Hiring Guide: TeamCity Developers
Hiring TeamCity developers is about more than “setting up a CI server.” The best engineers turn CI/CD into a reliable product: versioned pipelines, reproducible builds, fast and observable feedback, and safe deploys with crisp rollbacks. Strong TeamCity specialists understand build agents and resource management, Kotlin DSL pipelines, artifact dependencies, snapshot dependencies, caching and test parallelization, and how to weave security and compliance directly into the pipeline. This guide helps you define the role, vet candidates on real signals (not trivia), and plan the first 30–90 days. You’ll also find related Lemon.io pages to round out your delivery team.
Why Choose TeamCity (and When It Fits)
- Polyglot, legacy-friendly CI: First-class support for JVM, .NET, JavaScript/TypeScript, Python, Go, mobile, and monorepos. Easy to adopt for mixed stacks and legacy build systems.
- Kotlin DSL for pipelines: Version your pipelines alongside code, review changes via PRs, and generate repeatable build chains without click-ops drift.
- Build chains & dependencies: Snapshot and artifact dependencies create efficient, cache-friendly pipelines across microservices and monorepos.
- Smart test history & flakiness detection: Test re-run rules, history-based prioritization, code coverage tracking, and test quarantine management reduce noise and increase developer trust.
- On-prem or cloud agents: Fit stringent security/compliance needs with self-hosted control, or burst to cloud with scalable agents for peak workloads.
What Great TeamCity Developers Actually Do
- Codify everything in Kotlin DSL: Projects, build configurations, VCS roots, templates, parameters, dependencies, and triggers—kept in the repo with code review and change history.
- Design build chains that scale: Orchestrate snapshot dependencies for parallelism, artifact dependencies for reuse, and conditional steps to avoid redundant work.
- Speed up feedback loops: Cache dependency layers, warm container images, split tests intelligently, and use build features like “Checkout on Agent” and incremental builds.
- Keep builds reproducible: Pin tool versions, containerize steps, lock OS images, and validate via checksumed artifacts and SBOM generation.
- Engineer for reliability: Agent pools & requirements, failure conditions, retry rules, grace thresholds for flaky tests, and automatic fallbacks with clear notifications.
- Secure the pipeline: Secret management, parameter masking, restricted build parameters, signed artifacts, policy checks (e.g., OPA), and least-privilege VCS/registry access.
- Add observability: Export build and agent metrics, publish test analytics, annotate PRs, and integrate chat/issue trackers for one-click triage.
- Enable the org: Reusable templates, shared build steps, and documentation so product teams can add pipelines without bottlenecking on DevOps.
Core TeamCity Concepts Strong Candidates Should Know
- Projects & build configurations: Hierarchies, templates, parameters, and build steps. Avoid duplicated configs by using templates and DSL.
- Snapshot & artifact dependencies: Model multi-stage pipelines (build → test → package → deploy) with correct ordering and artifact reuse.
- Triggers & VCS roots: Branch filters, per-branch parameters, PR triggers with status reporting, and build-on-tag for releases.
- Agent management: Agent requirements, pools, elasticity, Docker-based agents, and resource constraints to avoid starvation.
- Build features & failure conditions: Commit status publisher, swabra/cleanup, test retries, failure-on-new-tests, and performance failure rules.
- Kotlin DSL & modularization: Settings.kts structure, reusable functions, typed parameters, and cross-project modules for large orgs.
- Secrets & compliance: Credentials parameters, masking, external secret stores, artifact signing, SBOMs, provenance (SLSA-minded) workflows.
- Integrations: Container registries, package managers, artifacts storage, issue trackers, chat, cloud providers, and deployment targets.
Common Use Cases (Map Them to Candidate Profiles)
- Monorepo pipelines: Partial builds/tests via path filters, build matrices for affected packages, and shared caches for fast PR feedback.
- Microservices CI/CD: Build chains that compile, test, scan, containerize, sign, push, and deploy per service with promotion gates.
- Mobile CI: iOS/Android with signing, provisioning, device farm tests, and artifact distribution to testers.
- Compliance-ready releases: SBOMs, license checks, vulnerability scans, and signed artifacts baked into release builds.
- Infrastructure pipelines: Terraform/Ansible with plan/apply gated by policy checks and change review, plus drift detection.
Anti-Patterns Strong Candidates Avoid
- Click-ops drift: Editing pipelines only in the UI; tough to code-review, reproduce, or roll back.
- Single giant build: Serializing compile, test, package, and deploy instead of using build chains and parallel stages.
- Unbounded logs & artifacts: No retention policies; slow UI and storage bloat over time.
- Agent starvation: Not sizing pools or constraints, causing long queues and random timeouts.
- Secret sprawl: Embedding credentials in scripts or env files; lack of rotation and masking.
- Ignoring flakiness: Treating flaky tests as normal noise; failing to quarantine, re-run, or fix root causes.
Adjacent Lemon.io Roles You May Also Need
Define the Role Clearly (Before You Post)
- Outcomes (90–180 days): “PR feedback < 10 min,” “Flake rate < 1%,” “Release pipeline with signed artifacts & SBOM,” “Parallel test time cut by 50%,” “Mean restore time from failed deploy < 10 min.”
- Stack & repos: Languages, package managers, container strategy, mono vs. polyrepo, and build toolchains (Gradle/Maven, npm/pnpm, .NET, etc.).
- Security posture: Secrets handling, artifact signing, policy checks, and provenance requirements (e.g., SLSA levels, SOC2/ISO evidence).
