Overview
This guide shows how Cornerstone tech recruiting delivers the right engineers, faster, with clear pricing and measurable outcomes. If you lead Engineering, Talent, or Operations, you’ll see exactly which roles we fill, how our process works, what it costs, and what results to expect.
We combine specialized technical recruiting services with operational discipline. Expect transparent SLAs, structured interviews, and security-first handling of candidate data.
Demand for engineering remains high. Software developer roles are projected to grow 25% from 2022–2032, according to the U.S. Bureau of Labor Statistics. Speed and quality matter.
In the sections below, we detail our roles-and-stacks coverage, end-to-end playbook, AI use cases with bias mitigation, compliance posture, pricing models, and role-specific interview kits. Use this to assess fit and decide how Cornerstone tech recruiting can move your roadmap forward.
Roles and tech stacks we recruit
You get a single partner able to hire across software, data, cloud, security, QA, product, design, and IT operations—from IC through leadership. The outcome is a calibrated pipeline matched to your stack and stage, without juggling multiple vendors.
Our team operates like a focused tech recruiting agency. We align on competencies, level, and stack before outreach, and we present tightly screened shortlists. With deep coverage across core functions and adjacent roles, we can spin up hiring sprints or run ongoing programs. Use this section to confirm we cover your priority roles and technologies.
Software engineering (backend, frontend, full-stack)
We recruit backend, frontend, and full‑stack engineers who can ship in your environment and lifecycle. We calibrate for language, framework, architecture, and delivery maturity (CI/CD, trunk-based, PR discipline).
Typical stacks include:
- Backend: Java, Kotlin, Go, C#, Node.js, Python; frameworks like Spring, .NET, Express, Django, FastAPI
- Frontend: TypeScript, React, Next.js, Vue, Angular; state and testing (Redux, Jest, Cypress)
- Full-stack: combinations of the above with GraphQL/REST, microservices, Docker/Kubernetes
We evaluate coding fluency, design tradeoffs, and collaboration patterns (code reviews, RFCs). Expect crisp signal on build/run ownership and impact at scale.
Data and machine learning
We place data engineers, analytics engineers, data scientists, ML engineers, and platform/ML Ops roles. Our screening separates modeling skill from productionization and governance.
Common stacks include:
- Data: Python, SQL, dbt, Spark, Airflow, Kafka, Snowflake, BigQuery, Redshift, Databricks
- ML: PyTorch, TensorFlow, scikit‑learn, MLflow, Kubeflow, SageMaker; vector DBs and LLM ops when relevant
We probe data modeling, pipeline reliability, feature lifecycle, and experiment design. You’ll see candidates who meet both statistical rigor and engineering quality bars.
Cloud, platform, and DevOps/SRE
We recruit platform engineers, SREs, DevOps, and cloud architects who improve reliability and developer velocity. We screen for systems thinking, IaC discipline, and observability depth.
Typical stacks include:
- Cloud: AWS, Azure, GCP; VPC design, identity, cost management
- Platform: Kubernetes, ECS, Terraform, Pulumi, Helm
- Observability: Prometheus, Grafana, Datadog, New Relic, OpenTelemetry; incident response and SLOs
We assess operability (toil reduction, runbooks, error budgets), change management, and real availability improvements.
Cybersecurity and GRC
We support blue team, red team, AppSec, cloud security, GRC, and leadership roles. Candidates bring practical hardening experience and risk frameworks aligned to your sector.
Coverage includes:
- AppSec/SecEng: SAST/DAST, SCA, threat modeling, secure SDLC
- CloudSec: IAM, KMS, network policies, CSPM
- GRC: SOC 2, ISO 27001, HIPAA, SOX; policy, audit, vendor risk
We align to trust frameworks such as the five SOC 2 Trust Services Criteria described by the AICPA SOC 2 Trust Services Criteria and ISO/IEC 27001’s ISMS standard (ISO/IEC 27001). Expect candidates who can reduce risk and pass audits.
Mobile and embedded/hardware
We fill native mobile, cross‑platform, and embedded roles where performance and reliability are non‑negotiable. We screen for platform internals and release discipline.
Coverage includes:
- Mobile: Swift/SwiftUI, Objective‑C, Kotlin, Jetpack Compose, React Native, Flutter
- Embedded: C/C++, Rust, RTOS, Yocto, device drivers, board bring‑up, lab tools (JTAG/oscilloscope)
We probe memory, concurrency, battery/network tradeoffs, and firmware update strategies to ensure shipped quality.
QA automation and test engineering
We recruit SDETs, QA automation, performance testers, and quality leaders who enable ship confidence and speed. We emphasize automation strategy over manual throughput.
