Senior Full Stack Engineer/ Extensive AI-Driven Development

The Opportunity

We're hiring a Senior Full Stack Engineer to drive the technical execution of our core platform. You'll work alongside our CTO and product leadership to design scalable systems, mentor our engineering team, and deliver features that directly power property managers across the US. This is a high-ownership, high-visibility role - not just a coding seat.

You will also have fundamental responsibility for driving the structure and adoption of AI-driven development, testing, deployment, etc. and must come to the job with true expertise in organizing an engineering team and platform to maximize this effectiveness.

What You'll Do

• Fundamental responsibility for driving the structure and adoption of AI-driven development, testing, deployment, etc. and must come to the job with true expertise in organizing an engineering team and platform to maximize this effectiveness.
• Architect and lead development of full-stack features across our SaaS platform using Node.js, React, and AWS
• Partner with the CTO and Product team to translate business requirements into scalable, maintainable technical solutions
• Own the full SDLC - from functional specification and design through implementation, testing, and production support
• Lead and mentor engineers; conduct code reviews, set standards, and build a culture of technical excellence
• Drive cloud infrastructure decisions on AWS (Lambda, RDS, serverless architecture)
• Establish and enforce development best practices: design patterns, testing standards, CI/CD pipelines
• Communicate technical progress, risks, and trade-offs clearly to senior leadership and non-technical stakeholders
• Contribute to hiring, onboarding, and growing the engineering org as we scale

What We're Looking For

Required

• 2+ Years driving the structure and adoption of AI-driven development, testing, deployment across a complex codebase. Preference for ClaudeCode, though Codex is also acceptable.
• 7+ years of professional software engineering experience
• Deep expertise in Node.js and at least one modern frontend framework (React preferred; Angular or Vue also considered)
• Strong command of MySQL, Postgres, and AWS RDS for relational database design and query optimization
• Hands-on AWS experience - Lambda, EC2, S3, RDS, API Gateway, and serverless patterns
• Proficiency in scripting with Python for automation and backend tooling
• Solid understanding of design patterns, multithreaded environments, and distributed systems
• Experience mentoring engineering teams and managing cross-functional priorities in a fast-paced environment
• Unix/Linux systems experience and Git-based version control workflows
• Fundamental understanding of the business concept endlessly repeated by the CTO: "YES, BUT FASTER."
• Excellent verbal and written communication, bridging the gap between Engineering, Product, Executive Leadership and, occasionally, our Customers.

AI Specifics

• 2+ Years driving the structure and adoption of AI-driven development, testing, deployment across a complex codebase. Preference for ClaudeCode, though Codex is also acceptable.
• Demonstrated experience tailoring agentic coding environments to project-specific conventions, including custom workflows, lifecycle automation, and tool integrations, with measured impact on team velocity and code quality.
• Experience architecting systems with AI-maintainability in mind, including schema-first patterns, single-source-of-truth derivations, clean module boundaries, and predictable interfaces that reduce LLM hallucination surface area.
• Track record of designing or adopting code conventions and engineering guardrails that prevent common LLM failure modes such as hallucinated APIs, scope creep, type-system bypasses, and schema duplication.
• Experience producing and maintaining technical documentation in formats that AI tools can read, write, and keep in sync with code, including code-based diagrams, decision records, and domain references.
• Ability to evaluate AI tooling options across cost and capability tiers, and to make selection decisions appropriate to team segment, task type, and quality/cost tradeoffs.
• Demonstrated experience tailoring agentic coding environments to project-specific conventions, including custom workflows, lifecycle automation, and tool integrations, with measured impact on team velocity and code quality.
• Experience architecting systems with AI-maintainability in mind, including schema-first patterns, single-source-of-truth derivations, clean module boundaries, and predictable interfaces that reduce LLM hallucination surface area.
• Track record of designing or adopting code conventions and engineering guardrails that prevent common LLM failure modes such as hallucinated APIs, scope creep, type-system bypasses, and schema duplication.
• Experience producing and maintaining technical documentation in formats that AI tools can read, write, and keep in sync with code, including code-based diagrams, decision records, and domain references.
• Ability to evaluate AI tooling options across cost and capability tiers, and to make selection decisions appropriate to team segment, task type, and quality/cost tradeoffs.
• Familiarity with model reasoning-depth controls and their cost-quality tradeoffs, and a habit of applying new prompt patterns and model capabilities as the frontier evolves.
• Expansive familiarity with the information sources, communities, and channels that surface cutting-edge AI capabilities, tooling, and trends.
• Experience designing AI-augmented CI/CD pipelines - code review, eval gates, test generation, changelog generation, deployment-aware automation - and measuring their impact on PR throughput, bug rates, time-to-merge, and code-review burden.
• Experience leading refactoring, migration, or modernization work with AI tooling as a force multiplier, with concrete examples of velocity and quality outcomes.
• Familiarity with empirical AI productivity research and the practice of validating tool adoption with measurement before scaling.
• Track record of mentoring engineers across mixed AI-fluency levels and cost / IP / budget constraints.

Education

B.E. / B.Tech / M.Tech in Computer Science, Electronics & Communication, or Information Technology - or equivalent practical experience.