AI Engineer Salary London 2026: Full Breakdown

You’re trying to figure out if an AI engineer salary in London in 2026 is actually worth the rent, the commute, the taxes, and the stress of passing six technical interviews while someone says “we move fast here” with a straight face.

London AI jobs can look amazing from the outside. £90k here, £130k there, equity mentioned in tiny font, bonus “discretionary,” and recruiters sliding into your inbox with roles that sound senior but pay like mid-level.

So let’s break it down properly.

AI Engineer Salary London 2026: Quick Answer#

In 2026, a typical AI engineer salary in London is likely to sit around:

1. Junior AI Engineer: £45k to £65k
2. Mid-level AI Engineer: £65k to £95k
3. Senior AI Engineer: £95k to £140k
4. Staff or Lead AI Engineer: £130k to £180k
5. Principal AI Engineer or AI Architect: £160k to £230k+
6. AI Research Scientist at top firms: £120k to £250k+, depending on publications, PhD, and niche expertise
7. AI Engineer in finance or big tech: £120k to £250k total compensation is realistic for strong candidates

That last phrase matters: total compensation.

Base salary is only one part of the money. In London, AI engineers can also receive:

• Annual bonus
• Stock or RSUs
• Sign-on bonus
• Pension contributions
• Private health insurance
• Training budget
• Remote work allowance
• Relocation support

A £105k base salary at a bank can beat a £120k startup offer if the bank gives a 20% bonus, better pension, and more stability.

On the other hand, a £95k startup role with meaningful equity might be worth it if the company is growing fast, but only if the equity terms are clear and realistic.

Why London AI Engineer Salaries Are Still High In 2026#

London is expensive, yes. But it is also one of Europe’s strongest AI job markets.

AI hiring is being pushed by four big forces:

1. Banks and fintechs are automating risk, fraud, trading, and customer service
2. Startups are building AI products around agents, copilots, search, and workflow automation
3. Large companies are adding machine learning into every internal system
4. Regulation is creating demand for safer, explainable AI

Companies like Revolut, Wise, Monzo, Barclays, HSBC, JPMorgan, Bloomberg, Google DeepMind, Meta, Amazon, Microsoft, Spotify, Booking.com, Adyen, Klarna, SAP, Siemens, Bosch, Airbus, and ING all compete for people who can build reliable AI systems.

Some of those firms are not headquartered in London, but they either hire there, run UK offices, or compete in the same European talent market.

That competition matters.

A strong AI engineer in London may also get interest from:

• Berlin, where senior AI roles often land around €85k to €130k
• Amsterdam, where companies like Adyen, Booking.com, and ING may pay €80k to €140k
• Stockholm, where Spotify and Klarna can reach €75k to €130k
• Madrid or Barcelona, where BBVA, Telefónica, Inditex, and Glovo-type firms may offer €55k to €100k
• Paris, where AI and data roles can range from €65k to €140k
• Dublin, where big tech roles may reach €90k to €160k

London still tends to pay higher cash compensation than most EU cities, especially in finance, big tech, and AI research.

But the cost of living eats fast.

AI Engineer Salary London 2026 By Experience Level#

Let’s make this practical.

Your salary depends heavily on experience level, not just years worked. A “senior” title at a small startup may map to mid-level at Google DeepMind or Meta.

Entry-Level AI Engineer Salary London

Expected range in 2026: £45k to £65k base

This is usually for people with:

• 0 to 2 years of experience
• Strong Python
• Some machine learning projects
• Good SQL
• Basic cloud knowledge
• A master’s degree, bootcamp, PhD start, or strong portfolio

Common job titles:

• Junior AI Engineer
• Graduate Machine Learning Engineer
• Junior Data Scientist
• Applied AI Engineer
• NLP Engineer, Junior
• Computer Vision Engineer, Junior

At this stage, you are not usually being paid for big architecture decisions. You are being paid to ship supervised tasks, clean data, evaluate models, write decent code, and learn quickly.

You may work on:

1. Prompt evaluation
2. Data pipelines
3. Model fine-tuning
4. API integration
5. Feature engineering
6. Internal copilots
7. Reporting and dashboards
8. Model monitoring basics

A realistic London graduate AI offer might be £50k base plus 5% bonus at a bank, or £55k base plus small equity at a startup.

If you are seeing £35k AI engineer jobs in London, be careful. Sometimes those are really data analyst jobs with “AI” added to the title.

