Build your career with senior-led engagements.

Lead cloud architecture and migration engagements across AWS, Azure, and GCP for enterprise clients, owning the technical relationship from assessment through production handover.

• Design landing zones, migration roadmaps, and target-state cloud architectures
• Lead client-facing workshops and act as the primary technical point of contact
• Review and guide junior engineers on migration execution and IaC standards
• 8+ years in cloud infrastructure, with at least one full enterprise migration led end-to-end
• Hands-on expertise in Terraform, multi-account governance, and network security design

Build and operate data pipelines, dimensional models, and analytics foundations for client data platform modernization engagements.

• Design and build batch and streaming ingestion pipelines
• Develop dbt models, testing frameworks, and semantic layer definitions
• Work directly with client data teams to validate quality and reconciliation
• 3-5 years of experience with SQL, dbt, and a cloud data warehouse (Snowflake/BigQuery/Redshift)
• Comfortable working independently in client environments with shifting priorities

Support security posture assessments, vulnerability management, and compliance evidence collection for SOC 2 and ISO 27001 client engagements.

• Run vulnerability scans and maintain the risk register and remediation tracker
• Assist with compliance evidence collection and audit preparation
• Monitor cloud security posture and flag configuration drift
• 1-3 years in security operations, GRC, or a related field
• Familiarity with at least one compliance framework (SOC 2, ISO 27001, or similar) is a plus

Define SLOs, build observability, and lead incident response for client production platforms under our managed reliability practice.

• Define SLIs/SLOs and implement error budget policies with engineering teams
• Build and tune observability stacks (Prometheus, Grafana, Datadog)
• Lead incident response and post-incident RCA documentation
• 4+ years in SRE, DevOps, or platform engineering roles
• Experience with Kubernetes and at least one major cloud provider required

Build production ML and generative AI systems for client engagements, from feature pipelines through deployment and monitoring.

• Design and deploy RAG pipelines, model training workflows, and MLOps infrastructure
• Implement evaluation frameworks and guardrails for production LLM applications
• Collaborate with client data teams on feature engineering and model integration
• 3+ years building and deploying ML systems in production, not just notebooks
• Practical experience with at least one LLM orchestration framework (LangChain, LlamaIndex, or similar)

A structured rotational programme across cloud infrastructure and data engineering teams, working alongside senior consultants on live client engagements.

• Rotate across cloud and data engineering teams over the first 12 months
• Support senior consultants on documentation, testing, and configuration tasks
• Complete structured training in cloud fundamentals, SQL, and IaC tooling
• 2026 graduates in Computer Science, IT, or a related field
• No prior professional experience required — strong fundamentals and genuine curiosity matter most