For CTOs, Founders & Engineering Leaders

Senior Engineers
Embedded in Your Team

We embed senior DevOps, cloud, Kubernetes, software, and private AI engineers into product teams that need faster execution, lower platform risk, and stronger internal ownership.

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Trusted by teams in gaming, fintech, and health tech.

Embedded Senior Engineers Add delivery capacity without a long hiring cycle
Knowledge Transfer Your team keeps the knowledge and ownership
Cloud Cost Discipline Architecture choices shaped around efficiency
Private AI Ownership Open models and controlled deployment
Services

DevOps, Software Engineering, Platform & Private AI Services

From a single senior engineer to a focused delivery pod, we step into the work that blocks product teams and reduce the management overhead that usually comes with outside help.

Core Engagement

Senior Outstaffing & Team Extension

Embed senior engineers who can own tickets, platform work, production issues, and architecture decisions from day one. We work inside your repos, your sprint cadence, and your delivery process so extra capacity translates into actual output.

  • Senior DevOps, cloud, Kubernetes, software, reliability, and private AI engineering capacity
  • Engineers work inside your tooling, rituals, communication channels, and security boundaries
  • Documentation and knowledge transfer are built into delivery instead of left for the end

Software Engineering

Add senior backend and product engineers who can ship features, stabilize existing systems, and work closely with your internal team from planning through production release.

  • Backend services, APIs, integrations, and production-facing application work
  • Architecture cleanups, refactors, and engineering support for active product roadmaps
  • Hands-on collaboration with your own engineers, product team, and release process

Platform & Cloud Foundations

Modernize legacy operations, reduce cloud waste, and give teams a cleaner platform base to build on. We design environments that are easier to run and easier to scale.

  • Cloud architecture, Kubernetes platform design, and operating model improvements
  • Manual process reduction, environment standardization, and clearer ownership boundaries
  • Delivery shaped around performance, maintainability, and cost discipline

CI/CD & GitOps Enablement

Improve release speed and reduce deployment risk with delivery workflows your team can maintain without depending on heroics.

  • Build, test, deploy, and environment promotion pipelines with rollback safety
  • GitOps workflows, release governance, and change visibility for growing teams
  • Less deployment friction between engineering, QA, and platform ownership

Observability & Reliability Engineering

Build the monitoring and operational routines that help teams detect issues earlier, respond faster, and reduce avoidable firefighting.

  • Metrics, logs, dashboards, tracing, and actionable alerting design
  • Incident response workflows, escalation paths, and post-incident improvement loops
  • Operational visibility that supports engineering leadership, not just on-call teams

Hiring, Vetting & Team Development

Improve engineering quality over time by tightening hiring loops, raising interview quality, and building stronger internal capability.

  • Technical interview design, senior candidate vetting, and deeper engineering assessments
  • Academy cohorts and structured upskilling for internal engineers and support teams
  • Mentorship and delivery habits that strengthen long-term team performance

Private AI Infrastructure

Deploy local or hybrid AI stacks with GPU orchestration, inference optimization, and security controls that keep sensitive data under your control.

  • Private model serving, self-hosted inference, and hybrid deployment patterns
  • GPU utilization, performance tuning, and operating cost control
  • AI delivery designed for security-sensitive teams and internal ownership
Engagement Models

How Engineering Leaders Typically Work With Infraheads

We structure engagements around delivery ownership, speed to impact, and knowledge transfer. Most clients begin with a narrow need and expand only after the work proves out.

Why Leaders Choose Us

What You Actually Get

We are measured by faster delivery, lower platform risk, and stronger internal capability after we join the engagement.

Fast Senior Ramp-Up

We staff senior engineers who can contribute to delivery, architecture, and operations without a long onboarding ramp.

Ownership Stays With You

We build in your environment, document decisions, and transfer knowledge so your team stays in control after the engagement.

20%+ Cost Reduction Mindset

Cloud and tooling decisions are evaluated for total cost and operational drag, not just technical elegance.