Typical stacks include:
- Frameworks: Cypress, Playwright, Selenium, Appium
- Performance: JMeter, Gatling, k6; environment parity, data seeding
- CI/CD: test gating, flaky test control, coverage, and risk-based testing
Expect candidates who improve failure detection time and reduce mean time to restore.
Product management and UX/UI
We place PMs (core, growth, platform), product leaders, UX researchers, product designers, and UX writers. We index on customer obsession, prioritization, and clear delivery stories.
Signals we screen:
- Strategy: outcomes, roadmapping, metrics (north-star, guardrails)
- Discovery: research methods, hypothesis framing, experiment design
- Design: systems thinking, accessibility, prototyping, interaction craft
We ensure cross-functional fluency with engineering and go‑to‑market partners.
IT support, service desk, and systems/network
We fill help desk, desktop support, SysAdmin, IT Ops, and network engineers. We calibrate for SLAs, automation, and secure-by-default practices.
Coverage includes:
- Endpoint: MDM (Jamf, Intune), configuration baselines
- Systems: Windows/Linux admin, AD/Azure AD, scripting (PowerShell/Bash)
- Network: switching/routing, Wi‑Fi, VPN, SD‑WAN, firewall policies
Expect candidates who close tickets faster, reduce repeat incidents, and elevate user satisfaction.
How our tech recruiting process works from intake to offer
Our process is transparent, structured, and measurable from day one. You’ll know what happens each week, which signals we’re collecting, and when to expect submittals, interviews, and offers.
We scope success up front, build diverse pipelines quickly, and keep interviewers calibrated with structured scorecards. Along the way, we apply candidate experience best practices to lift acceptance rates. Use this section to confirm we match your operating cadence.
Discovery and role calibration
We start with a 60–90 minute intake to define success criteria, leveling, required competencies, and de‑risking factors. We convert your JD into a role scorecard with must‑have and nice‑to‑have signals.
We map interview loops to the scorecard. Examples include coding, systems design, behavioral, and values interviews. For senior roles, we add a business impact case.
This upfront clarity reduces misalignment and accelerates time‑to‑submit. Expect the first calibrated shortlist in 3–5 business days for most roles.
Sourcing channels and outreach
We blend outbound, referral mining, and inbound optimization to build diverse, qualified pipelines. Our sourcers target both active and passive talent with tailored messaging that reflects your value prop.
Channels include platforms like LinkedIn, GitHub, Stack Overflow, SeekOut, and curated communities.
We also run targeted campaigns and activate alumni/referral networks. Outreach is A/B tested for response and equity language. The goal is predictable weekly throughput without burning interview capacity.
Technical screening and structured interviews
Every candidate is screened against the scorecard using structured methods. We run calibrated phone screens, coding exercises, or live problem‑solving. We favor job‑relevant assessments over puzzles.
We use rubrics with level guides, define pass/fail anchors, and run interviewer calibration to reduce variance. Senior and specialist roles include systems design or architecture reviews. The result is consistent, defensible decisions that improve signal and reduce bias.
Candidate experience and employer branding
We operate a humane, transparent process that respects candidate time. This lifts close rates and protects your brand.
We set expectations, share timelines, and provide prompt feedback. We equip candidates with interview prep and realistic role context to avoid late‑stage surprises. Post‑interview debriefs are scheduled within 24–48 hours to keep momentum. Strong CX is a competitive edge in tight markets.
Offer management and acceptance
We drive to a clean, timely close by aligning on compensation early and de‑risking concerns. We advise on bands, equity, and benefits competitiveness.
We coach hiring teams on narrative—impact, growth path, manager, culture—and coordinate references as a two‑way diligence tool.
We also manage resignations and start logistics. The result is fewer stalls and higher acceptance.
Tools we use across recruiting operations and technical assessment
Our stack blends ATS/CRM, sourcing tech, assessments, and collaboration tools with security controls that protect candidate data. You’ll know what runs under the hood and how we integrate with your systems.
We can operate in your ATS for RPO/embedded programs or in our own environment for search projects. Where AI is used, we keep humans in the loop and maintain audit trails.
ATS/CRM and sourcing technology
We typically work with market-leading ATS/CRMs and sourcing platforms that integrate via APIs and webhooks to keep data current and secure.
Common systems we support include Greenhouse, Lever, Ashby, Workday, and SmartRecruiters for ATS; Gem, SeekOut, and LinkedIn Recruiter for sourcing/CRM. We align data models (stages, tags, sources) and enforce access controls by role.
For embedded programs, we adopt your stack to preserve reporting continuity.
