DevOps & platform engineering
CI/CD, Infrastructure as Code (Terraform, CDK), automated releases, and environments that match how your product actually ships.
A single senior operator who covers the full modern stack: from Kubernetes and GitOps to production blockchain nodes, observability, and hardening—without the overhead of a large firm.
→ Unicorn-grade breadth: stack design, delivery, and cost optimisation in one engagement.
One person, full capacity — fractional or project-based leadership with hands-on execution, not slide decks alone.
End-to-end support for teams who need cloud-native operations, chain-grade reliability, and security—without stitching together five different vendors.
CI/CD, Infrastructure as Code (Terraform, CDK), automated releases, and environments that match how your product actually ships.
SLOs, incident response, Prometheus, Grafana, Loki, Datadog—lower MTTR through measurable signals and practical runbooks.
Multi-cloud and AWS/GCP/Azure designs, migration, fault tolerance, and FinOps-minded architecture—proven on large regulated and SaaS workloads.
EVM and protocol nodes, RPC, validators, indexing pipelines, sync performance, upgrades, and secure key and wallet patterns.
Kubernetes hardening, RBAC, policy (OPA), runtime security (Falco), service mesh TLS, and secure delivery pipelines.
Practical automation with ML where it earns its place, plus a clear view on what to adopt next versus what is hype—aligned to your risk and compliance posture.
A production dApp on VeChainThor—secure backend, AI-assisted fraud detection, DAO-driven incentives—with infrastructure, backend, and deployment owned end to end. That same ownership model applies to client work: clear accountability from code to cluster.
metermate.vet →Strategy that connects new tooling to outcomes: where automation fits, how to phase adoption, and how to keep operational costs and security under control as the stack evolves.
Most “cloud” or “platform” issues are not a missing tool—they are layered: incentives, habits, and constraints underneath the ticket. Here is the behavioural stack I use to read a situation, plus the signals teams send when something is off—and how we work through it.
Before we touch Kubernetes, Helm, or a chain client, it helps to see where pressure actually lives. These layers stack—ignore the bottom and the top keeps breaking.
If one of these sounds like you, we map it onto the stack above and pick a sensible first move—no noise, no theatre.
Emerging technology—whether it is cloud, Blockchain, or AI—is everywhere. Most of it is noise.
You want to know what’s real, what works, and what’s worth building.
You’ve got an idea. Instead of debating it for months, build a lean pilot, validate it, and kill or scale fast.
You started strong. Now it’s stuck.
You need someone to cut through complexity and get it shipped.
Leadership doesn’t care about hype.
They care about ROI, risk, and results — you need a case that actually lands.
Common behavioural patterns—each maps to a different entry point, but the same stack underneath.
Platforms and vendors get chosen before outcomes are crisp. Teams look busy, releases feel brittle, and nobody can explain the ROI in one sentence.
Product and platform talk past each other: features ship while operability, security, and cost are treated as a late surprise instead of a joint bet.
One or two people hold production in their heads. Change feels risky; on-call is tense; knowledge does not compound into runbooks and automation.
POCs multiply but nothing graduates or gets killed. Budget and attention leak with no explicit kill/scale decision—classic exploration without closure.
Leadership wants “AI” or “cloud modernisation” as a headline. You need a measurable narrative and staged bets—not a slide of buzzwords.
Risk and regulation are real, but reviews turn into gates that stall delivery. You need controls that match how software actually ships.
Three stacked modes—usually interleaved—so behaviour, systems, and evidence move together.
Clarify outcomes, incentives, and sequencing: what to adopt, defer, or stop. Named trade-offs so product, finance, and engineering can agree on the same story—not parallel fictions.
Hands-on work on infra, security, and delivery paths that fit your team’s real habits: CI/CD, observability, guardrails, and feedback loops people will actually use.
Short spikes and pilots with clear success and exit criteria: prove or disprove fast, then scale, pivot, or kill—so exploration does not become permanent thrash.
If you are hiring for reliability, migration, chain ops, or a leaner cloud bill, you get a single accountable expert who has shipped at protocol scale and inside regulated enterprises.
rishikesh.pal@gmail.comLetterkenny, Ireland · Remote worldwide