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Forward Deployed Engineer – AI
OPAQUE Systems. Serve as the technical bridge between enterprise customers and OPAQUE's confidential AI platform .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and deploying AI solutions, particularly in agentic workflows and RAG pipeline design, while effectively collaborating with enterprise customers and engineering teams. Proficient in Python and familiar with AI frameworks and LLM integrations, ensuring compliance with enterprise deployment constraints.
Highest-signal resume keywords
5+ Years Software Engineering ExperienceAgentic Workflow DevelopmentRAG Pipeline DesignStrong Python SkillsExperience with LLM APIs
ATS Keywords
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Hard Skills
Software EngineeringAgentic Workflow DevelopmentRAG Pipeline DesignPythonAI FrameworksLLM API IntegrationMulti-Agent OrchestrationMemory ArchitectureEmbedding ModelsVector Databases
Soft Skills
Technical CommunicationCustomer CollaborationProblem SolvingExecutive-Level Engagement
Tools & Technologies
LangChainLlamaIndexLangGraphCrewAIOpenAI APIAnthropic APIGemini API
Industry Keywords
AI/ML SystemsEnterprise Deployment ConstraintsIAMData ResidencyNetwork TopologyCompliance RequirementsSOC 2HIPAAFedRAMPConfidential Computing
Tech Stack
Tools & technologiesPython
About the role
Key responsibilities & impact- 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
What you’ll need- 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