5.0 Clutch Credibility

Real client feedback, repeat work, and delivery experience across gaming, fintech, and health tech.

Private AI Without Lock-In

We deploy AI on your hardware or hybrid infrastructure with open models, so your data and operating costs stay under your control.

Certified Delivery + Academy Pipeline

Certified engineers backed by a training engine that helps you strengthen internal talent instead of depending on outside help forever.

Technology Expertise

Platforms, Tooling & Infrastructure

Production-proven cloud, Kubernetes, DevOps, observability, and private AI technologies our engineers operate in real client environments.

Cloud Platforms

Core cloud infrastructure delivery across the platforms we actively support, shaped around uptime, spend discipline, and clear operational ownership.

  • AWS
  • Azure

Containers & Platform Ops

Container platforms, cluster operations, and workload management for teams scaling beyond ad hoc DevOps.

  • Kubernetes
  • Docker
  • Helm
  • Talos Linux
  • Kubespray
  • EKS
  • AKS

Delivery Automation

Pipelines, infrastructure as code, and GitOps workflows that shorten release cycles without creating brittle operational overhead.

  • Terraform
  • Ansible
  • Jenkins
  • GitHub Actions
  • GitLab CI
  • ArgoCD
  • GitLab

Observability & Incident Response

Metrics, logs, dashboards, and alerting stacks that help teams detect issues earlier and respond with better operational context.

  • Prometheus
  • Grafana
  • Zabbix
  • Datadog
  • ELK Stack

Private AI Infrastructure

Secure local and hybrid inference platforms for organizations adopting open-weight models while keeping sensitive workloads under their own control.

  • NVIDIA CUDA
  • vLLM
  • Ollama
  • LocalAI

Data & Messaging Infrastructure

Data stores and event infrastructure that support resilient applications, internal platforms, and production-grade service integrations.

  • PostgreSQL
  • Redis
  • Confluent Kafka
  • MongoDB
  • Elasticsearch
Kubernetes Help

Not Just Anybody — We Can Help!

Our engineers are certified Kubestronauts. When your Kubernetes platform needs an upgrade, a rescue, or a turnkey on‑prem deployment, we step in with production-proven patterns — including our open-source turnk8s project for Talos-based clusters.

Kubestronaut jacket — letter H
Kubestronaut jacket — letter E
Kubestronaut jacket — letter L
Kubestronaut jacket — letter P
Read about turnk8s
Academy

Infraheads Academy & Team Upskilling

Use the academy for company cohorts, internal team development, and engineers who need practical production infrastructure skills rather than theory alone.

Official Cisco Networking Academy Partner
Find us on Academy Locator ↗
Beginner

Infrastructure Foundations

12 weeks · labs + mentor feedback

For juniors, career changers, and internal support teams moving into infrastructure work.

  • Linux, terminal workflows, users, permissions, packages, and service management
  • TCP/IP, DNS, routing, VPN basics, and practical network troubleshooting
  • Git, pull requests, branching strategy, and team collaboration habits
  • Containers, images, registries, and the basics of running workloads
  • Cloud foundations: compute, storage, IAM, and cost awareness
  • Documentation discipline, ticket handling, and incident communication

Outcome: ready for junior infrastructure work or progression into the platform engineering track.

Intermediate

Platform Engineering Bootcamp

12 weeks · real project labs

For DevOps engineers, backend developers, and company cohorts building delivery maturity.

  • Kubernetes workloads, services, ingress, Helm, and day-to-day cluster operations
  • Terraform module design, remote state, secrets handling, and environment promotion
  • CI/CD pipeline design, release gates, rollback strategy, and artifact management
  • Observability with Prometheus, Grafana, logging, tracing, and SLO thinking
  • GitOps with ArgoCD, deployment governance, and operational change control
  • Incident response, root-cause analysis, and postmortem writing

Outcome: able to own a modern platform stack with less supervision and better production discipline.

