Top Tech Jobs & Startup Jobs

Build and scale AI-powered systems in collaboration with data scientists and product managers. Develop reliable frontend and backend architectures, data pipelines, and cloud infrastructure. Deploy machine learning outputs into production-ready applications, provide technical expertise to customers, and manage the full software lifecycle while balancing rapid prototyping with long-term maintainability.

Build scalable, maintainable, and well-tested React applications that visualize AI and machine learning insights. Collaborate with data scientists, data engineers, and designers to deliver client-facing products. Lead frontend feature planning, deployment infrastructure, technical standards, reusable component libraries, mentoring, training, and onboarding while serving as the frontend engineering authority for the team.

Build and optimize cloud platform infrastructure, multi-environment architectures, Infrastructure as Code, Kubernetes clusters, and automated deployment solutions. Own security controls, monitoring, logging, incident response, and root cause analysis for production environments. Collaborate with software and ML engineers on production readiness, develop Python platform tooling, and mentor engineers through reviews and best-practice sharing. The role may support government clients and require UK Developed Vetting eligibility and occasional onsite work.

Design and scale Faculty’s Fellowship learning experience across regions and cohorts. Responsibilities include developing modular curricula, mentor tools, train-the-trainer programs, delivery standards, secondment pipelines, and continuous improvement reporting. The role partners with SMEs, facilitators, operations, business-unit leaders, and People teams while delivering broader capability projects and evaluating learner progression, mentor impact, and program quality.

Lead the architecture, development, and deployment of production-grade AI, machine learning, software, and infrastructure systems. Establish scalable ML deployment standards, collaborate with engineering, data science, product, and commercial teams, advise clients, and mentor junior engineers. The role requires strong technical leadership, cloud expertise, client-facing communication, and the ability to deliver robust systems in a fast-paced environment.

Lead high-impact AI projects for energy, transition, and environment clients. Define data science approaches, design robust software architectures, develop bespoke algorithms, mentor data scientists, assess technical feasibility, plan projects, estimate timelines, and lead delivery teams. Build client relationships, translate business problems into mathematical frameworks, contribute to thought leadership, and ensure rigorous best practices throughout the project lifecycle.

Leads private equity AI due diligence, market scans, AI maturity benchmarking, portfolio value creation, and internal AI use cases. Translates technical risks, data assets, IP, architecture, AI economics, and disruption potential into investment insights. Manages client relationships, project delivery, commercial viability, proposals, business development, and cross-functional teams while advising PE sponsors and portfolio executives on AI strategy and value creation.

Lead technical direction for complex data science and machine learning projects, design production-grade solutions, define roadmaps, manage technical risk, support sales engagements, advise customers, establish best practices, and mentor data scientists and cross-functional teams.

Lead the technical direction and delivery of complex AI and software projects. Architect and maintain scalable production systems, define project roadmaps, oversee high-risk delivery, develop shared engineering libraries, and guide architectural decisions. Lead hiring, mentor engineers, advise customers, estimate workstreams, recommend technologies, and coach technical and non-technical stakeholders.

Lead the technical direction and delivery of complex machine learning and software projects. Architect scalable production systems, define roadmaps, manage high-risk workstreams, develop reusable libraries, mentor and hire engineers, evaluate technologies, estimate work, and advise customers and stakeholders. The role combines advanced software and ML engineering with team leadership, technical coaching, client delivery, and solution architecture.