Senior engineers embedded in your team by discipline — within a week.
Hiring full-time takes three to six months. Agencies give you juniors and call them a team. We embed senior engineers directly into your existing team by discipline — frontend, backend, DevOps, design, QA, or project management. They work in your tools, join your standups, and own outcomes, not just tickets. No recruitment overhead, no long notice periods, no commitment beyond the project scope.
Matched to your stack and working alongside your team within a week
Senior engineers only — no bait-and-switch to juniors after the contract is signed
Work in your tools, attend your standups, own outcomes not just tickets
Fixed weekly rate with milestone-based structure — no open-ended billing
RaftLabs provides dedicated development teams organised by discipline: frontend (React, Next.js, TypeScript), backend (Node.js, Python, Go, PostgreSQL), DevOps and cloud (AWS, GCP, Docker, Kubernetes, Terraform), UX/UI design (Figma, research-led), QA engineering (Playwright, Cypress, automated test suites), and project management (sprint delivery, milestone reporting). Engineers are embedded into the client's existing team and work in the client's tools. Engagements start within one week. All work is fixed-rate with milestone-based structure and no long-term commitment beyond project scope.
Trusted by
Embedded engineers who own outcomes, not just tickets
The difference between a contractor and an embedded engineer is accountability. A contractor completes the tasks assigned. An embedded engineer understands the product context, raises problems before they compound, and cares whether the sprint delivers.
RaftLabs dedicated teams embed at the discipline level — a senior engineer matched to your stack, working inside your processes, accountable to your team lead. No agency-layer overhead between them and the work.
Disciplines
What we embed
Frontend engineering
Senior frontend engineers embedded at React 18/19 + Next.js 13--16 (App Router and Pages Router), Vue 3 + Nuxt 3, TypeScript (strict mode), and Tailwind CSS v3/v4. Engineers assessed on your specific framework version and existing codebase patterns before matching -- an engineer embedded into a Next.js App Router codebase with Tailwind v4 is not the same profile as one joining a Vue 3 + Pinia + Vite SPA, and we do not pretend otherwise. Technical depth expected at senior level: rendering strategy decisions (SSR vs ISR vs client-side per route based on data freshness and SEO requirements); Core Web Vitals optimisation (LCP, CLS, INP -- not just Lighthouse scores); component architecture patterns (compound components, context vs Zustand vs Redux Toolkit for state management based on the specific problem); bundle analysis and code splitting for Time to Interactive reduction; and WCAG 2.1 AA accessibility implementation rather than surface-level aria attribute decoration. Design system work: Storybook component library maintenance, design token implementation, and Figma-to-code handoff that does not require a back-and-forth interpretation cycle. The engineer joins your Jira or Linear board, follows your branching strategy, participates in your code review process, and ships working software to your staging environment from sprint one -- not from sprint three after spending two sprints on environment setup.
Backend engineering
Senior backend engineers matched to your specific runtime and data stack -- Node.js with NestJS or Fastify, Python with FastAPI or Django, Go, or Java with Spring Boot -- with the database and infrastructure experience appropriate to your current architecture. Technical assessment before matching: the engineer can explain the difference between horizontal and vertical scaling for your specific data pattern; knows when to use Redis pub/sub vs a message queue (Kafka, RabbitMQ, AWS SQS) for the event pattern you're building; and has designed a PostgreSQL schema or query optimisation approach for a table at a scale similar to yours. API design at senior level: REST endpoint design that your frontend team can rely on without constant negotiation about response shape; GraphQL resolver implementation with DataLoader for N+1 prevention; Webhook event handling with idempotency keys; and background job architecture with retry logic, dead letter queues, and monitoring. Authentication and security: OAuth 2.0 PKCE flows, JWT validation and rotation, RBAC permission models, and parameterised queries as a default -- not an afterthought. Database work expected without supervision: schema design for normalisation vs query performance trade-offs, query explain-plan analysis, index strategy, and PostgreSQL VACUUM and autovacuum configuration for your write volume. Integration work: third-party API integration with rate limit handling, circuit breakers, and retry logic that does not crash your application when a downstream service is slow. Matched to your existing data model -- no proposing a rewrite of working systems unless you ask for it.
