AI Engineer, causaLens

Infrastructure

Salary not provided

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Mid and Senior level

London

2-5 days a week in office

causaLens delivers Digital Workers that enterprises can truly rely on.

Open for applications

causaLens delivers Digital Workers that enterprises can truly rely on.

21-100 employees

B2BArtificial IntelligenceEnterpriseBig dataDeep TechStrategic IntelligenceData AnalysisNo-Code

Open for applications

Salary not provided

+ Share options

Mid and Senior level

London

2-5 days a week in office

21-100 employees

B2BArtificial IntelligenceEnterpriseBig dataDeep TechStrategic IntelligenceData AnalysisNo-Code

Company mission

It’s time for Digital Workers to take on the repetitive workflows, freeing humans to focus on what matters most.

Job

Company

Role

Who you are

Expertise in the deployment of enterprise-grade AI solutions to cloud and on-premise customer environments with a focus on availability, observability and security
Proven track record with at least one of the major cloud providers and an understanding of DevOps best practices
Hands-on experience building production-grade solutions using LLMs, RAGs, MCPs, and agentic workflows
Client-facing experience with a forward deployed engineering mindset. You’ll work directly with both technical teams and business stakeholders to understand real-world challenges and deliver solutions that drive measurable impact
Strong solution architecture and delivery skills: ability to translate complex business problems into scalable, intelligent AI solutions

What the job involves

We’re looking for AI Engineers who are passionate about helping world-leading enterprises put cutting-edge AI agents into production
You’ll work on impactful, high-visibility projects - designing, building, and delivering intelligent solutions that solve real business problems at scale
Collaborate directly with top-tier enterprises to understand needs, design and deploy bespoke agentic workflows
Design and implement robust architectures that leverage the latest AI technologies
Lead the delivery of high-impact AI products from concept to deployment

Application process

Our interview process consists of screening sessions with the hiring manager and a "Day 0" which involves an approximately 3-hour in-person challenge followed by an in-person presentation and interviews
Have questions? We encourage open dialogue—reach out anytime

Salary benchmarks

Our take

causaLens want to help organisations better optimise business outcomes and their operations. It does this by facilitating AI-based decision making, that brings in more cause-and-effect nuance when arriving at outcomes than other approaches. This is known as Causal AI.

Since emerging from Stealth in January 2021, causaLens has grown revenues tremendously, with clients including Tier1 banks, hedge funds, governments and Fortune 500 companies. It has seen significant funding which has enabled it to grow to meet the growing global demand for Causal AI.

The company has also invested aggressively in its technology to maintain its competitive lead. It continues to launch new features, such as an AI agents platform that runs on its Causal AI and also utilises advanced quantitative reasoning,

Freddie

Company Specialist at Welcome to the Jungle

Insights

Top investors

-12% employee growth in 12 months

Glassdoor (3.6)

Company

Funding (last 2 of 3 rounds)

Jan 2022

$45m

SERIES A

Apr 2019

$4.6m

SERIES A

Total funding: $50.6m

Company benefits

Learning and Development Budget
Benefits to choose from, including Health/Dental Insurance
25 days holiday (excl. bank holidays)
Share options
Employer pension contribution match
Work abroad (2 weeks per annum)
Special Discounts

Company values

Kind and Inspirational
Trustworthy and Accountable
Driven and Resilient

Company HQ

West Kensington, London, UK

Leadership

Dr. Darko Matovski

(CEO)

Has a PhD in Computer Science from Southampton. Previously worked for Man Group and as a Quantitative Researcher at another hedge fund.

Maksim Sipos

(CTO/CSO)

Has a PhD in Physics from the University of Illinois. Career began at a hedge fund in Princeton, where they utilised petabyte-size live algorithmic systems managing 100s of millions of USD.

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