- Scale targets: Concurrency, daily build counts, peak event load (release days), agent capacity, and storage/retention budgets.
- Quality gates: Coverage thresholds, performance budgets, lint/type-check gates, and change-failure-rate targets.
Sample Job Description (Copy & Adapt)
Title: TeamCity Developer — Kotlin DSL • Build Chains • Secure CI/CD
Mission: Turn CI/CD into a reliable product: fast feedback, reproducible builds, secure artifacts, and safe, observable deploys for every service and app.
Responsibilities:
- Implement and maintain TeamCity pipelines in Kotlin DSL with reusable templates and typed parameters.
- Design build chains with snapshot/artifact dependencies for parallelism and reuse; tune caching and test splitting.
- Integrate scanners (SAST/DAST/SCA), SBOMs, license checks, and artifact signing; enforce policy gates.
- Manage agent pools, auto-scaling, and resource constraints; containerize build steps for reproducibility.
- Instrument pipelines with metrics, logs, and PR annotations; publish dashboards and actionable alerts.
Must-have skills: TeamCity admin & Kotlin DSL, build chains, agent management, Docker/containers, artifact/versioning strategy, and CI security basics.
Nice-to-have: Infrastructure as code (Terraform), policy-as-code (OPA/Conftest), package registries, mobile CI experience, and supply-chain security (signing, provenance).
How to Shortlist Candidates (Portfolio Signals)
- Kotlin DSL repos: Public or sanitized examples showing modular DSL, templates, shared steps, and strong parameterization.
- Measurable wins: Documented reductions in build time, flake rate, and meantime-to-restore; before/after dashboards.
- Operational maturity: Agent auto-scaling, failure conditions, retry policies, and storage/retention governance.
- Security & compliance: SBOMs, signed artifacts, secrets hygiene, policy gates, and audit-friendly logs.
- Developer experience: PR annotations, reproducible local runs, deterministic containers, and clear runbooks.
Interview Kit (Signals Over Trivia)
- Kotlin DSL design: “Show how you’d structure a monorepo pipeline with shared templates, per-package parameters, and path-based triggers.”
- Build chain performance: “We need PR feedback in <10 minutes. Which steps run on draft PRs vs. main? How do you split and prioritize tests?”
- Agent strategy: “Release days spike concurrency 4×. Outline agent pools, auto-scaling, and constraints to avoid starvation.”
- Security & supply chain: “Add SBOMs, license checks, and artifact signing. Where do you enforce policies and how do you report failures to developers?”
- Failure handling: “Deploy step fails 1% of the time after success in staging. Propose rollbacks, promotion gates, and failure conditions.”
- Observability: “Which metrics and logs show CI health? How do you avoid alert fatigue while catching regressions quickly?”
First 30/60/90 Days With a TeamCity Developer
Days 1–30 (Stabilize & Baseline): Audit current projects; export settings to Kotlin DSL; create shared templates; baseline PR feedback time, flake rate, queue time, and artifact storage; add essential failure conditions and masked parameters; document runbooks.
Days 31–60 (Speed & Reliability): Introduce build chains and parallelization; implement test splitting and retries with quarantine; warm caches and base images; create agent pools and auto-scaling; integrate SBOM and SCA scans; enable PR annotations and chat alerts.
Days 61–90 (Security & Scale): Add artifact signing and provenance; enforce policy-as-code; tune retention policies; add dashboards for CI KPIs; load-test release-day scale; ship blue/green or canary deploys with promotion pipelines; finalize quarterly CI roadmap.
Scope & Cost Drivers (Set Expectations Early)
- Concurrency & agents: Higher parallelism needs more agents and better caching strategies; costs scale with burst capacity.
- Monorepo vs. microservices: Monorepos need smart path filters and test splitting; microservices need template reuse and promotion pipelines.
- Security level: SBOMs, signing, policy gates, and audit logging add predictable—but valuable—work.
- Artifact footprint: Large artifacts and long retention policies increase storage costs and cleanup complexity.
- Mobile builds & special runners: iOS/macOS agents and device testing add capacity and licensing considerations.
Internal Links: Related Lemon.io Pages
Call to Action
Get matched with vetted TeamCity Developers—share your stack, repo model, and CI goals to receive curated profiles ready to ship fast, secure pipelines.
FAQ
- Why Kotlin DSL over configuring in the UI?
- Kotlin DSL makes pipelines versioned, reviewable, and reproducible. You can test changes, roll them back, and avoid config drift—crucial for scale and auditability.
- How can we speed up PR feedback without sacrificing coverage?
- Run fast linters/types/unit tests on PR, split slow suites, cache dependencies, and defer integration/e2e to post-merge or selective triggers. Use build chains to parallelize and prioritize.
- What’s the difference between snapshot and artifact dependencies?
- Snapshot dependencies enforce build order and revision alignment; artifact dependencies reuse outputs (e.g., compiled libs, images) to avoid rebuilding and to standardize inputs for later stages.
- How do we manage agents efficiently?
- Use pools per workload, set agent requirements, auto-scale with cloud agents, and pin heavy steps to capable runners. Keep base images warm and monitor queue/usage metrics.
- How do we integrate security into CI/CD?
- Add SCA/SAST/DAST steps with severity gates, generate SBOMs, sign artifacts, and enforce policy-as-code. Mask and rotate secrets; restrict build parameters and external access.
- What KPIs prove CI health?
- PR feedback time, queue time, flake rate, build success rate, change failure rate, mean time to restore, artifact storage growth, and agent utilization.
