Staff-level Go Engineer
Shipping dependable Go services on Kubernetes
I’m Jagadesh Achanta, a St. Louis-based backend and platform engineer
who has spent the last decade building Go systems and the Kubernetes
infrastructure that keeps them healthy. I help product and platform
teams scale APIs, operators, and control planes while keeping delivery
fast and operations boring.
Teams bring me in when they need senior Go judgment—low-latency
services, resilient data pipelines, or controller logic that glues cloud
platforms together. I meet them where they are, co-own outcomes, and
make sure the codebase remains approachable long after handoff.
Go expertise
What I build for engineering teams
I specialise in Go-first ecosystems where reliability, observability,
and iteration speed matter. Typical mandates blend backend delivery with
platform automation.
Mission-critical Go services
Design and implement APIs, data pipelines, and background workers that
can carry regulated workloads and tight SLOs.
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High-concurrency services with gRPC/REST
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CQRS, event streaming, and idempotent workflows
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Profiling, benchmarking, and runtime tuning
Kubernetes controllers & operators
Author custom controllers that turn operational knowledge into
automated, tested reconciliation logic.
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controller-runtime, Kubebuilder, operator-sdk
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Multi-cluster orchestration and fleet management
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Policy, provisioning, and lifecycle automation
Platform glue & developer experience
Build the tooling that lets Go services deploy, observe, and recover
predictably across environments.
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GitOps pipelines, release automation, golden paths
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Observability: OpenTelemetry, Prometheus, Grafana
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Cost and capacity guardrails for microservice fleets
Working style
How I embed with Go and platform teams
01 · Understand the system
Trace requests, map deployments, read the code, and spot the edges where
reliability slips. I produce a concise technical brief so stakeholders
agree on the problems worth solving.
02 · Co-build the improvements
Pair with your team to deliver the Go services, controllers, or tooling
we agree on. Everything ships with tests, instrumentation, and runbooks
so production never feels like a science experiment.
03 · Leave teams empowered
Document decisions, run knowledge-transfer sessions, and create
dashboards that keep the system honest. I stay available for
architecture reviews as workloads evolve.
Selected engagements
Recent Go + Kubernetes work
Global fintech · Risk scoring platform
Re-architected Go services handling 20k requests/sec and introduced
KServe-backed canaries to meet strict audit controls.
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Cut p99 latency from 120 ms to 70 ms with targeted profiling
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Implemented feature-flagged rollouts and circuit breakers
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Delivered production dashboards and on-call playbooks
Healthcare SaaS · Imaging pipelines
Built Go-based controllers that orchestrate Kubeflow jobs and GPU pools,
enabling nightly retrains under HIPAA/SOC2 constraints.
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Automated checkpointing across spot/preemptible instances
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Integrated audit logging and anomaly alerts into Go services
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Reduced recovery time from hours to minutes after node loss
Developer tools · Managed cluster product
Led the Go control plane for a multi-cloud Kubernetes offering, unifying
provisioning, policy, and billing integrations.
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Designed reconciliation loops for 1k+ managed clusters
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Introduced structured logging and OpenTelemetry tracing
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Hardened upgrade workflows with soak tests and rollbacks
Core stack
Go-first tooling with production discipline
Languages & frameworks
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Go (1.17–1.23), generics, Go modules, fuzzing
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gRPC, protobuf, REST, GraphQL gateways
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Concurrency patterns, worker pools, pipeline design
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Testing: Ginkgo/Gomega, testify, integration harnesses
Infrastructure & lifecycle
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Kubernetes (GKE, EKS, AKS, on-prem), Helm, Kustomize
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controller-runtime, client-go, Crossplane, operators
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Terraform, Pulumi, GitHub Actions, ArgoCD, Tekton
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Observability with OpenTelemetry, Prometheus, Loki
Writing & talks
Sharing practical lessons from Go projects
How I use Go to design resilient operators, admission webhooks, and
telemetry pipelines that support ML teams.
A controller-runtime deep dive covering reconciliation design, testing,
and rollout strategies.
Combining Go automation with scheduling policies to balance spend,
reliability, and developer experience.
Hiring for a Go-heavy role?
If you need a senior engineer who can ship Go services, tame Kubernetes,
and mentor teams along the way, let’s talk. I work remotely with
US-friendly hours and have open availability for 2025 engagements.