Coding and systems design assessments
We use role-relevant evaluations that mirror on‑the‑job work. Options include structured phone screens, practical take‑homes with strict time boxes, and live pair‑programming.
For coding, we calibrate difficulty to level and evaluate correctness, complexity handling, and communication. For systems design, we assess requirements capture, tradeoffs, scalability, and failure modes. We avoid gotchas and ensure every assessment has a clear rubric and feedback loop.
Collaboration and security controls
We coordinate with Slack/Teams, project trackers, and calendaring to keep hiring in lockstep.
Security is table stakes. We align to SOC 2 and ISO 27001 principles in how we handle PII: least‑privilege access, MFA, encrypted storage, and periodic audits. We can sign DPAs and support vendor security reviews.
Engagement models and pricing for tech hiring
Choose the model that fits your stage and volume: contingency search, retained/engaged search, RPO/embedded, or contract/C2H. We publish ranges and terms so you can decide quickly.
All models include structured process, reporting, and compliance. Guarantees and volume discounts help de‑risk your decision. Use this section to match model-to-need.
Contingency search
Best when you need 1–5 hires per function without upfront fees. You pay only on successful placement.
Typical terms:
- Fee: 18%–25% of first‑year base salary
- Guarantee: 60–90‑day replacement window
- Delivery: first shortlist in 3–5 business days; typical time‑to‑fill 25–45 days for engineers
Use this when roles are common enough for competitive sourcing and you value speed and flexibility.
Retained/engaged search
Ideal for executives, niche specialists, or confidential roles requiring deep market mapping and proactive alignment.
Typical terms:
- Fee: 25%–35% of first‑year comp (base or OTE), with an engagement fee (1/3 upfront, 1/3 shortlist, 1/3 offer)
- Milestones: research brief, longlist, shortlists, calibrated interviews
- Guarantee: 90–120‑day replacement
Use this when precision, stakeholder management, and confidentiality outweigh breadth.
RPO and on-demand/embedded recruiters
Designed for scale (multi‑hire programs), surges, or to stand up talent operations. We place dedicated recruiters/sourcers working inside your systems.
Typical terms:
- Pricing: monthly per recruiter/sourcer or outcome‑based; typical ranges $18,000–$28,000 per recruiter/month depending on scope
- Throughput: 3–6 hires per recruiter per month depending on role mix
- SLAs: weekly submittals, interview-to-offer ratios, time‑to‑fill targets
Choose this when you need repeatable throughput and employer brand continuity.
Contract and contract-to-hire
Use contractors to move fast, manage budgets, or de‑risk new headcount. C2H gives you try‑before‑you‑buy flexibility.
Typical terms:
- Bill rates: engineers at $85–$160/hour depending on stack and market
- Markup: aligned to benefits, payroll taxes, and compliance
- C2H conversion: prorated or waived after a minimum hours threshold (e.g., 1,000–1,500 hours)
This model manages delivery risk while keeping optionality.
Guarantees, replacements, and volume discounts
We align incentives with performance. Guarantees vary by model, seniority, and exclusivity.
Common options:
- Replacement windows: 60–120 days
- Volume discounts: tiered fees for 5+, 10+, 25+ hires
- Exclusivity incentives: reduced fees or extended guarantees
We’ll recommend the structure that best balances speed, cost, and risk for your goals.
Geographic reach, remote capability, and compliance posture
We hire across the U.S., support remote‑first teams, and can extend to nearshore/offshore through trusted partners. We also advise on visas, clearances, and compliance frameworks.
Security and equity are built in. Expect data privacy controls, EEOC/OFCCP practices, and AI governance. Use this to confirm we can support your geography and regulatory needs.
U.S. markets, remote-first, and global/nearshore support
We run programs across major U.S. metros and fully remote teams. For nearshore/offshore, we partner with vetted networks and can coordinate with your EOR provider.
We calibrate comp to market and set interview hours to accommodate time zones. Where needed, we can refer reputable EOR options and align on payroll/compliance workflows.
The outcome is predictable delivery regardless of location.
Visa and clearance considerations
We understand immigration timelines and clearance constraints and scope accordingly.
We support H‑1B transfers, TN, OPT/CPT, and green card strategy in partnership with your counsel; see USCIS H‑1B for official guidance. For public trust/DoD roles, we recruit cleared talent and follow agency requirements; see the Defense Counterintelligence and Security Agency for clearance processes. We’ll set realistic timelines and screening workflows.
Data privacy, EEOC/OFCCP, and security certifications
We align our operations with U.S. equal opportunity and federal contractor standards and modern security frameworks.
