Software Engineer – AI-Augmented Software Development (Hayward)
CoreAi Consulting
Job Description
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