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First American (India) seeks a senior full-stack engineer to provide technical leadership and join a hands-on engineering team. The role emphasizes AI-assisted development, guardrails, and scalable architectures.
You will mentor senior engineers and drive cross-team initiatives across AWS, TypeScript/Node.js, and React/Next.js. The ideal candidate will design, build, and operate production software while defining standards for delivery, security, and observability.
We are looking for senior full-stack engineer with sound hands-on to provide technical leadership and join our engineering team. This is a senior individual contributor role with no direct reports.
The ideal candidate will lead cross-team and cross-product initiatives, contribute directly to production software, establish engineering guardrails, build reusable frameworks and AI capabilities, and mentor senior engineers and technical leads. AI-assisted engineering is a baseline expectation. Strong experience with AWS, TypeScript/Node.js, React/Next.js, distributed systems, data architecture, security, and AI Engineering is required.
Lead cross-team and cross-product initiatives from design through production adoption
Design, develop, test, deploy, debug, and operate critical production software
Define architectural principles and guardrails while preserving team autonomy
Review high-risk designs for trade-offs, failure modes, security concerns, and integration risks
Build shared frameworks, libraries, services, and tooling that improve quality and delivery speed
Create reusable AI workflows, evaluations, validation mechanisms, and safety guardrails
Apply AI responsibly across design, coding, testing, documentation, debugging, and analysis
Establish standards for design, testing, code reviews, CI/CD, and release readiness
Improve reliability, scalability, performance, security, and observability
Lead major cross-product incident response and drive preventive actions
Design APIs, event-driven systems, distributed workflows, integrations, and data models
Translate product direction into technical strategies and implementation plans
Mentor senior engineers and technical leads and contribute to technical hiring
Demonstrated Staff Engineer-level impact across multiple teams, products, or domains
Experience leading complex initiatives through production delivery and adoption
Strong hands-on full-stack engineering skills and willingness to contribute directly to implementation
Deep experience with AWS and cloud-native, scalable, secure, and observable architectures
Strong proficiency in:
Strong understanding of distributed and event-driven systems, including:
Proficiency with AI-assisted development tools and agentic engineering workflows
Ability to:
Strong knowledge of:
Experience designing reliable, scalable, observable, and operationally supportable systems
Strong architectural judgment and experience building reusable capabilities adopted across multiple teams
Ability to mentor senior engineers and influence technical decisions without formal authority
Strong communication skills across engineering, product, architecture, and leadership teams
Experience building internal AI agents, evaluation systems, context frameworks, or AI safety guardrails
Experience defining engineering standards across multiple teams
Experience improving developer productivity through shared platforms, automation, or paved-road solutions
Experience with AWS services such as:
Experience with Infrastructure as Code (IaC), CI/CD, automated quality gates, and progressive delivery
Experience with Datadog, CloudWatch, distributed tracing, service-level objectives (SLOs), and incident reviews
Experience modernizing complex systems or building B2B SaaS and enterprise software platforms
The ideal candidate is a hands-on technical leader who can seamlessly move between organization-level architecture and production implementation. They define technical direction, build foundational software, and help multiple teams adopt it successfully.
They think in systems, lead through influence, and mentor technical leaders. They apply AI Engineering with discipline, using context, constraints, evaluations, and human review boundaries to improve delivery safely. They are motivated by building reusable systems, developing stronger engineers, enabling safer delivery, and creating more reliable products.
React, Next.js
AWS, serverless and cloud-native services, Infrastructure as Code
Relational and NoSQL databases, data integration, and data integrity
IAM, threat modeling, application security, cloud security
CI/CD, automated testing, observability, reliability, code reviews, design reviews
Coding agents, agent workflows, context engineering, evaluations, validation, and guardrails