Practices include:
- EEOC‑aligned hiring and adverse‑impact monitoring
- OFCCP Internet Applicant recordkeeping where applicable
- Security alignment with SOC 2 and ISO 27001 principles
This gives stakeholders confidence in fairness and data handling.
Role-specific interview kits and scorecards
Structured scorecards reduce noise, speed decisions, and improve fairness. Below are concise kits you can adopt or adapt.
Each kit defines competencies, example prompts, and pass/fail anchors. Use them to calibrate interviewers and improve signal from the first loop.
Senior software engineer
Competencies: code quality, systems design, ownership, and collaboration.
- Coding: medium complexity problem; assess correctness, complexity handling, and testability. Pass if candidate produces clean, tested code and explains tradeoffs.
- Systems design: design a scalable feature (e.g., rate‑limited API); assess requirements capture, data modeling, consistency choices, failure modes. Pass if design is coherent with clear tradeoffs.
- Behavioral: ownership story; incident or project rescue; collaboration with product/design. Pass if examples show impact and accountability.
Decision rule: hire if two strong signals (coding + design) with no red flags and culture add.
DevOps/SRE
Competencies: reliability engineering, automation, observability, and incident management.
- Deep dive: walk through an SLO and error budget; discuss how it informed change velocity. Pass if candidate ties metrics to operational decisions.
- Systems: explain CI/CD design for a microservices platform; IaC choices and rollback plans. Pass if plan reduces toil and risk.
- Incident: postmortem case; MTTD/MTTR reduction actions. Pass if they demonstrate blameless culture and durable fixes.
Decision rule: hire if they demonstrate measurable reliability improvements and strong runbook thinking.
Data engineer
Competencies: data modeling, pipeline reliability, performance, and governance.
- Modeling: design a star schema for analytics vs. data vault tradeoffs. Pass if model supports query patterns and change management.
- Pipelines: build/operate a CDC pipeline with late‑arriving data; assess idempotency and backfills. Pass if they balance latency vs. correctness.
- Quality/governance: testing strategy, lineage, and privacy considerations. Pass if they propose scalable checks and documentation.
Decision rule: hire if they show end‑to‑end ownership and production reliability.
AI in our recruiting workflows: use cases, outcomes, and risk mitigation
We use AI to increase coverage and reduce cycle time—never to replace judgment. Humans make decisions; AI accelerates research and matching.
Our program aligns to the NIST AI Risk Management Framework, with bias controls and auditability. Use this to understand where AI helps and how we keep it fair.
Sourcing and matching accelerators
We apply AI to parse profiles, enrich skills, and prioritize outreach targets based on scorecard fit. It improves top‑of‑funnel coverage and time‑to‑submit.
Outputs are always reviewed by recruiters before contact. We test prompts/models, measure uplift, and turn off features that degrade diversity or quality. The result is broader, faster pipelines without false positives flooding interview loops.
Bias mitigation and human-in-the-loop
We strip non‑signal attributes where possible, use structured scorecards, and run regular calibration sessions.
AI suggestions never auto‑advance candidates. Recruiters verify evidence against competencies. We monitor stage‑by‑stage rates for adverse impact patterns and adjust sourcing/interview steps accordingly. Fairness remains a leadership metric, not a side note.
Auditability and governance
We log model versions, prompts, and decision checkpoints for review. Access is role‑based and monitored.
Vendors are vetted for security and compliance. We align with SOC 2/ISO 27001 data practices and NIST AI RMF principles to reduce risk. This governance protects candidates, clients, and outcomes.
Benchmarks, SLAs, and throughput capacity
We publish program targets and typical outcomes so you can set expectations. Metrics vary by role, market, and brand strength; we calibrate with you up front.
As a reference point, LinkedIn’s research cites a 44‑day global median time‑to‑hire across roles (LinkedIn time-to-hire research). Our tech programs are designed to beat that for most roles with structured pipelines.
Time-to-submit, interview, and fill
We operate to the following targets for common tech roles:
- Time‑to‑submit: 3–5 business days for first calibrated shortlist
- Time‑to‑interview: 5–10 business days from shortlist to first loop
- Time‑to‑fill: 25–45 days for senior software engineers in major U.S. metros; 35–60 days for niche/lead roles
We’ll set role‑ and market‑specific SLAs during intake and report weekly.
Offer-acceptance and 90-day retention
Quality shows up in acceptance and retention. Our targets are:
- Offer‑acceptance rate: 80%–90% with aligned compensation and clear role context
- 90‑day retention: 95%+ for FTE placements with structured onboarding
We review these outcomes quarterly and adjust sourcing and assessment to improve where needed.
Hiring sprints and scaling timelines
For growth programs, we structure sprints with predictable throughput.
