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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and deploying secure and scalable LLM applications, with a strong foundation in machine learning lifecycle management and cloud infrastructure. Proven ability to mentor teams, communicate effectively with diverse stakeholders, and implement best practices for AI systems.
Highest-signal resume keywords
LLM Application DevelopmentMachine Learning Lifecycle ManagementTensorFlow or PyTorch ExperienceAWS, Azure, or GCP ProficiencyDocker and Kubernetes Expertise
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningPythonSoftware EngineeringAI Safety EvaluationCloud ArchitectureInfrastructure ManagementModel OperationalizationScalable ML SystemsMulti-Agent Harness ToolingCybersecurity Practices
Soft Skills
Exceptional CommunicationMentoringCollaborationOwnershipAutonomy
Tools & Technologies
AWSAzureGCPDockerKubernetes
Certifications & Qualifications
Eligibility for Security Clearance
Industry Keywords
AI SystemsMachine LearningTechnical ScopingArchitectural DecisionsClient Challenges
Tech Stack
Tools & technologiesAWSAzureCloudCyber SecurityDockerGoogle Cloud PlatformKubernetesPythonPyTorchTensorflow
About the role
Key responsibilities & impact- Lead development and deployment of cutting-edge AI systems for diverse clients
- Lead technical scoping and architectural decisions for high-impact machine learning systems and capability testing of frontier AI models
- Design and build production-grade ML software, tools, and scalable infrastructure
- Define and implement best practices and standards for deploying machine learning at scale across the business
- Collaborate with engineers, data scientists, product managers, and commercial teams to solve critical client challenges
- Act as a trusted technical advisor to customers and partners, translating complex concepts into actionable strategies
- Mentor and develop junior engineers
- Shape the engineering culture and technical depth of the team
- Partner with frontier labs on practical, high-stakes AI safety
- Bridge AI research and real-world impact through scalable ML systems
Requirements
What you’ll need- Significant experience building and deploying secure and scalable LLM applications
- Familiarity with multi-agent harness tooling and AI Safety evaluation procedures
- Understanding of the full machine learning lifecycle
- Experience operationalising models built with TensorFlow or PyTorch
- Deep software engineering expertise
- Strong Python skills
- Hands-on experience with AWS, Azure, or GCP, including cloud architecture, infrastructure management, and end-to-end cybersecurity practices
- Extensive experience with Docker and Kubernetes for building and managing applications at scale
- Ability to work with ownership and autonomy in fast-paced, high-growth environments
- Exceptional communication skills with technical teams and senior, non-technical stakeholders
- Eligibility for Security Clearance, requiring continuous residence in the UK for the past 5 years
- Ability to work in the UK; applicants must indicate whether they require visa sponsorship
- Willingness to travel throughout the UK weekly if applying for the Defence team
Benefits
Comp & perks- Flexible working arrangements; the company is open to conversations about part-time hours
- Opportunity to work on high-impact, cutting-edge AI systems
- Mentoring and professional development through collaboration with experienced teams and frontier labs
- Diverse and inclusive workplace
- Human-reviewed applications
- Option to opt out of the AI interview note-taker