Fully remote | Complete engagement job
Founded in Palo Alto by Dr. Andrew Ng and Israel Niezen, Factored helps U.S. companies build and scale world-class AI, ML, and Data teams, powered by the top 1% of LATAM talent, with a defining purpose: To empower brilliant humans, unleash their potential, and amplify their impact in the world.
At Factored, you’ll be part of a community that values learning, ownership, and authenticity, where your growth is personal and your ideas matter. We’re transparent, curious, and collaborative. We strive for excellence, celebrate diversity, encourage curiosity, and build an environment where you can truly thrive.
As a Senior Software Engineer at Factored, you will engage full-time in designing and building the foundational systems that make enterprise-scale generative AI possible. Your work will transform cutting-edge AI strategies into secure, robust, production-grade applications used by global and Fortune 500 organizations. You will shape architectures, elevate performance, and deliver intelligent systems powered by agentic workflows and advanced ML capabilities. This role exists for engineers who want to own complex, high-impact problems and build at the frontier of AI.
Functional Responsibilities:
- Architect, design, and implement backend systems that integrate with LLMs, and ensure services are scalable, secure, and production-ready
- Implement agentic architectures for complex AI workflows.
- Build, deploy, and manage cloud-native AI applications on AWS (Lambda, ECS, SageMaker) and other modern infrastructure.
- Fine-tune prompts and build RAG pipelines to optimize performance.
- Implement AI security guardrails and conduct risk assessments to ensure compliance, privacy, and safety.
- Monitor application health with observability tools (APM, logging, LLM performance metrics) and proactively resolve performance issues.
- Work closely with ML Engineers to consume and integrate trained models into production systems.
- Maintain high engineering standards: modular code, automated testing, CI/CD pipelines, and documentation.
- Partner with product managers, designers, and cross-functional teams to deliver user-facing AI features that drive measurable value.
Qualifications:
- 5+ years of professional experience as a Software Engineer or in a related role, with a strong foundation in Python.
- Hands-on experience or strong interest in Generative AI frameworks such as LangGraph, LangChain, OpenAI, and RAG implementations.
- Experience with cloud platforms like AWS, including building, deploying, and managing cloud-native applications; exposure to Azure or GCP is also valuable.
- Experience designing and developing APIs using frameworks like FastAPI, Django, or Flask; willingness to learn best practices for scalable production systems is appreciated.
- Strong system design and problem-solving skills, including building, testing, and optimizing backend systems or AI workflows.
- Practical experience with databases (PostgreSQL or NoSQL), and vector databases for RAG workflows.
- Proficiency with DevOps and CI/CD tools such as Docker, Kubernetes, Terraform, and Git-based workflows.
- Understanding of deep learning model development and deployment, with familiarity using frameworks like PyTorch or HuggingFace; motivated learners are welcome.
- Excellent English communication skills, both written and spoken, with the ability to collaborate effectively with global teams and explain complex AI concepts clearly.
- A growth mindset and genuine interest in learning and applying new AI/ML techniques to real-world challenges.
Our Benefits:
- Ownership through equity participation.
- Competitive salary for top AI & data talent.
- Annual company retreat.
- Education bonus for continuous learning.
- Company-wide winter break.
- Paid time off.
- Optional in-person events and meetups.
- Tailored career roadmaps.
- High-performance culture.
Top Skills
What We Do
Factored (backed by Andrew Ng's AI Fund and deeplearning.ai) helps leading tech companies select, upskill, and build world-class data science, machine learning and AI engineering teams much faster and more cost effectively. Our engineers have been personally vetted, educated, and mentored by some of the most talented and recognized AI educators and engineers from Silicon Valley, Stanford University and deeplearning.ai.