- Typical sprint: 6–12 hires in 6–10 weeks per function
- Embedded/RPO capacity: 3–6 hires per recruiter per month, mix‑dependent
- Lead‑time to spin up: 1–2 weeks for embedded teams; 3–5 business days for search
This lets you phase headcount with roadmap milestones.
Case studies and ROI from recent tech hiring programs
Numbers matter more than narratives. Here are anonymized outcomes with methodology notes so you can benchmark.
We track cycle time, interview efficiency, acceptance rates, and ramp impact. We compare to pre‑program baselines where available.
Startup hypergrowth sprint
Scenario: Series B SaaS company needed 10 engineers in 8 weeks to hit a launch window.
- Outcome: 12 hires (8 backend, 2 frontend, 2 SRE) in 9 weeks; time‑to‑fill averaged 32 days
- Acceptance: 87% acceptance rate after leveling bands and adding a systems design preview
- ROI: Avoided 2‑month release slip; estimated $1.2M revenue preserved based on forecast
Method: Embedded recruiter + sourcer + weekly calibration; structured loop and hiring manager training.
Mid-market platform modernization
Scenario: Replatforming to microservices/cloud required specialist hires across platform and data.
- Outcome: 7 hires in 10 weeks (platform, SRE, data, QA); incident rate dropped 28% after 90 days
- Efficiency: Interview‑to‑offer ratio improved from 10:1 to 4:1 through better pre‑screens
- ROI: Reduced on‑call toil and faster deploys; backlog burn‑down accelerated by 22%
Method: Retained search for lead roles + contingency for ICs; introduced SLOs and design rubrics.
Security uplift in regulated industry
Scenario: Healthcare org needed AppSec and GRC uplift pre‑audit.
- Outcome: AppSec lead + GRC manager placed; SOC 2 audit passed with fewer corrective actions
- Timeline: 45 and 41 days to fill respectively
- ROI: Reduced vendor risk backlog by 35% and unlocked enterprise deals
Method: Retained search; candidates evaluated against SOC 2/ISO 27001 controls and audit experience.
Agency vs in-house vs RPO vs embedded: model comparison for tech teams
No single model fits every stage. This section helps you weigh speed, quality, and cost across options.
We’ll recommend a model based on your volume, role mix, budget, and maturity. We can shift models as needs change.
Speed and quality-of-hire
- Agency search is fastest for targeted roles; you get immediate pipeline and calibrated shortlists.
- RPO/embedded balances speed with brand continuity; interview load is managed centrally.
- In‑house can be high quality but spins up slower without existing pipelines and process infrastructure.
Choose the model that maintains interview signal and reduces rework for your leaders.
Cost and total ROI
- Contingency fees are variable; you pay only on success—efficient for sporadic hires.
- RPO/embedded smooths cost per hire at scale and builds durable process/IP.
- In‑house requires fixed overhead and tooling; ROI grows with steady volume.
Model ROI should include vacancy cost, ramp time, and manager hours saved—not just fee percentages.
When to choose each model
- Contingency: 1–5 hires, common stacks, need speed and flexibility.
- Retained: executive/niche/confidential, complex stakeholder management.
- RPO/embedded: 5+ monthly hires, new function build‑out, or sustained scale.
- Contract/C2H: budget flexibility, uncertain long‑term need, or pilot initiatives.
We can blend models across functions to optimize outcomes.
Post-hire onboarding and success enablement
Hiring is step one; successful ramp and retention complete the ROI. We extend support through structured onboarding touchpoints.
We align with managers on expectations, feedback cadence, and risk flags to protect your investment.
First 30/60/90-day alignment
We co‑create a 30/60/90 with objectives, stakeholders, and success signals. Managers commit to weekly one‑on‑ones and early feedback.
At 30 days, confirm environment and scope. At 60, measure first deliverables. At 90, assess impact and growth plan. Clear checkpoints reduce early attrition and set a positive trajectory.
Feedback loops and retention checks
We run candidate and manager check‑ins at 2 and 8 weeks to surface risks early. If something’s off, we intervene quickly.
We aggregate feedback to refine sourcing, assessment rubrics, and onboarding kits. This loop raises quality-of-hire and protects acceptance and retention metrics over time.
Next steps and how to get started
If you’re ready to accelerate hiring with clarity and accountability, we’ll start with a short discovery. You’ll leave with a tailored plan, model recommendation, and SLAs.
Share your roles and goals, and we’ll propose the right mix—search, retained, RPO/embedded, or contract/C2H—plus pricing, guarantees, and a first‑week delivery plan. Let’s build a calibrated pipeline that your team is excited to interview and hire.