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About the Role
As a Lead Software Engineer at Faculty, you will drive the technical strategy, architecture, and deployment of secure AI systems in high-stakes domains. You will bridge AI research and production impact, setting the benchmark for engineering excellence and operationalizing scalable ML infrastructure. You will champion safety-first AI frameworks, evaluate model capabilities, and manage multi-agent systems. You will advise client leadership, mentor engineers, and steer teams to solve critical AI challenges.
Responsibilities
- Steer technical strategy, system architecture, and capability testing for complex ML systems and Frontier AI models.
- Architect production-grade, secure ML software, orchestration tools, and scalable cloud infrastructure.
- Establish company-wide standards and best practices for safe, reliable, and ethical machine learning deployment at scale.
- Collaborate with cross-functional teams and executive stakeholders to translate client needs into AI solutions.
- Advise senior clients and partners as an AI safety and technical authority.
- Mentor and develop engineering talent, elevating team capabilities and nurturing an inclusive culture.
- Partner with Frontier Labs to advance safety evaluation procedures, multi-agent tooling, and AI governance frameworks.
Requirements
- Significant leadership experience designing, deploying, and securing scalable LLM applications, multi-agent frameworks, and AI safety evaluation processes.
- Exceptional software engineering fundamentals and advanced Python expertise, focused on building resilient, enterprise-ready systems.
- Deep hands-on experience with cloud platforms (AWS, Azure, GCP), scalable cloud architectures, container orchestration (Docker, Kubernetes), agent sandboxing, and end-to-end cybersecurity.
- Mastery over the full ML lifecycle, with proven expertise operationalizing production systems using PyTorch, TensorFlow, or similar frameworks.
- Excels in fast-paced, high-growth environments, demonstrating autonomy, strategic ownership, and a track record of guiding technical decisions.
- Communicates persuasively with technical teams and senior non-technical stakeholders, translating complex technical risks into clear strategic direction.
Skills
- AI
- Machine Learning
- LLM
- Multi-agent systems
- AI safety
- Python
- Cloud platforms (AWS, Azure, GCP)
- Scalable cloud architectures
- Docker
- Kubernetes
- Cybersecurity
- PyTorch
- TensorFlow
Work Type
- Full-time
Experience Level
- Lead
- Senior
About the Company
- Faculty was established in 2014 with the belief that AI would be the most important technology of our time.
- Faculty has worked with over 350 global customers to transform performance through human-centric AI.
- Faculty innovates, builds, and deploys responsible AI that makes a significant impact.
- Faculty possesses unparalleled technical, product, and delivery expertise.
- Faculty serves clients across government, finance, retail, energy, life sciences, and defense.
- Faculty's business and reputation are growing rapidly.
- Faculty seeks individuals with intellectual curiosity and a desire to build a positive legacy through technology.
- Faculty empowers employees to envision and implement powerful AI applications.
Equal Opportunity
- Faculty aims to grow a diverse team, recognizing that diversity of individuals fosters diversity of thought and strengthens the principle of seeking truth.
- Diverse teams deliver better work, relevant to the world.
- Faculty is united by deep intellectual curiosity and a desire to use abilities for measurable positive impact.
- Applications are strongly encouraged from people of all backgrounds, ethnicities, genders, religions, and sexual orientations.
- Candidates who do not meet all requirements but are excited by the role and possess key strengths are encouraged to apply.
- Conversations about part-time hours are welcome.
- Faculty is open to the use of AI for research and interview preparation, but not for generating answers during live interviews.
- Faculty uses an AI note-taker (Metaview) in interviews, with an option to opt out.
- Every application is reviewed by a human, never decided by AI.