Lead Forward Deployment Engineer

Job description

About The Role: We are looking for an architect-level Lead Engineer to own our custom internal tools initiative. You will lead a lean, AI-augmented team to design, build, and operate internal software that replaces major enterprise SaaS platforms. This role combines strong backend architecture and system design with hands-on delivery: you will define the technical blueprints, host and scale applications from scratch, and mentor new college graduates into productive engineers. What You'll Do: • Backend Architecture & System Design: Design scalable backend services, data models, and integration architectures for internal tools replacing complex SaaS platforms. Set and enforce architectural standards across the team. • Understanding Use Cases: Work directly with stakeholders to understand business use cases deeply, translate ambiguous requirements into clear technical designs, and make pragmatic build-vs-buy and scope trade-offs. • Hosting & Scaling from Scratch: Own the full lifecycle of internal applications — provisioning infrastructure, deploying, scaling, monitoring, and operating them in production. • CI/CD Ownership: Build and maintain end-to-end CI/CD pipelines with automated testing, code scanning, and branch-protection guardrails — the definitive quality gate for all code, including AI-generated code. • AI-Assisted Development: Use AI development tools (e.g., Claude Code, Cursor) to accelerate delivery, and establish team practices for reviewing, refactoring, and hardening AI-generated code. • Cross-Functional Collaboration: Partner with Sales, Pre-Sales, Project Management, and other internal teams to prioritize work, gather feedback, and iterate quickly. • Technical Mentorship: Guide new college graduates and junior engineers on architectural first principles, code quality, security, and effective AI-assisted development. What You Bring: • 7+ years building production-grade, full-stack applications (e.g., Python, Node.js, Go, React, relational and vector databases). • Strong backend architecture and system design skills — proven ability to design distributed systems and critically evaluate, refactor, and modularize sub-optimal code, including LLM-generated code. • Core knowledge of Kubernetes, Docker, cloud platforms (AWS/GCP), and distributed systems; experience running multi-service containerized environments in production. • Demonstrated experience hosting and scaling internal applications from scratch, including building CI/CD pipelines end to end (GitHub Actions, GitLab CI, or Jenkins). • Adept with AI development tools and agentic coding workflows; hands-on experience using them to ship real products. • Working knowledge of secure SDLC practices: automated static/dynamic code scanning, secret detection, and OWASP Top 10 awareness built into the pipeline. • Strong cross-functional collaboration and communication skills; able to work directly with non-engineering stakeholders and turn use cases into shipped software. • Track record of mentoring junior engineers.