Forward Deployed Engineer (AI)

ABOUT THIS ROLE

As a Forward Deployed Engineer (AI) at OPAQUE Systems, you are the technical bridge between our enterprise customers and OPAQUE's confidential AI platform. You will work directly with customer engineering teams — from initial architecture review through production deployment — helping them install and deploy OPAQUE in their environment, and build AI solutions (agents / agentic workflows, RAG pipelines, LLM integrations) that run on OPAQUE's confidential AI platform.

This is a hands-on technical role. You will write code, run POCs, architect solutions, and own the customer's path from "interested" to "getting value." You will also be a critical signal source for the product team — the patterns you see in the field shape what OPAQUE builds next.

KEY RESPONSIBILITIES

• Develop custom AI / agentic solutions tailored to customer needs
• Lead technical discovery and architecture scoping with enterprise customers — translate vague AI / agentic aspirations into concrete implementation plans.
• Design and build production-grade solutions for agentic workflows, RAG pipelines, and LLM integrations on OPAQUE's platform.
• Partner with customer engineering teams through production deployment — unblock integration issues, debug failures, and ensure the solution is maintainable.
• Run technical whiteboard sessions, architecture reviews, and POC demonstrations with CTO, CISO, and engineering leader audiences.
• Synthesize field observations into product feedback — use case patterns, integration friction, objections, and feature gaps.
• Build reusable artifacts: integration guides, POC templates, architectural reference designs, and objection playbooks.
• Stay ahead of the AI landscape — agentic frameworks, RAG techniques, LLM capabilities, enterprise AI tooling.

QUALIFICATIONS

• 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 — comfortable with executive-level technical conversations.
• Strong understanding of enterprise deployment constraints: IAM, data residency, network topology, compliance requirements (SOC 2, HIPAA, FedRAMP).
• Security-aware engineering mindset — understands trust boundaries, data flow, and why cryptographic attestation matters for regulated industries.
• Bonus: Experience with confidential computing, TEEs, or privacy-preserving AI.