Mid-Level AI Engineer Salary London

Expected range in 2026: £65k to £95k base

Mid-level is where the market gets interesting.

You can work independently, own model components, speak to product teams, and debug production issues without needing constant help.

Typical profile:

• 2 to 5 years of experience
• Strong Python and ML frameworks
• Experience with cloud platforms
• Some MLOps knowledge
• Can evaluate tradeoffs
• Can deploy models into production
• Understands model performance and business impact

Common tools:

• Python
• PyTorch
• TensorFlow
• scikit-learn
• Hugging Face
• LangChain or similar AI app frameworks
• Docker
• Kubernetes basics
• AWS, GCP, or Azure
• MLflow, Weights & Biases, or similar
• PostgreSQL, BigQuery, Snowflake, or Databricks

Mid-level AI engineers in London may see:

• £70k to £85k at many startups
• £80k to £100k at fintechs
• £85k to £110k total comp at large companies
• £95k+ if they have niche skills in LLMs, recommender systems, fraud, or quant-style ML

This is also where negotiation starts to matter a lot.

A recruiter may open with £75k. The real budget might be £90k. If you already have an offer from another firm, suddenly the “band is fixed” becomes “let me check with the hiring manager.”

Funny how that works.

Senior AI Engineer Salary London 2026#

Expected range in 2026: £95k to £140k base

Senior AI engineers are paid for judgment.

At this level, you are not just training a model and calling it a day. You are asking:

• Should we use an LLM here at all?
• Can we solve this with search plus rules?
• What happens when the model fails?
• How do we measure quality?
• How do we reduce latency?
• What is the cost per request?
• Can legal and compliance approve this?
• Can this system survive real users?

Senior AI engineers in London often own production systems that affect revenue, risk, or customer experience.

You may work on:

1. Fraud detection models for fintech
2. AI agents for customer support
3. Search and ranking systems
4. Personalisation engines
5. Internal developer tools
6. Credit risk models
7. Document intelligence
8. Voice and chatbot systems
9. Forecasting systems
10. AI safety and evaluation tooling

A senior AI engineer at a London fintech like Revolut or Wise may receive something like:

• £100k to £135k base
• Bonus or performance pay
• Equity depending on level
• Strong pension and benefits

At a large US tech company in London, a senior ML or AI engineer might see:

• £120k to £160k base
• RSUs worth £40k to £100k+ per year
• Bonus around 10% to 20%
• Total compensation that can pass £200k

At AI research-heavy firms, compensation varies wildly. A strong candidate with a PhD, publications, and production engineering skill can be in a completely different market from a general software engineer who has added LLM APIs to a product.

Staff AI Engineer Salary London

Expected range in 2026: £130k to £180k base

Staff AI engineers are force multipliers.

You influence multiple teams, set technical direction, mentor seniors, and stop expensive mistakes before they happen.

You are likely expected to:

• Define AI architecture
• Review model design
• Choose build versus buy
• Set evaluation standards
• Improve reliability
• Partner with security and legal
• Help hire other engineers
• Influence senior leadership
• Turn vague AI ideas into shippable systems

This is where business impact becomes very visible.

A staff AI engineer who saves a bank millions in fraud losses, or helps a SaaS product add a profitable AI feature, can justify a high salary.

London staff-level AI total compensation can reach:

• £150k to £220k in fintech
• £180k to £280k in big tech
• £130k to £200k in strong startups
• £160k to £250k+ in finance, depending on bonus

Principal AI Engineer Or AI Architect Salary London

Expected range in 2026: £160k to £230k+ base

Principal roles are less common, and the interview bar is high.

You are judged on:

1. Depth in machine learning
2. System design
3. Product sense
4. Cost control
5. Security awareness
6. AI governance
7. Leadership without needing a manager title
8. Evidence of previous large-scale impact

This is not “I made a chatbot.”

This is more like:

• “I designed the AI platform used by 15 product teams”
• “I reduced inference costs by 40%”
• “I led migration from prototype notebooks to production services”
• “I created evaluation systems for regulated AI products”
• “I built ranking models that improved revenue by 8%”

At this level, total compensation can be huge if you are in the right company.

In London finance or big tech, principal AI engineers can see £220k to £350k+ total compensation. In rare cases, more.

AI Engineer Salary London 2026 By Company Type#

Not every AI job pays the same. The company type can change your offer by £50k or more.

