Forward Deployed Engineer – AI Solutions Architect

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Embrace Software Inc

Site WebLinkedInTous les Emplois

201 - 500 employés

Fondée en 2021

💸 Finance

📚 Éducation

Software • Finance • Education

Embrace Software Inc. est une société d'investissement spécialisée dans l'acquisition et le développement d'entreprises de logiciels de classe mondiale à travers divers secteurs industriels. En mettant l'accent sur les logiciels critiques pour les missions, Embrace vise à ajouter de la valeur à son portefeuille d'entreprises, qui va des petites et moyennes entreprises aux entreprises du Fortune 500. La société soutient ses entreprises acquises en fournissant des ressources et une expertise opérationnelle pour favoriser la croissance et améliorer la satisfaction client.

Description

• Design and ship production RAG systems for enterprise customers — chunking strategy, embeddings, hybrid retrieval, reranking, query rewriting, citation grounding, the works. • Own retrieval evaluation end-to-end — define golden sets, build eval pipelines (Ragas, TruLens, LangSmith, or custom), and drive measurable quality wins (think context precision 0.65 → 0.90, not "looks good to me"). • Architect agentic systems layered on top of RAG — multi-step retrieval, tool use, MCP integrations, guardrails, output validation. • Embed directly with customer engineering teams — pair on whiteboards, write code in their repos, debug their data, present to their CTO. • Technically lead a distributed team of FDEs across time zones — set the quality bar, review architecture, mentor engineers, own customer outcomes. • Close the loop with our product org — what breaks in the field shapes what we build next.

🎯 Exigences

• 7+ years engineering experience, with at least 2 years shipping production RAG (not POCs) at real scale. • Demonstrated depth on the parts of RAG that actually matter: Chunking strategies and the ablations you ran to choose one. • Vector DB trade-offs from real production use — Pinecone, Qdrant, Weaviate, pgvector, Vespa, OpenSearch (pick your 2–3 and have opinions). • Hybrid search, reranking (Cohere, cross-encoders, ColBERT), HyDE, query rewriting, context compression. • Retrieval and generation evaluation — you can quote real numbers from real systems you've owned. • The boring-but-critical stuff: access control, citation enforcement, freshness, multi-tenancy, cost-at-scale. • Strong Python; production experience on at least one cloud (AWS / Azure / GCP). • Hands-on with at least one agent framework — LangGraph, AutoGen, CrewAI, Semantic Kernel, or equivalent. • Customer-facing presence — you can walk into a Fortune 500 architecture review and earn trust in 30 minutes. • Track record of leading engineers, not just being one.

🏖️ Avantages

• Competitive salary commensurate with experience. • Opportunities for career advancement and professional development. • Experience collaborating with a diverse, global team within a remote work setting.