Forward Deployed Engineer (Mid-Level)
Company Overview
TECQMIND is an end-to-end AI professional services and staffing partner. We don’t just talk about AI; we build the teams and infrastructure required to turn AI theory into production-scale reality. From fractional C-suite leadership to specialized engineering squads, we provide the technical "how" for businesses ready to scale.
The Role
As a Forward Deployed Engineer at TECQMIND, you are the technical face of our custom implementation services. You will work at the intersection of software engineering, data science, and client success. Your mission is to embed with our clients, understand their technical bottlenecks, and deploy production-ready AI solutions.
Notably, you will serve as a primary technical bridge between our domestic clients and our world-class engineering partners based in Taiwan.
Key Responsibilities
Integration & Implementation: Own the end-to-end deployment of custom AI models (e.g., RAG pipelines, LLM agents) within client environments.
Global Technical Liaison: Act as the technical point of contact between North American clients and our Taiwanese technology partners, ensuring requirements are clearly communicated and executed across time zones.
Infrastructure Building: Assist in designing and maintaining robust Data Lakes and "Model Gardens" tailored to client IP.
Full-Stack Optimization: Ensure that AI tools communicate effectively with existing APIs and legacy software, focusing on low latency and high reliability.
Continuous Refinement: Monitor deployed models for performance degradation or data drift to ensure ongoing "Continuous Optimization."
Technical Consulting: Translate complex business requirements into high-performing technical specifications for our overseas development teams.
Required Qualifications
Experience: 3–5 years of professional experience in Software Engineering, Data Engineering, or Machine Learning Engineering.
Core Technical Stack: Proficiency in Python is a must. Deep experience with modern AI frameworks (e.g., LangChain, LlamaIndex, PyTorch, or TensorFlow).
Cloud & Infrastructure: Hands-on experience with at least one major cloud provider (AWS, GCP, or Azure) and containerization tools like Docker and Kubernetes.
Data Proficiency: Experience working with Vector Databases (e.g., Pinecone, Weaviate, Milvus) and designing data pipelines.
Problem Solving: A "builder" mindset—you enjoy the challenge of working with messy, real-world data and legacy codebases.
Highly Desired: Preferred Qualifications
Bilingual Proficiency: Professional fluency in both English and Mandarin (written and verbal) is highly desired to facilitate seamless collaboration with our Taiwan-based partners.
Cross-Cultural Collaboration: Proven experience working with overseas tech partners and the ability to manage technical workflows across different time zones.
Client-Facing Experience: Experience in a consultative engineering role or technical account management.
MLOps Knowledge: Familiarity with CI/CD for ML and data security standards (SOC2, HIPAA, etc.).