Big Tech And AI Labs

Examples:

• Google DeepMind
• Meta
• Amazon
• Microsoft
• Apple
• NVIDIA
• OpenAI-style AI labs with London hiring
• Spotify for ML-heavy product roles
• SAP for enterprise AI roles

Expected London ranges:

• Mid-level: £85k to £130k base
• Senior: £120k to £170k base
• Staff: £150k to £220k base
• Total comp can reach £180k to £350k+

These companies usually pay well because they compete globally.

They also test hard.

Expect interviews on:

1. Coding
2. Machine learning fundamentals
3. System design
4. ML system design
5. Product thinking
6. Research depth, for some roles
7. Behavioural examples

The upside is pay, prestige, quality coworkers, and strong infrastructure.

The downside is competition, slower promotions, and sometimes narrow ownership.

Fintech And Banking

Examples:

• Revolut
• Wise
• Monzo
• Starling
• Barclays
• HSBC
• JPMorgan
• Goldman Sachs
• Bloomberg
• ING
• BBVA, for European comparison
• Adyen, if comparing Amsterdam fintech pay

Expected London ranges:

• Mid-level: £75k to £110k
• Senior: £100k to £150k
• Staff or lead: £140k to £220k total comp
• Quant-style ML or trading-adjacent roles can go higher

Finance pays well because AI affects money directly.

Common use cases:

• Fraud detection
• Anti-money laundering
• Credit scoring
• Market data analysis
• Risk modelling
• Customer support automation
• Document processing
• Personal finance insights
• Trading signals, in some firms

These jobs often require stronger risk awareness.

If you say “the model is probably fine” in a regulated bank interview, that is not ideal.

You should be ready to discuss:

• Bias
• Explainability
• Monitoring
• Audit trails
• Data privacy
• Model drift
• Human review
• Rollback plans

Startups And Scaleups

Expected London ranges:

• Junior: £45k to £65k
• Mid-level: £65k to £95k
• Senior: £90k to £130k
• Staff or founding AI engineer: £110k to £170k, sometimes with equity

Startups can be brilliant or chaotic. Often both before lunch.

The salary may be lower than big tech, but you might get:

• More ownership
• Faster promotions
• Equity
• Direct access to founders
• Less bureaucracy
• A chance to build from scratch

But be careful with equity.

Ask:

1. What percentage of the company does this represent?
2. What is the strike price?
3. What is the vesting schedule?
4. Is there a one-year cliff?
5. What was the last valuation?
6. How much runway does the company have?
7. Is there refresh equity?
8. What happens if the company is acquired?

A £120k role with mystery equity is not automatically better than a £135k role with clean bonus and pension.

AI Engineer Salary London 2026 By Skill Set#

Your salary is partly tied to what kind of AI problems you can solve.

Some skills pay more because they are harder to hire for.

LLM Engineer Salary London

Expected range:

• Mid-level: £75k to £110k
• Senior: £105k to £155k
• Staff: £140k to £220k total comp

LLM engineers build products around large language models.

Common work:

• Retrieval-augmented generation
• AI agents
• Prompt evaluation
• Fine-tuning
• Tool calling
• Guardrails
• Document search
• Cost and latency optimisation
• Model routing
• Human feedback loops

In 2026, companies are more careful than they were during the early AI hype years.

They do not just want someone who can call an API. They want someone who can ship a system that users trust.

Good LLM engineers know:

• When RAG is enough
• When fine-tuning makes sense
• How to test hallucinations
• How to create eval sets
• How to reduce token spend
• How to handle private data
• How to monitor outputs
• How to build fallback flows

If you can show this in a portfolio, you can negotiate better.

Machine Learning Engineer Salary London

Expected range:

• Mid-level: £70k to £105k
• Senior: £100k to £150k
• Staff: £135k to £210k total comp

Machine learning engineers are often more production-focused than data scientists.

They take models from notebook to service.

Hiring teams look for:

1. Python
2. Software engineering habits
3. Model training
4. Data pipelines
5. Deployment
6. Monitoring
7. Feature stores
8. Batch and real-time inference
9. Testing
10. Cloud infrastructure

A strong ML engineer who can write clean code, understand model behaviour, and work with platform teams is valuable.

A weaker candidate who only knows notebooks may struggle to reach senior pay.

AI Research Scientist Salary London

Expected range:

• Research scientist: £90k to £160k
• Senior research scientist: £130k to £220k
• Top-tier specialist: £200k to £300k+ total comp

Research roles are different.

