Software Engineer - AI-Augmented Software Development
2 days ago
San Francisco
Job Description: Software Engineer – AI-Augmented Software Development Role Summary We are seeking a Software Engineer – AI-Augmented Software Development, who can drive the next generation of software engineering by combining strong technical depth with expertise in GenAI, agentic workflows, and AI-augmented software development. This is not a traditional engineering role. We are looking for someone who can design and implement AI-driven software engineering process, establish best practices, and lead how AI is used across the SDLC—not just write code faster. You are expected to use AI as a force multiplier across the entire SDLC, including design, coding, testing, debugging, documentation, and production support. You will play a key role in defining how teams build, test, deploy, and operate software using AI, while ensuring quality, security, and scalability at an enterprise level. Locations: San Francisco, CA, Dallas, TX and Austin, TX Key Responsibilities • Define and implement AI-augmented software development process, including the use of GenAI tools, coding assistants, and agentic systems across development, testing, debugging, and documentation, • Design and operationalize agent-based software development processes, where multi-step engineering tasks (feature development, bug fixing, modernization) are executed through structured AI workflows, • Design and development of scalable, secure software systems while actively contributing hands-on to architecture, coding, and critical problem-solving, • Establish standards, guardrails, and best practices for AI-assisted development, including prompt design, validation frameworks, security constraints, and quality benchmarks, • Break down complex engineering problems into structured, AI-executable tasks with clear context, constraints, and validation criteria, enabling consistent and scalable AI-assisted delivery, • Effectively leverage AI by reviewing and validating outputs, identifying hallucinations, security risks, incomplete implementations, and architectural gaps before production use, • Drive improvements in engineering productivity and outcomes, defining and tracking metrics such as cycle time, defect rates, test coverage, and automation levels Required Qualifications • 6+ years of strong software engineering experience with deep expertise in system design, APIs, distributed systems, and cloud-native architecture, • Hands-on experience with GenAI tools and platforms (e.g., GitHub Copilot, Cursor, OpenAI, Claude, Gemini, or similar), with a clear understanding of how to apply them effectively in software development workflows, • Demonstrated ability to design and guide AI-assisted development, not just use AI tools passively, • Proficiency in one or more languages such as Java, Python, JavaScript/TypeScript, or similar, with the ability to operate across the full stack when needed, • Strong experience with testing, CI/CD, DevOps practices, and production systems, • Ability to critically evaluate AI-generated outputs for correctness, security, and completeness Preferred Qualifications • Experience building or implementing agentic software development workflows or AI-driven automation systems, • Experience modernizing legacy applications using AI-assisted approaches, • Cloud experience (AWS, Azure, or GCP) and familiarity with enterprise-scale systems, • Exposure to governance, security, and compliance considerations in enterprise environments, • Prior experience mentoring engineers or leading technical initiatives What Success Looks Like In this role, success is not just measured by code delivered, but by how effectively you: • Drive adoption of AI augment software development in a structured, measurable, and sustainable way, • Establish scalable AI-driven software development practices & Processes, • Enable teams to significantly improve software delivery speed and quality, • Reduce manual effort through automation and intelligent workflows, • Ensure all AI-assisted software development outputs meet enterprise-grade coding standards