Senior IAM Security Engineer

Salary - £110-120k + 10% Bonus + Benefits

Location – Fully Remote

Newly created role within a major UK Brand who are looking for a Senior Security Engineer to build on and expand their IAM and Authentication capability.

First and foremost, they need a Senior level Security Engineer with experience working in cloud-native (AWS) infrastructure environments, building out CI/CD pipelines, deploying infrastructure/policy-as-code, with a breadth of experience across various cyber disciplines.

But crucially within this role, they are looking for someone who can build and run their global IAM capabilities that secure their environments both internally and externally. You will be responsible for designing IAM policy and governance, introducing policy-as-code as well and integrating IAM with the wider CI/CD pipelines, infrastructure-as-code and cloud native services; working with the wider Engineering departments to ensure IAM security is built in from the start.

This is an incredibly rare and exciting opportunity to join one of the most advanced Security Engineering departments and take ownership of one of its most pivotal Security service lines, with freedom and financial backing to introduce novel concepts.

Key Responsibilities

• Build out, operate and lead the global IAM capabilities that secure their environments.
• Lead on the automation of IAM policy and governance through policy-as-code; covering identity standards and audit/attestation workflows.
• Integrate IAM with the wider cloud-native security services, building it into the CI/CD pipelines and infrastructure-as-code.
• Work with wider Engineering departments to ensure IAM is embedded into company-wide development projects and a productive priority, not hindrance.

Key Requirements

• Minimum 5 years’ experience in a technical security engineering role, with at least 2 focused on Identity & Access Management (IAM)
• Experience operating in cloud-native (AWS) environments building out and operating IAM functions.
• Hands-on, practical experience automating IAM Governance and Policy through policy-as-code and integrating into wider Infrastructure-as-code and CI/CD pipelines.
• Familiarity with a range of IAM tools and concepts – particularly AWS associated tooling and technology.
• Track record and ability to interact with wider Security and Engineering departments to ensure IAM and Security are built in at development stage as a priority, rather than after-thought.

Senior Cloud SecOps Engineer

Salary - £110-130k + 30-50% Bonus + Benefits

Location – London (required in office 3 days per week)

I’m currently working with one of the most innovative, tech-driven Investment Management firms who are looking to bring in a Senior Cloud SecOps Engineer. They are rebuilding their entire SecOps function from the ground up, meaning there is a blank canvas to build out a best-in-class, cloud-native SecOps capability.

Working alongside and reporting directly into the Head of SecOps, you will be responsible for understanding their current SecOps estate, ‘lifting and shifting’ what’s good, and completely ripping up and re-writing what’s not; in turn creating a lean but incredibly efficient cloud-based SecOps function.

You will effectively act as the technical bridge between the internal SOC function and the wider Platform Engineering capability – ensuring their cyber monitoring, detection and response capabilities are aligned to their wider cloud strategy and fully secure.

The ability to read and write code will be essential as well as significant experience working in cloud environments, with an in-depth knowledge of the associated cloud security tooling/concepts – Infrastructure as Code (Terraform), Containers (Kubernetes), Continuous Integration and Delivery (Gitlab)

This is genuinely an incredible opportunity to join the most established organization within this industry and have a blank canvas to build out their SecOps capability from the ground up; with freedom to build and innovate as you see fit and genuinely impact a truly elite Investment Management firms enterprise estate.

Responsibilities

• Build out a cloud-native, scalable SecOps capability capable of defending against cyber threat actors.
• Take ownership of and consistently develop the SecOps monitoring, detection and response tooling; automating and fine-tuning wherever possible, whilst adopting and configuring into the cloud infrastructure.
• Work closely with internal SOC and Platform teams to ensure the cloud based SecOps capability aligns with Platform Engineering cloud strategy.
• Report to and influence senior stakeholders across the organization, translating technical concepts into relevant associated risks

Requirements

• Experience building and developing scalable security monitoring and detection tooling using open source tooling in public cloud environments.
• Depth of knowledge and experience working in hybrid cloud environments – AWS / Azure in particular
• Strong proficiency in coding/scripting/development languages (this will be tested)
• Deep knowledge of cloud security tooling/concepts – Infrastructure as Code (Terraform), Containers (Kubernetes), Continuous Integration and Delivery (Gitlab)
• Prior experience working with/within MSSPs and an understanding of how to maximise their functionality (not essential, just a bonus)
• Ability to work with and influence wider teams and stakeholders across the business

If you’re an experienced Cloud SecOps Engineer looking to join an organisation which will provide you the platform and freedom to build and develop freedom a cloud-native SecOps capability from the ground up, whilst working alongside and learning from one of the most respected leadership teams within this space, then click apply or get in touch directly with your up to date CV - j.dale@lawrenceharvey.com

Senior Cloud Security Engineer

Location – Fully Remote (from within the UK)

Salary - £110-120k + Bonus + Benefits

Newly created role for a highly technical, hands-on Senior Cloud Security Engineer to join a major UK Brand undergoing a major security transformation.

Reporting into the Global Head of Cloud Security and working alongside a team of some of the most talented Security Engineers, you will be responsible for building and running defensive security controls for highly available cloud-native infrastructure.

For this particular role, they need someone who is a genuine Engineer who can build secure CI/CD pipelines, build and deploy multi-cluster Kubernetes and containers environments, deploy Infrastructure-as-Code in Terraform, and script/code in Python.

Key Responsibilities:

• Build and maintain defensive security controls in cloud-native (AWS) environments.
• Build out and secure CI/CD pipelines.
• Build out and secure multi-cluster container (Kubernetes) environments.
• Deploy Infrastructure-as-Code where possible to automate security processes and controls.
• Work closely with wider platform, application and research engineering teams to advise on building, maintaining and expanding security controls.