They may require:

• PhD in machine learning, AI, computer science, statistics, maths, or related field
• Publications at NeurIPS, ICML, ICLR, ACL, CVPR, or similar
• Strong maths
• Original research ability
• Coding skill
• Ability to collaborate with engineering teams

Google DeepMind and similar AI research groups can pay extremely well, but the bar is high.

You need proof, not just interest.

MLOps Engineer Salary London

Expected range:

• Mid-level: £70k to £100k
• Senior: £95k to £140k
• Lead: £125k to £180k total comp

MLOps is one of the best salary paths if you like engineering more than model theory.

Companies have realised that AI demos are easy. Reliable AI systems are hard.

MLOps engineers handle:

• Model deployment
• CI/CD for ML
• Feature pipelines
• Model registries
• Monitoring
• Infrastructure
• Data quality checks
• Inference scaling
• Cost optimisation
• Security controls

This skill set is valuable in large companies like Siemens, SAP, Bosch, Airbus, and ING, where production reliability matters more than flashy demos.

AI Engineer Salary London Compared With Europe#

London usually beats most European cities for AI salary, but not always after tax and rent.

Here is a rough 2026 comparison for senior AI engineers:

1. London: £95k to £140k base, higher in finance and big tech
2. Amsterdam: €85k to €140k at firms like Adyen, Booking.com, ING
3. Berlin: €80k to €130k at tech companies and AI startups
4. Dublin: €90k to €160k at big tech-heavy employers
5. Paris: €75k to €140k, higher at elite AI firms
6. Stockholm: €75k to €130k at Spotify, Klarna, and fintech firms
7. Madrid: €55k to €100k at BBVA, Telefónica, and scaleups
8. Barcelona: €50k to €95k, with some remote EU roles paying more
9. Milan: €50k to €95k, depending on company
10. Munich: €80k to €140k at Siemens, Bosch, automotive, and enterprise firms

London’s big advantage is the high ceiling.

The downside is that a salary that sounds massive may feel normal after:

• Rent
• Council tax
• Transport
• Student loans
• Pension contributions
• Childcare, if relevant
• Higher-rate tax
• National Insurance
• Food and social life

A £110k salary in London is good. It is not private-jet money. It is “nice flat share or modest one-bed, save properly, buy Pret without crying” money.

What You Actually Take Home In London#

Let’s keep this simple.

Approximate monthly take-home pay in the UK depends on tax code, pension, student loans, and benefits. But rough numbers help.

Estimated Monthly Take-Home Pay

For a single person with standard tax assumptions, before student loan and pension tweaks:

• £50k salary: around £3,200 per month
• £70k salary: around £4,200 per month
• £90k salary: around £5,200 per month
• £110k salary: around £6,100 per month
• £130k salary: around £7,000 per month
• £160k salary: around £8,400 per month

These are only rough figures.

Pension contributions can reduce taxable income, which may be smart. Student loan repayments can reduce take-home. Bonus income may be taxed heavily at first, then corrected later through payroll or self-assessment.

London Cost Reality Check

Monthly costs can look like this:

• Room in shared flat: £900 to £1,400
• One-bed flat in decent area: £1,800 to £2,700
• Council tax: £120 to £250
• Transport: £150 to £300
• Groceries: £250 to £450
• Gym: £30 to £120
• Phone and subscriptions: £40 to £120
• Eating out and social life: £250 to £700
• Utilities and internet: £150 to £300

So yes, AI engineer salary London numbers are strong.

But you still need to negotiate because London will happily eat your raise in rent and oat flat whites.

What Affects Your AI Engineer Salary In London#

Your pay is not random.

These factors push offers up or down.

1. Production Experience

Have you shipped models that real users touched?

If yes, say that clearly.

Better resume bullet:

• “Deployed an LLM-based support assistant used by 40,000 monthly users, reducing average ticket handling time by 28%”

Weak resume bullet:

• “Worked on chatbot using Python and OpenAI API”

Hiring managers pay for outcomes.

2. Domain Knowledge

AI plus domain knowledge pays well.

Examples:

• AI plus finance
• AI plus healthcare
• AI plus cybersecurity
• AI plus legal tech
• AI plus logistics
• AI plus climate
• AI plus manufacturing
• AI plus retail

A general AI engineer might get £95k.

An AI engineer who understands fraud systems, payment risk, and real-time inference might get £130k at a fintech.

3. System Design Skill

You need to explain how the thing works at scale.

