Senior Software Engineer (GenAI/ML)

Posted 73 days ago

Job Description

This job posting has expired and no longer accepting applications.

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.

At Factored, we believe that passionate, smart people expect honesty and transparency, as well as the freedom to do the best work of their lives while learning and growing as much as possible. Great people enjoy working with other passionate, smart people, so we believe in hiring right, and are very selective about who joins our team. Once we hire you, we will invest in you and support your career and professional growth in many meaningful ways. We hire people who are supremely intelligent and talented, but we recognize that intelligence is not enough. Perhaps more importantly, we look for those who are also passionate about our mission and are honest, diligent, collaborative, kind to others, and fun to be around. Life is too short to work with people who don’t inspire you.

We are a transparent workplace, where EVERYBODY has a voice in building OUR company, and where learning and growth are available to everyone based on their merits, not just on stamps on their resume. As impressive as some of the stamps on our resumes are, we recognize that human talent and passion exist everywhere, and come from many backgrounds, so stamps matter much less than results. All of us are dedicated doers and are highly energetic, focusing vehemently on execution because we know that the best learning happens by doing. We recognize that we are creating OUR COMPANY TOGETHER, which is not only a high-performing fast-growing business but is changing the way the world perceives the quality of technical talent in Latin America. We are fueled by the great positive impact we are making in the places where we do business and are committed to accelerating careers and investing in hundreds (and hopefully thousands) of highly talented data science engineers and data analysts.

In short, our business is about people, so we hire the best people and invest as much as possible in making them fall in love with their work, their learning, and their mission. When not nerding out on data science, we love to make music together, play sports, play games, dance salsa, cook delicious food, brew the best coffee, throw the best parties, and generally have a great time with each other.

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