• Design, build, and maintain evaluation pipelines for production AI agent systems • Instrument multi-agent workflows with tracing and observability tooling • Build evaluation datasets using real production traffic and interaction logs • Develop quality scoring and robustness scoring systems for LLM outputs • Improve reliability of AI systems handling non-deterministic model behavior • Implement and optimize HITL (Human-in-the-Loop) escalation workflows • Analyze production failures and drive architectural improvements • Own the full feedback loop between evaluations, prompt optimization, architecture updates, and re-testing • Contribute to prompt engineering and model optimization strategies • Collaborate on multi-agent orchestration and workflow reliability decisions • Work across backend systems, deployment pipelines, monitoring, and operational sustainment • Participate in production support and on-call responsibilities • Maintain high engineering standards around scalability, observability, and maintainability • Operate independently across development, testing, deployment, and production ownership

• Lead the design and implementation of innovative AI-driven applications and microservices • Drive strategic initiatives to enhance project outcomes and effectiveness • Collaborate with cross-functional teams to secure successful project execution • Innovate processes to maintain exceptional standards of operational excellence • Utilize technical knowledge to guide teams through complex challenges • Foster a culture of collaboration and continuous improvement • Provide mentorship and coaching to team members to enhance their skills • Stay updated on industry trends to inform strategic decisions

GC AI is the fastest-growing and most trusted legal AI platform for in-house legal teams. We're building the future of legal work, and we're doing it fast. You'll join at a pivotal moment—when decisions matter, impact is immediate, and the runway to shape your career is wide open. We’re a high-performing team where you'll have real ownership and influence from day one. More than 1,500 companies use GC AI to drive their business forward, including 150+ public companies, 25+ unicorns, and brands such as News Corp, Miro, Bass Pro Shops, Snyk, Skims, Liquid Death, Vercel, Zscaler, and TIME. We've 10x'd revenue in 12 months, raised a $60 million Series B ($555 million valuation), and are growing faster than ever. We are backed by incredible investors, including Scale Venture Partners, Northzone, Sound Ventures, and Guillermo Rauch, CEO of Vercel. If you thrive when the stakes are high and the path isn't paved, you'll love it here. Our six guiding principles are: 1% better every day, customer obsession, ship today, find a way, care deeply, and own it completely. Come shape the future of legal work with us. Location We are hiring for this role to be based in the United States or Canada. This is a remote role unless you fall within the following parameters. If you live within approximately 50 miles of our San Mateo, CA or Provo, UT office, the position follows a hybrid schedule with in-office days on Mondays, Wednesdays, and Fridays. About The Role We're seeking an exceptional AI Engineer to help lead the development of our cutting-edge AI platform. This is a unique opportunity to shape how artificial intelligence transforms legal work. You'll be the technical cornerstone of our AI initiatives, working directly with our CTO (ex-Replit) and founding data engineer (ex-Lyft, Instagram and Plaid) to architect systems that push the boundaries of what's possible with LLMs in the legal domain. Why This Role Matters We're at a pivotal moment in legal technology, where AI can fundamentally transform how legal work gets done. As our AI Engineer, you'll be the architect of systems that make this transformation possible. Your work will define not just how our platform evolves, but how an entire industry adapts to and leverages AI. This is a chance to solve novel technical challenges while having a real impact on how legal professionals work. What You'll Do - Architect and drive our core AI/LLM infrastructure and features from conception to production. - Design and implement AI systems that handle complex legal reasoning and document analysis. - Lead the evaluation and integration of LLM capabilities and AI tools. - Establish best practices for AI development, and reliability. - Build frameworks for rapid prototyping and validation of AI features. - Guide and mentor our growing team of AI engineers. - Shape our technical strategy and roadmap alongside senior leadership. Impact You'll Have - Design and run rigorous legal-grade evals that harden model choices, prompts, and retrieval for accuracy and explainability. - Improve real-world outcomes (precision, recall, latency) by advancing RAG, structured reasoning, and tool-use pipelines. - Translate domain insights into AI-powered product features that users immediately feel - better answers, fewer edits. - Help build the leading legal AI platform for in-house teams. Required Experience - 5+ years of software engineering experience, with 2+ years focused on AI systems. - Deep expertise in LLM implementation and optimization. - Strong track record of building production AI systems at scale. - Experience with modern AI frameworks and tools. - Proven ability to lead technical initiatives and mentor engineers. - Strong foundation in TypeScript and modern software architecture. Nice to Have - Experience with RAG systems and LLM evaluation. - Familiarity with legal domain or legal text processing. - Track record of technical publications or open-source contributions. - Experience with multi-agent AI systems. The Mindset - Problem Solver: You come alive tackling complex challenges without obvious solutions. - Ownership-Driven: You take initiative without needing direction and focus on outcomes. - Continuous Learner: Your curiosity drives you to constantly level up your engineering skills. - Startup DNA: You thrive in fast-paced environments where responsibilities evolve. What We Offer Growth & Impact - Shape the future of a rapidly growing startup - Direct collaboration with founding team - Real influence on company strategy and direction - A voice that matters - your ideas will be heard and implemented Environment & Benefits - Competitive salary, equity and healthcare - We’re a hybrid company — many roles are remote-friendly, while some teams require meeting in person a couple of days a week in the Bay Area office. - High-energy, joyful team environment Career Development - Mentorship and learning opportunities - Clear path for growth in an expanding company - Exposure to cutting-edge technologies and practices - Freedom to innovate and own crucial systems A Note On Pace We’re building something new in a once-in-a-generation shift in technology and the legal industry, so we move at a relentless pace. We expect urgency, ownership, and good judgment even when things aren’t perfectly clear. If you need structure and consensus to do your best work, this isn’t the right place for you. If you thrive in ambiguity and growth, work with intensity, and want real responsibility, keep reading. We’re excited to meet you. Compensation GC AI's compensation package includes a competitive base salary benchmarked against real-time market data, as well as meaningful equity and excellent benefits for all full-time roles. Our US-based compensation range for this role is $165,000 – $350,000. This range spans four levels, from mid-level to Principal. Final compensation will vary based on leveling, market conditions, geographic location, and candidate qualifications, including relevant knowledge, skills, and experience assessed during the interview process. These compensation bands are just the starting point. After someone joins and proves they’re an exceptional performer, we adjust quickly to ensure their compensation aligns with their impact. Equal Opportunity Employment GC AI is an equal opportunity employer that supports workplace diversity and does not discriminate on the basis of race, color, religion, gender identity/expression, national origin, age, military service eligibility, veteran status, sexual orientation, marital status, physical or mental disability, or any other protected class. GC AI is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. #LI-GCAI Fraud Notice to GC AI Applicants To protect yourself against phishing and recruitment fraud, please note that GC AI only accepts job applications through our official careers page at https://gc.ai/careers and through sponsored jobs on LinkedIn. All legitimate communication from our team regarding job opportunities will come from a GC AI team member with a @gc.ai or @getgc.ai email address. GC AI will never: - Refer you to external websites to apply - Conduct interviews over email, chat platforms, or messaging apps - Ask you to provide payment or purchase equipment - Request personal or financial information such as your mailing address, social security number, credit card numbers, or banking information during the application process Examples of fraudulent email addresses: - info.gcai.careers.com@gmail.com - info.gc.aicareers.online.com@gmail.com - Any email address ending in @gmail.com, @yahoo.com, or other free email services If you are contacted by someone claiming to be from GC AI via an unofficial channel or from a suspicious email address, please do not share any information. Mark the communication as "phishing" or "spam" and do not respond.