For example:

• How does data flow in?
• Where is it stored?
• How is the model called?
• What happens if the model fails?
• How do you monitor quality?
• How do you control cost?
• How do you protect user data?
• How do you run experiments?
• How do you roll back?

This is where many candidates lose senior offers.

They know ML, but they cannot design the surrounding system.

4. Communication

AI work touches product, legal, support, security, data, engineering, and leadership.

If you can explain AI tradeoffs in plain English, you are more valuable.

A hiring manager wants someone who can say:

• “This model is accurate, but too slow”
• “This approach is cheaper, but needs human review”
• “This looks good in offline testing, but we need live A/B results”
• “This should not be automated because the downside risk is too high”

That kind of judgment pays.

5. Interview Performance

Painful but true.

You might be worth £130k, but if you freeze in interviews, you may get a £90k offer or no offer.

Most London AI engineer interviews test:

1. Python coding
2. Algorithms, depending on company
3. ML fundamentals
4. ML system design
5. General system design
6. Past project deep dive
7. Behavioural examples
8. Product thinking
9. Cloud and deployment basics

Practise out loud. Seriously.

Thinking silently for 20 minutes and then saying “yeah so basically…” is not a strategy.

How To Negotiate An AI Engineer Salary In London#

Negotiation is awkward because nobody teaches it properly.

But if you do not negotiate, you may leave £10k to £40k on the table.

Step 1: Do Not Give A Low Number First

If a recruiter asks, “What salary are you looking for?” try:

• “I’m still learning about the scope of the role. Could you share the approved range?”
• “For the right senior AI role in London, I’m seeing ranges around £110k to £140k base depending on total package. Is that aligned with your band?”
• “I’m flexible depending on bonus, equity, and responsibilities. What range has been budgeted?”

Do not say “I’d be happy with £85k” if the role can pay £115k.

You have just donated £30k.

Step 2: Compare Total Compensation

Ask for the full package:

• Base salary
• Bonus target
• Bonus history
• Equity
• Equity vesting
• Pension contribution
• Private health
• Remote policy
• Training budget
• Notice period
• On-call expectations
• Promotion timeline

A £120k base with no bonus may be weaker than £110k plus 20% bonus and 10% pension.

Step 3: Use Competing Offers Carefully

If you have another offer, say it calmly.

Example:

“Thanks, I’m excited about the role. I do have another offer at £118k base with a 15% bonus. This role is my preference because of the AI platform work. If you can get closer to £125k base, I’d be ready to sign.”

Short. Polite. Specific.

No drama.

Step 4: Negotiate More Than Base

If base is fixed, ask about:

• Sign-on bonus
• Equity refresh
• Higher bonus target
• Earlier salary review
• Extra holiday
• Remote days
• Training budget
• Conference budget
• Relocation support
• Job title adjustment

Sometimes companies cannot move base because of internal bands, but they can move sign-on or equity.

Step 5: Know When To Stop

Once you have a strong offer, do not keep squeezing forever.

If they meet your number, accept gracefully.

Hiring managers remember people who negotiate professionally. They also remember people who turn it into a hostage situation.

Best-Paying AI Engineer Skills For 2026#

If you want to raise your salary before your next move, focus on skills that connect AI to business value.

High-Value Technical Skills

1. LLM application architecture
2. RAG with strong evaluation
3. Fine-tuning and model selection
4. ML system design
5. MLOps and deployment
6. Vector databases
7. Data engineering
8. Cloud architecture
9. Real-time inference
10. Security and privacy for AI
11. Cost optimisation
12. A/B testing
13. Monitoring and observability
14. Responsible AI and compliance
15. Python engineering quality

High-Value Business Skills

1. Translating vague product ideas into AI systems
2. Explaining model risk to non-technical people
3. Estimating cost before building
4. Knowing when not to use AI
5. Prioritising reliability over demos
6. Working with legal and compliance
7. Measuring impact in money, time, risk, or retention

That last point is huge.

Your salary rises when your work connects to numbers.

Say:

• “Reduced false positives by 18%”
• “Saved £400k per year in manual review cost”
• “Improved conversion by 6%”
• “Cut inference cost by 35%”
• “Reduced latency from 2.4s to 800ms”

Numbers make recruiters behave differently.

AI Engineer Resume Tips For London Roles#

Your CV needs to pass recruiters, hiring managers, and applicant tracking systems.

