Factored·4 days ago
4 days ago
Staff AI Engineer
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What you'll do
- Partner with client executives to translate ambiguous business problems into enterprise AI solution architectures with clear trade-off analyses (cost, latency, risk).
- Design and build scalable backend systems, data pipelines, and APIs integrating LLMs, agentic workflows,and RAGs.
- Implement multi-agent orchestration frameworks and advanced retrieval mechanisms (vector DBs, hybrid search) for complex workflows.
- Deploy and manage cloud-native AI applications across AWS, GCP, Azure, or Databricks using Docker, Kubernetes, Terraform, and CI/CD pipelines.
- Instrument systems with LLM telemetry, cost-tracking, security guardrails, and systematic evaluation harnesses (LLM-as-a-judge) to ensure safety and performance.
- Fine-tune prompts and optimize inference latency using caching, quantization, and cost-reduction strategies.
- Serve as the embedded technical authority within client environments to align cross-functional teams and manage technical risks.
- Elevate team standards (modular code, testing, CI/CD) and mentor client technical staff to build long-term operational autonomy
What they're looking for
- 8+ years of experience in Software/ML Engineering, with 3+ years specifically focused on production GenAI/LLM applications (RAG, agents, tool use) and 2+ years in customer-facing or forward-deployed roles.
- Deep hands-on experience building production systems with Generative AI frameworks (LangGraph, LangChain, LlamaIndex, OpenAI, vector databases).
- Proven ability to architect and scale complex backend microservices and APIs using Python (FastAPI, Django, Flask) alongside relational and NoSQL databases.
- Hands-on expertise building, deploying, and managing cloud-native applications on AWS, GCP, Azure, or Databricks using Docker, Kubernetes, Terraform, MLflow, and automated CI/CD pipelines.
- Experience implementing LLM telemetry, cost-tracking, security guardrails, and systematic evaluation harnesses (LLM-as-a-judge patterns).
- Exceptional ability to structure ambiguous client problems into clear technical requirements and present trade-off analyses (cost, latency, risk) to non-technical executive stakeholders.
- Fluent English communication (written and spoken) with a track record of driving engagements independently in fast-paced, high-stakes environments.
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
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 Staff AI Engineer at Factored, you will operate at the intersection of technical architecture, Generative AI, and enterprise strategy. Working directly with enterprise clients, you will act as a key technical contributor and trusted advisor.
This role is for technical leaders who combine system architecture mastery and hands-on ML/GenAI engineering with the executive presence needed to navigate ambiguous environments. You will define business problems, architect production-grade AI applications, align senior stakeholders, and own end-to-end delivery to drive measurable impact.
Functional Responsibilities:
- Partner with client executives to translate ambiguous business problems into enterprise AI solution architectures with clear trade-off analyses (cost, latency, risk).
- Design and build scalable backend systems, data pipelines, and APIs integrating LLMs, agentic workflows,and RAGs.
- Implement multi-agent orchestration frameworks and advanced retrieval mechanisms (vector DBs, hybrid search) for complex workflows.
- Deploy and manage cloud-native AI applications across AWS, GCP, Azure, or Databricks using Docker, Kubernetes, Terraform, and CI/CD pipelines.
- Instrument systems with LLM telemetry, cost-tracking, security guardrails, and systematic evaluation harnesses (LLM-as-a-judge) to ensure safety and performance.
- Fine-tune prompts and optimize inference latency using caching, quantization, and cost-reduction strategies.
- Serve as the embedded technical authority within client environments to align cross-functional teams and manage technical risks.
- Elevate team standards (modular code, testing, CI/CD) and mentor client technical staff to build long-term operational autonomy
Qualifications:
- 8+ years of experience in Software/ML Engineering, with 3+ years specifically focused on production GenAI/LLM applications (RAG, agents, tool use) and 2+ years in customer-facing or forward-deployed roles.
- Deep hands-on experience building production systems with Generative AI frameworks (LangGraph, LangChain, LlamaIndex, OpenAI, vector databases).
- Proven ability to architect and scale complex backend microservices and APIs using Python (FastAPI, Django, Flask) alongside relational and NoSQL databases.
- Hands-on expertise building, deploying, and managing cloud-native applications on AWS, GCP, Azure, or Databricks using Docker, Kubernetes, Terraform, MLflow, and automated CI/CD pipelines.
- Experience implementing LLM telemetry, cost-tracking, security guardrails, and systematic evaluation harnesses (LLM-as-a-judge patterns).
- Exceptional ability to structure ambiguous client problems into clear technical requirements and present trade-off analyses (cost, latency, risk) to non-technical executive stakeholders.
- Fluent English communication (written and spoken) with a track record of driving engagements independently in fast-paced, high-stakes environments.
Our Benefits:
- Ownership through equity participation.
- 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.
Company
Factored
Latin America, United States of America
Company facts come from this company's own listings. We only show what the postings themselves carry.