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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Backend Engineer (Forward Deployed) - **Company:** FADE TIME - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Salary:** $250,000.0 - $300,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Data Governance, Extract Transform Load (ETL), Python (Programming Language), Machine Learning, OpenAI, Software Engineering, Workflow Management Systems, Pinecone, Google Cloud, Cloud Platform System, LangChain, Retrieval-Augmented Generation, Large Language Models, Backend, Agentic-AI, Fastapi, Kubernetes, Information Technology, HuggingFace, Apache Kafka, Data Management, Machine Learning Operations, Api Design, GPT, Software Version Control, Docker - **Published:** November 7, 2026 - **Apply:** https://www.juju.com/job/28_25304_dc99d9eed9e1db9a910f5dfc7a595391 ## About the Role * 10+ years of software engineering experience, including significant time spent building data, ML, or backend systems * Python & ML/LLM Frameworks: Deep proficiency in Python with hands-on experience using Hugging Face, LangChain, OpenAI, Pinecone, and related ecosystems, including LLMs and AI Agents * Deployment & Infrastructure: Skilled in full-stack and API-based deployment patterns, including Docker, FastAPI, Kubernetes, and cloud environments (GCP, AWS, Azure) * Platform Orchestration: Experienced with workflow orchestration libraries, pub/sub systems (Kafka), and schema governance * Data Management: Expertise in data governance and operations, including Unity Catalog and policy management, cluster/job orchestration, data contracts and quality enforcement, Delta/ETL pipelines, and replay processes * ML Operations (for teams with an applied AI/ML focus): Experience with MLOps frameworks and best practices - model versioning, monitoring, and lifecycle management - and designing scalable ML systems such as RAG pipelines * Strong product and system design instincts - you understand business needs and how to translate them into technical architecture * Experience building usable systems from messy data and ambiguous requirements * Excellent communication and client-facing skills; you've led conversations with technical and non-technical stakeholders alike * Proven experience owning projects from scoping through deployment in ambiguous, high-stakes environments * Strong engineering background demonstrated by a Bachelor's degree in Data Science, Computer Science and related fields OR equivalent professional experience * Be willing to be on-call for our customers when situations arise * Travel: Willingness to travel for on-site client engagements as needed * Onsite: Available to work from the office a few days per week, depending on team needs - some NYC-based teams require 3 days per week onsite; your specific requirement will depend on the team you're placed with, We expect bold ideas, relentless drive, and the ability to turn ambiguity into opportunity. The pace is fast, the challenges are big, and the growth is unmatched. We're not for everyone, and we're okay with that. If you're looking for predictable routines, this isn't the place for you. But if you're driven to create, thrive in dynamic environments, and want a front-row seat to the AI revolution, you'll fit right in. ## Description As a Principal Forward Deployed Engineer (FDE) at Invisible, you'll lead high-impact, AI-powered solutions that reshape how our clients operate their most critical workflows. You won't just build and deploy - you'll drive the strategy, architecture, and execution of end-to-end systems, working directly with clients. This is a hybrid role: equal parts AI engineer, software builder, and technical consultant. It's perfect for someone who wants to be hands-on with models and close to the impact they generate. The team is increasingly focused on applied AI work - building and deploying LLM-powered and agentic systems in production - so strong ML engineering instincts can be a valuable addition alongside your architecture and leadership experience., * Partner with delivery and executive stakeholders to scope, design, and lead implementation of AI-driven solutions, including LLM and agentic systems * Identify transformational opportunities in messy, ambiguous workflows and turn them into repeatable systems * Lead architecture design and trade-off discussions across performance, scalability, cost, and reliability - including for ML/AI-specific systems like RAG pipelines and production-grade AI applications * Own projects from first discovery call through full deployment - including client-facing delivery, internal coordination, and post-launch iteration * Build shared infrastructure, reusable components, and internal playbooks to level-up the team, including MLOps practices for model versioning, monitoring, and lifecycle management * Coach and mentor mid-level engineers and help shape the culture of forward-deployed AI engineering at Invisible, Invisible is committed to fair and competitive pay, ensuring that compensation reflects both market conditions and the value each team member brings. Our salary structure accounts for regional differences in cost of living while maintaining internal equity., * Bonuses and equity are included in all full-time offers. Final compensation is determined by a combination of factors, including location, job-related experience, skills, knowledge, internal pay equity, and overall market conditions. Because of this, every offer is unique. Additional details on total compensation and benefits will be discussed during the hiring process.