DevOps and cloud
DevOps engineers embedded for specific infrastructure outcomes rather than general cloud administration. Engagement scopes matched to the gap: CI/CD pipeline setup (GitHub Actions or GitLab CI pipeline with build, test, security scan, and deployment stages; branch-based environment promotion from feature to staging to production; deployment rollback triggered by health check failure); containerisation and Kubernetes (Dockerfile optimisation for layer caching and image size; Kubernetes deployment configuration with resource requests/limits, pod disruption budgets, and horizontal pod autoscaler; Helm chart setup for release management); infrastructure as code with Terraform (state management in S3 with locking via DynamoDB; module structure for reusable infrastructure components; plan-and-apply workflow in CI); and AWS or GCP architecture (VPC design with public/private subnets and NAT gateway; RDS Multi-AZ setup; ECS Fargate vs EKS decision based on your operational capacity; cost tagging and Reserved Instance purchase recommendations). Monitoring setup: CloudWatch or Datadog dashboards with p50/p95/p99 latency and error rate per service; PagerDuty alerting with runbook links on every alert; distributed tracing setup with AWS X-Ray or OpenTelemetry. Security posture: IAM least-privilege role design; AWS Security Hub or GCP Security Command Center configured; secrets management with AWS Secrets Manager or HashiCorp Vault. Engineers who have operated the infrastructure they build -- they know which Kubernetes node issues surface at 2am, not just how to configure the cluster.
UX/UI design
Product designers embedded at two levels -- execution-focused and research-and-strategy-focused -- and matched based on what your engagement actually needs. Execution-level engagement: the product requirements are defined, the patterns are established, and you need a Figma-native designer who can work from your existing design system to produce pixel-accurate screens, interaction states, and developer-ready specs that your frontend team can implement without a daily interpretation conversation. At this level: Auto Layout mastery, component variant architecture, design token management, and handoff annotations in Figma Dev Mode that answer the questions developers would otherwise ask ("what happens at 375px?", "what is the hover state?", "what is the empty state?"). Research-and-strategy engagement: you are defining a new product or major feature and need validated direction before building. User interview moderation (semi-structured interview protocol, recruit from your existing user base or via Respondent.io), synthesis using affinity mapping and Jobs-to-be-Done framework, usability testing on prototype or live product with think-aloud protocol, and journey mapping for the end-to-end user experience. Design system work: component audit against existing design, token extraction, Figma library restructuring for team-scale use, and WCAG 2.1 AA colour contrast and touch target compliance audit. The designer works in your tools (Figma, Linear or Jira, Slack), joins your design reviews, and updates assets in the shared Figma file your team uses -- not in a separate file that has to be reconciled after the engagement ends.
QA engineering
QA engineers who build test automation infrastructure rather than executing manual test scripts -- the difference between a regression suite that runs on every PR and a spreadsheet of manual steps someone runs before a fortnightly release. Test automation stack: Playwright for end-to-end browser testing (cross-browser on Chrome, Firefox, Safari; mobile viewport simulation; network intercept for API mocking in E2E scenarios); Cypress for component-level integration testing within React applications; Jest or Vitest for unit tests on business logic functions with coverage thresholds enforced in CI. API testing: Supertest or Postman/Newman collection runs in CI for REST API contract testing; GraphQL schema compliance testing. Performance and load testing: k6 scripts for load profile definition (ramp-up, sustained load, spike scenarios) with Grafana k6 Cloud or a self-hosted InfluxDB + Grafana dashboard for result visualisation; Lighthouse CI for Core Web Vitals regression detection on every PR. Embedded in the sprint process: acceptance criteria in each user story are translated into automated test cases before development starts (BDD approach with Gherkin scenarios where the team prefers it, or direct Playwright test specs); tests are committed alongside the feature code in the same PR; CI pipeline fails on test regression before the PR can merge. Exploratory testing for new features: session-based exploratory testing with documented coverage notes, bug reports filed in your issue tracker with steps-to-reproduce, screenshots, and HTTP Archive (HAR) files for API debugging context.
Project management
Project managers embedded into your team who own sprint outcomes rather than coordinating around them -- the distinction being that they push back on unscoped work entering a sprint mid-cycle, escalate delivery risks before they compound, and take responsibility for communicating what is and is not achievable in the time available rather than waiting for the retrospective to document the miss. Sprint facilitation: two-week sprint cycle with kick-off planning (story point estimation review, acceptance criteria validation before commitment, velocity-based capacity planning), daily standup facilitation (synchronised, focused, 15-minute maximum), mid-sprint scope change evaluation (impact assessment before any change is accepted into the running sprint), and sprint review and retrospective structure that produces actionable improvement items rather than a venting session. Backlog management: user story writing with clear acceptance criteria (given/when/then format or explicit definition of done), technical task decomposition with engineering estimates, dependency mapping between epics and stories, and quarterly roadmap grooming with the product owner. Delivery reporting: weekly status report for stakeholders covering sprint progress vs plan (% stories completed vs planned), risks and mitigation actions (not discovered-at-end surprises), budget burn vs milestone completion, and blockers with owner and resolution date. Risk management: formal risk register maintained with likelihood, impact, and mitigation per risk; risks reviewed weekly and surfaced to stakeholders before they become issues. Technical grounding: PMs who can read a pull request, understand what a migration script does, and evaluate the technical argument for a scope trade-off -- not coordinators who relay decisions between the engineer and the stakeholder and introduce latency at every step.
