Tech Lead & Solutions Architect (AI & Application Management)
Posted Today by Datamatics Global Services, Inc.
Negotiable
Undetermined
Remote
Remote
Summary: The Tech Lead and Solutions Architect will bridge complex business requirements with advanced AI implementations, focusing on the design, development, and management of enterprise applications. This role emphasizes seamless integration with Google Gemini to enhance user experiences. The position requires leadership in both technical architecture and application development, ensuring robust and scalable solutions. The candidate will also mentor the engineering team and align technical strategies with business objectives.
Key Responsibilities:
- Architectural Blueprinting: Design end-to-end scalable architectures for multi-tier applications, prioritizing modularity and high availability.
- AI Integration: Lead the architectural strategy for deploying applications into the Google Gemini/Vertex AI ecosystem, focusing on Model Garden, Tuning, and Grounding.
- Data Strategy: Design data pipelines and vector databases (e.g., Pinecone, BigQuery Vector Search) to provide real-time context to LLMs.
- Full-Stack Leadership: Oversee the development of applications using modern frameworks (LWC, React, Node.js, or Python) ensuring clean code and robust security.
- Lifecycle Management: Manage the entire Application Development Life Cycle (SDLC), from initial discovery and prototyping to production support and refactoring.
- DevOps & Deployment: Architect CI/CD pipelines using tools like GitHub Actions, Jenkins, or Google Cloud Build to ensure rapid, low-risk deployments.
- Mentorship: Act as the "North Star" for the engineering team, performing code reviews and enforcing technical standards.
- Vendor & Stakeholder Management: Collaborate with Product Owners and senior leadership to align the technical roadmap with business OKRs.
- Innovation: Stay at the forefront of Generative AI, identifying opportunities to replace legacy manual workflows with autonomous AI agents.
Key Skills:
- 10+ years of IT experience, with at least 4 years in a Solutions Architect or Tech Lead capacity.
- Deep proficiency in Google Cloud Platform, specifically Vertex AI, Gemini Pro/Flash, and Generative AI Studio.
- Demonstrated experience with RAG (Retrieval-Augmented Generation), Prompt Engineering, and fine-tuning LLMs for specific industry domains.
- Expert in API-led connectivity (REST/gRPC) and event-driven architecture.
- Advanced knowledge of OAuth, JWT, and data privacy standards (HIPAA, GDPR) specifically regarding AI data processing.
- Experience in Healthcare or Fintech (highly regulated environments).
- Certifications: Google Professional Cloud Architect or Google Professional Machine Learning Engineer.
- Experience with Forward Deployment delivery models, working directly with end-users to iterate on AI-driven features.
Salary (Rate): undetermined
City: undetermined
Country: undetermined
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Role Purpose
As the Tech Lead and Solutions Architect, you will serve as the bridge between complex business requirements and cutting-edge AI implementation. You will lead the design, development, and long-term management of enterprise applications, ensuring they are seamlessly integrated with Google Gemini to deliver autonomous, intelligent, and scalable user experiences.
Core Responsibilities
< data-path-to-node="7">1. Solutions Design & ArchitectureArchitectural Blueprinting: Design end-to-end scalable architectures for multi-tier applications, prioritizing modularity and high availability.
AI Integration: Lead the architectural strategy for deploying applications into the Google Gemini/Vertex AI ecosystem, focusing on Model Garden, Tuning, and Grounding.
Data Strategy: Design data pipelines and vector databases (e.g., Pinecone, BigQuery Vector Search) to provide real-time context to LLMs.
Full-Stack Leadership: Oversee the development of applications using modern frameworks (LWC, React, Node.js, or Python) ensuring clean code and robust security.
Lifecycle Management: Manage the entire Application Development Life Cycle (SDLC), from initial discovery and prototyping to production support and refactoring.
DevOps & Deployment: Architect CI/CD pipelines using tools like GitHub Actions, Jenkins, or Google Cloud Build to ensure rapid, low-risk deployments.
Mentorship: Act as the "North Star" for the engineering team, performing code reviews and enforcing technical standards.
Vendor & Stakeholder Management: Collaborate with Product Owners and senior leadership to align the technical roadmap with business OKRs.
Innovation: Stay at the forefront of Generative AI, identifying opportunities to replace legacy manual workflows with autonomous AI agents.
Technical Qualifications
Platform Expertise: 10+ years of IT experience, with at least 4 years in a Solutions Architect or Tech Lead capacity.
Google Cloud & Gemini: Deep proficiency in Google Cloud Platform (Google Cloud Platform), specifically Vertex AI, Gemini Pro/Flash, and Generative AI Studio.
AI Methodologies: Demonstrated experience with RAG (Retrieval-Augmented Generation), Prompt Engineering, and fine-tuning LLMs for specific industry domains.
Integration: Expert in API-led connectivity (REST/gRPC) and event-driven architecture.
Security: Advanced knowledge of OAuth, JWT, and data privacy standards (HIPAA, GDPR) specifically regarding AI data processing.
Preferred Specialized Experience
Experience in Healthcare or Fintech (highly regulated environments).
Certifications: Google Professional Cloud Architect or Google Professional Machine Learning Engineer.
Experience with Forward Deployment delivery models, working directly with end-users to iterate on AI-driven features.
Success Metrics
AI Accuracy: Successful grounding of Gemini agents to achieve <5% hallucination rates.
Velocity: Maintaining a high deployment frequency with a <10% change failure rate.
Scalability: Systems designed to handle 2x current peak load without architectural redesign.