Senior AI Engineer at Factored

Job description

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 AI Engineer at Factored, you will engage full-time in designing and building production-grade GenAI systems that transform enterprise AI strategies into secure, scalable applications. You are a hands-on engineer working directly with client teams, shipping production code while contributing to technical strategy and learning from experienced leaders. You own complex, high-impact projects from architecture through optimization and deployment. This role exists for engineers who want to build at the frontier of AI while growing their technical expertise. Functional Responsibilities: Architect, design, and implement backend Python systems that integrate with LLMs via the Model Context Protocol (MCP) , ensuring services are scalable, secure, and production-ready. Implement complex, stateful agentic architectures and reasoning loops for multi-step AI workflows using frameworks like LangGraph. Build, deploy, and manage cloud-native AI applications on AWS (Bedrock, Lambda, ECS) and other modern infrastructure. Champion Spec-Driven Development (SDD) and Context-Driven Development (CDD) to ensure models produce deterministic, highly structured outputs. Architect semantic memory layers and build advanced RAG pipelines utilizing vector databases to optimize performance. Implement AI security guardrails , strict boundary controls, and Human-in-the-Loop (HITL) approval flows to ensure compliance, privacy, and safety. Monitor application health with observability tools (APM, LangSmith, Phoenix) to track agent trajectories, LLM performance metrics, and proactively resolve performance issues. Act as an internal AI accelerator by onboarding teams, building reusable prompts, and automating repetitive workflows to drive the adoption of AI-native developer tools (Claude Code, Cursor) org-wide. Collaborate with ML Engineers, product managers, and cross-functional teams to understand requirements and deliver AI features that drive measurable value. Communicate technical architecture and trade-offs clearly to stakeholders at all levels. Contribute to raising engineering standards through code review and knowledge sharing, treating prompts and context strictly as code. Qualifications: 5+ years of professional experience as a Software Engineer or in a related role, with a strong foundation in Python. Hands-on experience with modern Generative AI orchestration frameworks (LangGraph, LangChain, AutoGen) and agentic state management. Practical experience with the Model Context Protocol (MCP), function calling, tool-use APIs, and enforcing structured outputs across major foundation models. Experience with cloud platforms like AWS (including Bedrock), building, deploying, and managing cloud-native applications; exposure to Azure or GCP is also valuable. Experience designing and developing APIs using frameworks like FastAPI or Django to wrap agentic workflows into consumable backend services. Strong system design and problem-solving skills , capable of visualizing and debugging complex, non-linear agent trajectories and AI workflows. Practical experience with databases (PostgreSQL or NoSQL) and vector databases (Pinecone, Qdrant, Milvus) for semantic memory and RAG workflows. Proficiency with DevOps and CI/CD tools such as Docker, Kubernetes, Terraform, and Git-based workflows. Excellent English communication skills , both written and spoken, with the ability to collaborate effectively with global teams and explain complex AI concepts clearly. Comfortable translating between technical and business perspectives and managing ambiguous requirements. A growth mindset and genuine interest in learning and applying new AI methodologies (like SDD and CDD) to real-world challenges 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.

Requirements

Must-haves

Fully remote | Complete engagement job
Architect, design, and implement backend Python systems that integrate with LLMs via the Model Context Protocol (MCP) , ensuring services are scalable, secure, and production-ready.
Implement complex, stateful agentic architectures and reasoning loops for multi-step AI workflows using frameworks like LangGraph.
Build, deploy, and manage cloud-native AI applications on AWS (Bedrock, Lambda, ECS) and other modern infrastructure.
Champion Spec-Driven Development (SDD) and Context-Driven Development (CDD) to ensure models produce deterministic, highly structured outputs.
Architect semantic memory layers and build advanced RAG pipelines utilizing vector databases to optimize performance.
Implement AI security guardrails , strict boundary controls, and Human-in-the-Loop (HITL) approval flows to ensure compliance, privacy, and safety.
Monitor application health with observability tools (APM, LangSmith, Phoenix) to track agent trajectories, LLM performance metrics, and proactively resolve performance issues.
Act as an internal AI accelerator by onboarding teams, building reusable prompts, and automating repetitive workflows to drive the adoption of AI-native developer tools (Claude Code, Cursor) org-wide.
Collaborate with ML Engineers, product managers, and cross-functional teams to understand requirements and deliver AI features that drive measurable value.
Communicate technical architecture and trade-offs clearly to stakeholders at all levels.
Contribute to raising engineering standards through code review and knowledge sharing, treating prompts and context strictly as code.
5+ years of professional experience as a Software Engineer or in a related role, with a strong foundation in Python.
Hands-on experience with modern Generative AI orchestration frameworks (LangGraph, LangChain, AutoGen) and agentic state management.
Practical experience with the Model Context Protocol (MCP), function calling, tool-use APIs, and enforcing structured outputs across major foundation models.
Experience with cloud platforms like AWS (including Bedrock), building, deploying, and managing cloud-native applications; exposure to Azure or GCP is also valuable.
Experience designing and developing APIs using frameworks like FastAPI or Django to wrap agentic workflows into consumable backend services.
Strong system design and problem-solving skills , capable of visualizing and debugging complex, non-linear agent trajectories and AI workflows.
Practical experience with databases (PostgreSQL or NoSQL) and vector databases (Pinecone, Qdrant, Milvus) for semantic memory and RAG workflows.
Proficiency with DevOps and CI/CD tools such as Docker, Kubernetes, Terraform, and Git-based workflows.
Excellent English communication skills , both written and spoken, with the ability to collaborate effectively with global teams and explain complex AI concepts clearly.
Comfortable translating between technical and business perspectives and managing ambiguous requirements.
A growth mindset and genuine interest in learning and applying new AI methodologies (like SDD and CDD) to real-world challenges

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

aimlpythonawsllmazuregcpci/cddockerkubernetes

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Paid Time Off