How the engagement works
The process is designed to remove overhead, not add it. Most engagements are running within a week.
Step 1 — Requirements call (1 hour): We understand your stack, your team structure, the specific gap you need to fill, and your expected engagement length. We identify the right discipline and seniority level.
Step 2 — Match and introduction (2–3 days): We match an engineer against your stack and requirements. You meet them in a 30-minute technical introduction. If the fit is wrong, we rematch before the engagement starts.
Step 3 — Onboarding (day 1): The engineer is added to your tools, given access to your repositories, and joins your next standup. The first sprint starts.
Step 4 — Ongoing: Weekly check-in between your lead and our account manager. Monthly delivery review. Continuous availability for any issues between check-ins.
What discipline does your team need right now?
Tell us your stack, the gap you need filled, and your timeline. We match and start within a week.
Product Engineering -- Long-term engineering partnership for product iteration and scaling
DevOps -- Infrastructure, CI/CD, and deployment management for your engineering team
Quality Assurance -- Automated testing and QA-as-a-service for software teams
Frequently asked questions
Most engagements begin within 5 to 7 business days. We match an engineer to your stack and project requirements, schedule a short technical introduction call with your team lead, and embed them into your standups and tooling. The onboarding process is designed to be lean — the engineer is productive in the first week, not still getting set up at the end of week two.
We embed engineers across six disciplines: frontend (React, Next.js, Vue, TypeScript), backend (Node.js, Python, Go, PostgreSQL, MongoDB), DevOps and cloud infrastructure (AWS, GCP, Docker, Kubernetes, Terraform), UX/UI design (Figma, product design, design systems), QA engineering (Playwright, Cypress, automated test suites), and project management (sprint facilitation, delivery reporting, stakeholder communication). You can embed one discipline or a combination, depending on the gaps in your team.
Platform contractors are vetted for skills but not vetted for your specific stack, project context, or team culture fit. You manage the relationship, the performance, and the integration entirely. RaftLabs matches based on your specific technical stack and project requirements, handles the commercial structure, and provides an account manager who monitors delivery quality and can replace an engineer if needed. The engagement is a partnership, not a marketplace transaction.
Pricing depends on discipline, seniority level, and engagement length. A senior frontend or backend engineer typically runs $4,500 to $7,500 per month. A DevOps engineer or QA lead runs $4,000 to $7,000 per month. Design rates depend on whether the scope is execution (pixel work) or product design (research, systems, strategy). All engagements use a fixed weekly rate with milestone-based structure. We quote after understanding your specific requirements — team size, stack, engagement duration, and expected output.
Yes. Dedicated engineers work in your tools — GitHub or GitLab for source control, Jira or Linear for task management, Slack or Teams for communication, Figma for design handoff, whatever your team uses. They attend your standups, follow your branching strategy, participate in your code review process, and report to your team lead. The goal is seamless integration, not a parallel process that creates coordination overhead.
We handle replacement. If an engineer is not the right fit technically or culturally — assessed after the first two weeks — we replace them without additional cost or delay. We do not expect you to manage the performance issue directly. That is our responsibility. Fit mismatches are uncommon because our matching process is thorough, but when they happen, the process to resolve them is fast and clear.
The minimum engagement is four weeks. Most teams run engagements of three to six months, with the option to extend on a rolling basis. There is no long-term commitment required at the start — you engage for a defined period, evaluate the fit and output, and extend if it is working. We do not lock you into a 12-month contract to start an engagement.
Work with us
Tell us what you need. We'll tell you what it would take.
We scope Dedicated Development Teams in 30 minutes. You walk away with a clear cost, timeline, and approach. No commitment required.
Scope and cost agreed before work starts. No surprises. No obligation.
Working prototype within 3 weeks of kickoff.
Pay by milestone. You see progress before each invoice.
60-day post-launch warranty. Bug fixes, UI tweaks, and deployment support. No retainer.