Advanced

AI Infrastructure & SRE

12 weeks · capstone + mentorship

For senior engineers, ML platform teams, and companies building private AI capability.

  • GPU sizing, inference performance, batching, and workload scheduling
  • Local LLM deployment with Ollama, vLLM, model packaging, and evaluation
  • RAG architecture, vector storage, prompt versioning, and guardrail design
  • Secure platform design with secrets, access control, auditability, and compliance basics
  • Hybrid cloud versus on-prem tradeoffs, cost control, and vendor lock-in avoidance
  • Capstone delivery from architecture review to deployable AI service

Outcome: ready to design and operate private AI platforms in production, not just prototype them.

Insights

Insights for Engineering Leaders

Technical articles that show how we think about platform engineering, delivery risk, and infrastructure decisions in real client environments.

Aug 4, 2026 10 min read

A three-tier application with Docker Compose and Flyway

Build a three-tier application with Dockerfiles, two isolated Docker Compose networks, PostgreSQL, health checks, and versioned Flyway migrations.

Read article
Jul 6, 2026 4 min read

How we added an AI concierge to a static site

A lead-capturing AI concierge on a static site: a Cloudflare Worker proxies Claude, a self-contained widget rides every page, and captured leads land in the same mailbox as our forms.

Read article
Jun 19, 2026 8 min read

When engineers break production: blame, safety, and resilient systems

What psychology and organizational research say about production mistakes—and why reliable teams combine psychological safety with engineering controls and accountability.

Read article
Jun 4, 2026 7 min read

SSM Parameter Store vs Terraform state for shared values

Terraform state is convenient for Terraform-to-Terraform dependencies, but SSM Parameter Store is the better contract for shared infrastructure values consumed by many tools.

Read article
May 20, 2026 11 min read

Closing the loop: a self-improving AI bot for network access automation

How we built an AI coding agent that handles the full lifecycle of network access requests — from ticket to firewall rule to CI pipeline monitoring — and rewrites its own instructions after every failure.

Read article
Apr 30, 2026 7 min read

The AI agent arms race: why Pi might not be the king

The intersection of LLMs, autonomous agents, and complex tool use. Exploring the frontiers of what's possible in the era of AI-driven software engineering.

Read article
View all articles
FAQ

Questions Decision Makers Usually Ask

Short answers to the buying, staffing, and delivery questions that usually come up before an engagement starts.

Do you provide outstaffed engineers, project delivery, or both?

Both. Many clients start with one or more embedded senior engineers, while others use a focused delivery pod when the need is a defined platform or AI outcome.

Can you work inside our current cloud, Kubernetes, and CI/CD environment?

Yes. We usually work inside the client's existing repositories, cloud accounts, deployment workflows, and observability stack rather than forcing a new operating model.

How do you reduce risk when joining an internal engineering team?

We document decisions, work in your environment, align with your team cadence, and transfer knowledge as we go so ownership stays with your internal team.

Do you support private AI infrastructure for sensitive workloads?

Yes. We help teams design local or hybrid inference setups where model serving and sensitive data stay under client control instead of being pushed into unmanaged third-party platforms.

Can you also help us hire or upskill internal engineers?

Yes. We support technical vetting, interview loops, and internal upskilling through the Infraheads Academy when clients want to build longer-term delivery capacity in-house.

Contact

Tell Us What Needs To Move Faster

Need senior outstaffed engineers, platform cleanup, private AI rollout, or technical hiring support? Share the context and we will suggest a practical next step.

Good Fit If You Need

  • A senior DevOps, software, or platform engineer who can contribute immediately
  • CI/CD, Kubernetes, or observability work without heavy management overhead
  • Lower cloud spend and fewer reliability surprises
  • Private AI delivery with sensitive data staying under your control
  • Technical interviewing or academy cohorts for your internal team

Schedule

Book a discovery call ↗

Email

[email protected]

Phone

+374 94 537 510