one product environment
Experience hiring and scaling small, senior engineering teams

Equal Employment Opportunity Statement

Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected status.

Accessibility Accommodations

Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability, please let us know at [email protected].

Privacy Notice

By submitting your application, you agree that Normal Computing may collect, use, and store your personal information for employment-related purposes in accordance with our Privacy Policy.

Compensation Range: $250K - $340K

Apply Now

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