• Design and implement edge AI solutions optimized for diverse hardware including mobile SoCs, NPUs, and embedded accelerators. • Apply quantization, pruning, distillation, and architectural optimization to fit models within edge constraints. • Tune model performance for latency, energy efficiency, and memory footprint on target hardware. • Build cross-platform inference runtimes leveraging frameworks such as TensorFlow Lite, ONNX Runtime, and Core ML. • Optimize models for specific accelerator backends including DSPs, NPUs, and mobile GPUs. • Implement on-device model update, versioning, and rollback workflows that allow safe staged rollouts to large device populations and rapid recovery if a model release behaves unexpectedly in the field. • Design hybrid edge-cloud architectures that gracefully degrade based on connectivity and device capability. • Build telemetry pipelines that respect privacy while enabling continuous improvement. • Collaborate with hardware, firmware, and product teams to align AI capabilities with device constraints. • Implement secure execution paths, model protection, and integrity verification on edge devices. • Develop benchmarking suites that characterize accuracy, latency, and energy trade-offs across devices. • Drive responsible AI considerations including on-device privacy and bias evaluation. • Maintain comprehensive, current technical documentation — including architecture diagrams, design decisions, configuration references, runbooks, and operational procedures — so that the system remains supportable, auditable, and easy to onboard new engineers onto over time. • Stay current with edge AI hardware and software developments, regularly review release notes and community discussions, and translate noteworthy advances into concrete recommendations and adoption proposals for the team.