For AI engineer roles, your resume should show:

1. Clear Job Title Match

Use titles that match the role.

If your official title is “Software Engineer” but you did AI work, your headline can say:

Software Engineer, AI and Machine Learning Systems

That helps humans and ATS filters.

2. Strong Technical Summary

Example:

“AI Engineer with 5 years of experience building production ML and LLM systems in fintech. Skilled in Python, PyTorch, AWS, RAG, model evaluation, Docker, Kubernetes, and real-time inference. Built fraud and customer support automation systems serving 2M+ users.”

That is better than:

“Passionate AI engineer interested in solving problems.”

Passion is nice. Proof gets interviews.

3. Impact-Driven Bullets

Use this format:

Built X using Y, resulting in Z.

Examples:

• “Built a RAG-based document search system using Python, LangChain, and Elasticsearch, reducing average analyst research time by 32%”
• “Deployed fraud detection models to AWS SageMaker, improving recall by 14% while keeping false positives below target threshold”
• “Created automated evaluation pipeline for LLM responses, reducing manual QA time from 12 hours to 3 hours per release”
• “Optimised model inference service, cutting monthly cloud spend by £18k”

4. Skills Section That Is Not A Junk Drawer

Group skills clearly.

Example:

• Languages: Python, SQL, TypeScript
• ML: PyTorch, TensorFlow, scikit-learn, XGBoost
• LLMs: RAG, fine-tuning, prompt evaluation, vector search
• Cloud: AWS, GCP, Docker, Kubernetes
• Data: Spark, Airflow, Snowflake, PostgreSQL
• Monitoring: MLflow, Weights & Biases, Prometheus, Grafana

Do not list every tool you touched once in 2019.

5. Projects That Look Like Real Products

If you are early-career, projects matter.

Good AI projects include:

1. A RAG app with evaluation metrics
2. A fraud detection model with realistic imbalanced data
3. A model monitoring dashboard
4. A recommender system with offline evaluation
5. A fine-tuned model with before and after comparison
6. An AI agent with tool use and guardrails
7. A computer vision model deployed behind an API

Put the code on GitHub if possible. Add screenshots, a short README, and performance numbers.

Common Mistakes That Keep AI Engineer Salaries Low#

A lot of candidates are closer to high-paying roles than they think, but their positioning is messy.

Avoid these mistakes.

Mistake 1: Calling Everything “AI”

Hiring managers are tired.

If you used logistic regression, say that. If you used GPT-4, say that. If you built rules, say that.

Clear beats trendy.

Mistake 2: No Production Proof

A model in a notebook is not the same as a model in production.

Show deployment, monitoring, testing, and users.

Mistake 3: Weak Python

AI engineers still need to be engineers.

You should be comfortable with:

• Clean functions
• Classes when useful
• Testing
• APIs
• Async basics
• Data structures
• Performance issues
• Error handling
• Logging
• Packaging

Mistake 4: Ignoring Cost

In 2026, companies care about AI cost.

If your LLM feature costs £2 per user action, someone will ask questions.

Show you understand:

• Token costs
• Caching
• Model routing
• Batch processing
• Quantisation, where relevant
• Smaller models
• Latency tradeoffs

Mistake 5: Not Preparing Stories

Behavioural interviews matter.

Prepare stories about:

1. A failed model
2. A disagreement with product
3. A time you reduced cost
4. A time you improved reliability
5. A time you handled messy data
6. A time you explained risk
7. A time you mentored someone
8. A time you changed your mind

Use the STAR format, but do not sound like a robot reading HR homework.

Final Take: Is An AI Engineer Salary In London Worth It In 2026?#

Yes, for many people, an AI engineer salary in London is worth it in 2026.

But only if you are intentional.

The best-paid AI engineers are not just “AI people.” They are builders who can turn models into reliable products, explain tradeoffs, and show business impact.

Here is the short version:

• Junior AI engineers can expect £45k to £65k
• Mid-level AI engineers can expect £65k to £95k
• Senior AI engineers can expect £95k to £140k
• Staff AI engineers can expect £130k to £180k
• Principal and top AI roles can pass £200k total compensation
• Big tech, finance, and AI labs pay the most
• LLM, MLOps, ML system design, and domain expertise raise your value
• Negotiation can add serious money
• Your CV needs to show production impact, not just tools

Before you apply, make sure your resume is not quietly getting filtered out by ATS software. Run it through JobRise’s free checker here: https://jobrise.io/free-ats-checker/