Technical Architect - AI Engineering

Job highlights

• Leadership: Technical System Design,Code Reviews,Agile Development,Team Mentoring. Domain Advantage (Preferred): Healthcare tech experience (EMR,HMIS,healthcare data privacy standards).
• exposure to Healthcare / EMR/HMIS platforms is strongly preferred. . Disclaimer: This job posting has been aggregated from external source

Capital Numbers is seeking a hands-on Technical Architect - AI Engineering to design, build, and deploy production-grade AI systems while leading a high performing engineering team. In this role, you will bridge cutting-edge generative AI development with enterprise-grade system architecture, driving projects from concept to deployment.

Roles Responsibilities

• AI System Architecture: Design: Architect, build, and optimize scalable RAG (Retrieval-Augmented Generation) pipelines, LLM-driven applications, and multi-agent AI systems.
• Enterprise Integration: Integrate LLMs, custom embeddings, vector databases, and APIs with complex enterprise data layers and existing business applications.
• System Optimization: Reliability: Solve critical AI deployment challenges, including retrieval quality improvement, hallucination mitigation, latency reduction, and query cost management.
• Technical Leadership: Mentorship: Drive code reviews, establish coding standards, unblock developers, and mentor a small team of software and AI engineers.
• Security Infrastructure: Implement AI security best practices, ensure enterprise data privacy, and oversee deployment across cloud environments (AWS / Azure / GCP).

Skills

• Core Languages: Frameworks: Python, LangChain, LlamaIndex, OpenAI APIs, Hugging Face
• AI Architecture: Generative AI, RAG Pipelines, AI Agents, Vector Databases (Pinecone, ChromaDB, Weaviate, Qdrant), Prompt Engineering, Embeddings
• Cloud: DevOps: AWS / Azure / GCP, Docker, API Integration, Microservices, CI/CD
• Leadership: Technical System Design, Code Reviews, Agile Development, Team Mentoring
• Domain Advantage (Preferred): Healthcare tech experience (EMR, HMIS, healthcare data privacy standards)

Qualifications Experience

Educational Background: Bachelor's or Master's degree in Computer Science, Information Technology, Software Engineering, or a related technical field.

Production Track Record: Proven background in moving LLM/GenAI prototypes into production enterprise environments.

Domain Expertise: Experience working on complex data architectures; exposure to Healthcare/EMR/HMIS platforms is strongly preferred.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.