Technical Lead, AI Initiatives

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Juniper Square

Site WebLinkedInTous les Emplois

201 - 500 employés

💸 Finance

🏠 Immobilier

☁️ SaaS

💰 €75 000 000 Series C en 2019-11

Finance • Real Estate • SaaS

Juniper Square est une entreprise qui propose une plateforme complète et des solutions adaptées aux partenariats d'investissement privés. Fondée en 2014, l'entreprise se concentre sur la facilitation d'une connexion et d'une communication fluides entre les associés commandités (GPs) et les associés commanditaires (LPs) tout au long du cycle de vie de l'investissement. La technologie de Juniper Square est spécialement conçue pour soutenir les entreprises de l'immobilier commercial, du capital-investissement et des sociétés de capital-risque de toutes tailles. La plateforme offre des services tels que l'administration de fonds, la collecte de fonds, la gestion des investisseurs, la conformité et le reporting aux investisseurs, le tout visant à améliorer la transparence, la gouvernance des données et l'expérience globale des investisseurs.

Description

• Design and implement multi-agent systems, including agent orchestration, delegation, and tool interaction patterns. • Build scalable RAG (Retrieval-Augmented Generation) architectures using vector databases, embedding pipelines, and data chunking strategies. • Integrate and extend MCP (Model Context Protocol) tools for robust model-tool communication and workflow automation. • Lead development of AI-based features, prototypes, and production solutions using LLM APIs or self-hosted models. • Architect and optimize prompt engineering, prompt chains, agent loops, and refinement pipelines. • Implement and maintain agent evaluation frameworks (agent evals, scenario tests, regression testing). • Design automated evaluation harnesses for LLM quality, reliability, hallucination control, and performance metrics. • Drive iterative improvements through A/B testing, reward models, and feedback loops. • Monitor system performance, latency, cost, and reliability — and implement optimization strategies. • Lead and mentor engineers working on AI, data, and backend components. • Collaborate with product managers, researchers, and cross-functional teams to align tech strategy with business outcomes. • Conduct code reviews, enforce best practices, and maintain architectural standards. • Own technical roadmaps, sprint planning, and engineering execution. • Work with cloud platforms (AWS/GCP/Azure) to deploy scalable AI services. • Integrate vector databases (Pinecone, Weaviate, Elasticsearch, etc.). • Build APIs and microservices to expose AI capabilities to internal and external stakeholders. • Maintain secure, compliant, and efficient data pipelines for ingestion and retrieval.

🎯 Exigences

• Bachelor’s/Master’s degree in Computer Science, Engineering, AI, or related field. • 8+ years of software engineering experience with strong backend architecture skills. • 3+ years deep experience with LLMs, GPT models, agents, or advanced ML systems. • Strong hands-on experience with: • - MCP tools and LLM tool integration • - Agent frameworks (e.g., OpenAI Agents, LangChain, LlamaIndex, custom agents) • - RAG pipelines, embedding models, vector stores • - Agent evaluation, reliability testing, and model refinements • Proficiency in Python, TypeScript/Node.js, or similar languages. • Experience deploying LLM apps and APIs in production environments. • Deep understanding of AI limitations, hallucination control, and safety measures.

🏖️ Avantages

• Flexible working arrangements • Professional development opportunities • Competitive salary