OPAQUE Systems
11 - 50 employees
Founded 2021
AI is driving a massive platform shift, but like every major shift (PC, mobile, cloud), it demands a trust layer upgrade. AI is no different, except this time these systems are autonomous, non-deterministic, and operating at machine speed. Today, Enterprise AI leaders face a critical conflict. CEOs mandate AI adoption everywhere for competitive advantage and productivity gains, but CISOs, security and compliance teams rightfully block production deployments of AI agents using sensitive data due to risks of leaking data and violating compliance policies.
Forward Deployed Engineer – AI
Job not on LinkedIn
🔥 1 hour ago
Where this job comes from
Posted on OPAQUE Systems's careers page, not through a job board
First seen by Remote Rocketship 1 hour ago
Still open on OPAQUE Systems's site. Checked 44 minutes ago.
OPAQUE Systems
11 - 50 employees
Founded 2021
AI is driving a massive platform shift, but like every major shift (PC, mobile, cloud), it demands a trust layer upgrade. AI is no different, except this time these systems are autonomous, non-deterministic, and operating at machine speed. Today, Enterprise AI leaders face a critical conflict. CEOs mandate AI adoption everywhere for competitive advantage and productivity gains, but CISOs, security and compliance teams rightfully block production deployments of AI agents using sensitive data due to risks of leaking data and violating compliance policies.
📋 Description
• Serve as the technical bridge between enterprise customers and OPAQUE's confidential AI platform • Work with customer engineering teams from initial architecture review through production deployment • Install and deploy OPAQUE in customer environments • Develop custom AI and agentic solutions tailored to customer needs • Lead technical discovery and architecture scoping with enterprise customers • Design and build production-grade agentic workflows, RAG pipelines, and LLM integrations • Partner with customer engineering teams through production deployment, resolving integration issues and debugging failures • Run technical whiteboard sessions, architecture reviews, and POC demonstrations for CTO, CISO, and engineering leader audiences • Synthesize field observations into product feedback • Build reusable integration guides, POC templates, architectural reference designs, and objection playbooks • Stay current with agentic frameworks, RAG techniques, LLM capabilities, and enterprise AI tooling
🎯 Requirements
• 5+ years of software engineering experience working on production AI/ML systems • Hands-on experience building agentic workflows: tool use, multi-agent orchestration, memory architecture, agent reliability patterns • Deep hands-on experience with RAG pipeline design: chunking strategies, embedding models, vector databases, retrieval quality evaluation, re-ranking • Strong Python skills • Experience with AI frameworks (LangChain, LlamaIndex, LangGraph, CrewAI, or similar) • Experience integrating with LLM APIs (OpenAI, Anthropic, Gemini) in enterprise production environments • Ability to work directly with enterprise customer teams and comfort with executive-level technical conversations • Strong understanding of enterprise deployment constraints: IAM, data residency, network topology, and compliance requirements (SOC 2, HIPAA, FedRAMP) • Security-aware engineering mindset; understanding of trust boundaries, data flow, and cryptographic attestation • Experience with confidential computing, TEEs, or privacy-preserving AI is a bonus
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