Software Engineering Lead - AI-Augmented / Agentic SystemsCoreAi Consulting • United States
Software Engineering Lead - AI-Augmented / Agentic Systems
CoreAi Consulting
- United States
- United States
À propos
Software Engineering Lead – AI-Augmented / Agentic Systems
who can drive the next generation of software engineering by combining strong technical depth with expertise in GenAI, agentic workflows, and AI-augmented development. This is not a traditional engineering role. We are looking for someone who can design and implement AI-driven engineering systems, 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 Fransisco, CA, Dallas, TX and Austin, TX Key Responsibilities Lead the design and development of scalable, secure software systems while actively contributing hands-on to architecture, coding, and critical problem-solving Define and implement
AI-augmented engineering workflows , including the use of GenAI tools, coding assistants, and agentic systems across development, testing, debugging, and documentation Design and operationalize
agent-based development processes , where multi-step engineering tasks (feature development, bug fixing, modernization) are executed through structured AI workflows 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 Guide teams in effectively leveraging 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 8+ years of strong software engineering experience with deep expertise in system design, APIs, distributed systems, and cloud-native architecture 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 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 engineering workflows Demonstrated ability to
design and guide AI-assisted development , not just use AI tools passively 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 engineering 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: Establish scalable
AI-driven engineering practices Enable teams to significantly improve
delivery speed and quality Reduce manual effort through
automation and intelligent workflows Ensure all AI-assisted outputs meet
enterprise-grade standards Drive adoption of AI in a structured, measurable, and sustainable way Closing Note This role is for engineers who want to go beyond coding and redefine how software engineering is done using AI.
Compétences linguistiques
- English
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