Key Requirements:

• 5+ years’ experience working in cloud security dedicated roles (AWS preferred).
• In-depth knowledge of:
  • Securing CI/CD pipelines
  • Deploying Infrastructure-as-Code (Terraform)
  • Container security (Kubernetes)
  • Scripting/Coding knowledge (Python)
  • Securing AWS hosted environments
• Ability to interact with and influence both technical and non-technical stakeholders across the organization; championing security as an enabler rather than a blocker for different teams.

• Senior Machine Learning Engineers needed for high growth tech company
• Austin, TX – must be willing to work in office 4 days a week
• High competitive salary + equity + strong benefits

Senior Machine Learning Engineer

We're partnering with a fast-growing technology company that's building machine learning systems at significant scale to solve complex real-world challenges. Their platform processes billions of transactions annually and uses advanced AI to power intelligent decision-making for millions of end users.

As a Senior Machine Learning Engineer, you'll work at the intersection of machine learning and software engineering, collaborating closely with product and engineering teams to design, build and deploy production-grade ML models that directly influence business outcomes.

Compensation

• Total compensation: $335k–$400k
• Base salary: $210k–$260k
• Equity package included
• Comprehensive benefits

What you'll do

• Partner with product managers and engineers to translate business problems into scalable machine learning solutions.
• Design, develop and deploy production-ready machine learning models across areas such as ranking, prediction, optimisation, forecasting and recommendation.
• Build robust data pipelines, engineer high-quality features and integrate models into scalable production infrastructure.
• Monitor model performance, detect drift and continuously improve model accuracy through retraining and experimentation.
• Write clean, well-tested, production-quality code and contribute to engineering best practices across testing, reliability and performance.
• Research emerging machine learning techniques, prototype new approaches and validate ideas through offline and online experimentation.

What we're looking for

• PhD or Master's degree in Computer Science, Statistics, Mathematics or a related quantitative discipline (or equivalent industry experience).
• Strong background in machine learning and software engineering with experience delivering production ML systems.
• Expertise in one or more of the following areas:
  • Recommender systems
  • Bayesian machine learning
  • Multi-task learning
  • Meta-learning
  • Ranking, prediction or optimisation models
• At least 3 years of experience building end-to-end machine learning systems, including training, deployment, serving and monitoring.
• Experience with modern ML infrastructure such as TensorFlow, Kubeflow (or similar) and feature stores is highly desirable.
• Familiarity with large-scale deep learning architectures used for recommendation or ranking systems is a plus.

Working arrangements

• Hybrid working model with four days per week in the office and one day working remotely.

This is an opportunity to join a highly technical engineering team where machine learning sits at the core of the product. You'll have the chance to work on challenging problems at scale, collaborate with experienced engineers and researchers, and see your work make a measurable impact.

Our client is a global leader in fintech and payments, powering the secure movement of money and information for financial institutions, merchants, businesses, and consumers around the world. Their technology enables billions of transactions each year, supporting everything from card payments and digital wallets to banking and embedded financial services. This is an opportunity to join a highly respected organization at the forefront of payments innovation and make an impact at global scale.

About the Role

As Privacy Managing Counsel, you will support the company's Embedded Finance business by advising on privacy-by-design, responsible data use, and scalable compliance across products, partnerships, and commercial arrangements. You will work closely with product, engineering, compliance, risk, business, and legal stakeholders, as well as sponsor banks and consumer technology partners. Your work will help enable compliant growth, strengthen privacy governance, and support practical decision-making throughout the product lifecycle.

Responsibilities

• Advise business, product, engineering, compliance, risk, and legal stakeholders on privacy and data protection requirements applicable to embedded finance offerings, including the Gramm-Leach-Bliley Act (GLBA), state privacy laws, the California Consumer Privacy Act (CCPA), California Privacy Rights Act (CPRA), General Data Protection Regulation (GDPR), Fair Credit Reporting Act (FCRA), Health Insurance Portability and Accountability Act (HIPAA), and related frameworks.
• Partner with cross-functional teams to identify privacy implications, conduct risk assessments, and implement practical, scalable privacy-by-design controls throughout the product lifecycle.
• Advise on Banking-as-a-Service (BaaS) program structures and privacy-related compliance considerations across sponsor banks, program managers, processors, consumer-facing partners, and other third parties.
• Draft, review, and negotiate privacy and data protection provisions in commercial and technology agreements, including data use, licensing, vendor, service provider, customer, and data transfer agreements.
• Lead partner and vendor negotiations on privacy matters and participate in client-facing discussions related to data use, compliance obligations, and contractual risk.
• Develop, maintain, and enhance privacy policies, notices, procedures, training materials, and governance tools that promote consistent operational practices.
• Monitor evolving privacy laws and regulations and translate legal requirements into practical guidance for internal stakeholders.

Qualifications

• 8+ years of legal experience focused on privacy, data protection, financial services regulation, or related legal counseling.
• Experience advising on U.S. financial privacy laws, including GLBA and state privacy requirements.
• Experience drafting, reviewing, and negotiating commercial, technology, vendor, customer, data use, and data protection agreements within financial services, banking, payments, fintech, or similarly regulated industries.
• Experience supporting banks, fintech companies, payment processors, card networks, or comparable law firm clients.
• Active license to practice law in at least one U.S. jurisdiction.
• Juris Doctor (JD), Master of Laws (LL.M.), or equivalent legal qualification.

Preferred Experience

• CIPP/US or another recognized privacy certification.
• Experience supporting embedded finance, Banking-as-a-Service, or other partner-driven financial products.
• Experience advising within complex, multi-party ecosystems involving sponsor banks, processors, fintech platforms, and consumer-facing technology companies.
• Familiarity with implementing privacy-by-design practices within product development and engineering environments.