Senior cloud, DevOps & AI platform engineering
Byte Fusion brings three senior engineers together as one hands-on delivery team for SaaS, fintech and AI-driven product companies. We design and improve production cloud foundations, AI platform infrastructure, Kubernetes, infrastructure as code, CI/CD and observability across AWS, Azure and GCP.
01 / Engagements
Every engagement begins with written deliverables, boundaries, access needs and commercial terms. Start small, prove the working relationship, then expand only when the value is visible.
A focused technical review that converts cloud uncertainty into an evidence-backed, prioritised plan.
Senior delivery against one measurable cloud, AI infrastructure or release-engineering objective.
Consistent senior capacity for teams that need cloud, DevOps or AI platform delivery without adding another permanent role.
02 / Why Byte Fusion
Modern platform work now spans production cloud, developer experience and AI infrastructure. Byte Fusion combines cloud, Kubernetes, infrastructure as code, CI/CD, observability, security and AI platform engineering in one practical team.
Equal senior ownership
All three engineers contribute directly to delivery. We work with your engineering team, turn the problem into a measurable scope and stay focused on implementation. Architecture, code, evidence and handover are part of the same engagement.
Commercial scope and acceptance criteria stay tied to a useful business result.
Cloud foundations, developer platforms and AI infrastructure are designed as one operable system.
Start with an audit or sprint while avoiding a lengthy permanent hiring cycle.
Code, decisions, documentation and runbooks remain with your team.
03 / Senior team
Three hands-on senior engineers contributing across architecture, implementation, review and handover—with experience spanning production cloud, AI platforms, Kubernetes estates, infrastructure automation and software delivery.
Nearly seven years across AWS, Azure, EKS/AKS, Terraform, Linux and CI/CD. Focused on production cloud, automation, AI-ready platform foundations, cost, migrations and reliability.
View LinkedIn profileMore than twelve years across software, DevOps and cloud engineering. Currently focused on internal developer platforms, AI-assisted infrastructure delivery and automation across AWS, Azure and GCP.
View LinkedIn profileMore than sixteen years in engineering, combining current AI platform work with deep Kubernetes, Azure, Terraform/Terragrunt, platform security and critical production support experience.
View LinkedIn profile04 / Selected evidence
Selected individual delivery evidence from the engineers behind Byte Fusion. Client details and sensitive architecture remain confidential.
Reviewed a production footprint, identified waste and adjusted resources while protecting service requirements.
55% annual cost reductionWorked across planning, architecture, infrastructure, execution, documentation and cost decisions.
7 completed migrationsSupported production clusters, pipelines and infrastructure issues under real capacity and networking constraints.
Approximately 100 AKS clustersExperience includes multi-region Azure deployments and high-availability on-premise Kubernetes infrastructure.
10+ AKS · 200+ physical nodesDetailed examples can be discussed under NDA where appropriate. Metrics refer to selected individual engagements and programmes.
05 / Process
The operating model is built for distributed teams: decisions are written down, meetings are reserved for real decisions, and the handover is part of the deliverable.
A short call or written brief confirms the problem, urgency, constraints and fit.
You receive deliverables, exclusions, access needs, timing, owner and price in writing.
Progress, decisions, evidence and risks remain visible asynchronously throughout.
Code, documentation, runbooks and next actions stay with your team after handover.
07 / Practical details
The first conversation should remove commercial and operational uncertainty—not create more of it.
You can start with a small paid outcome, access experienced engineers immediately and remove an urgent platform bottleneck without committing to permanent headcount before the value is proven.
We build the cloud and Kubernetes foundations that AI workloads and engineering teams depend on: repeatable provisioning, secure environments, CI/CD, observability, cost controls and internal developer-platform automation.
Yes. An initial review can often begin with architecture notes, billing exports, redacted Terraform, CI/CD configuration and read-only evidence. Any broader access is agreed explicitly and kept to the minimum required.
Usually one short qualification or kick-off call and one handover. Additional meetings are arranged in advance and used only when a written update is not enough.
Yes, when the immediate work can be separated into a clear outcome or workstream. A sprint or fractional engagement can remove the current bottleneck while preserving a clean handover to the permanent hire.
The original boundary remains intact. Additional work becomes a new sprint or agreed hourly scope; it is not silently added to the engagement.
Yes. Reliability improvements, runbooks, alert design and incident follow-up can all be included. Live incident coverage and response windows are defined explicitly in the commercial scope.
Start with one real problem
Reply to the email or LinkedIn message that brought you here with your environment, current constraint and desired outcome. Byte Fusion will return a direct fit assessment and the smallest useful engagement.