AI and Integration Architect

Job summary

Define the technical blueprint and roadmap for enterprise AI adoption, focusing on LLMs, RAG, and predictive analytics. Design high-performance API services and event-driven architectures to power real-time AI applications.

Job details

Tiger Analytics is a global leader in AI and advanced analytics consulting, empowering Fortune 1000 companies to solve their toughest business challenges. We are on a mission to push the boundaries of what AI can do, providing data-driven certainty for a better tomorrow. Our diverse team of over 6,000 technologists and consultants operates across five continents, building cutting-edge ML and data solutions at scale. Join us to do great work and shape the future of enterprise AI. This role sits at the intersection of artificial intelligence and robust enterprise integration. Define the technical blueprint for scaling AI adoption across the organization, focusing specifically on LLMs, RAG, and predictive analytics, while building the high-performance API and messaging backbones required to fuel these real-time systems. Job Description AI Strategy & Architecture: Define the technical blueprint and roadmap for enterprise AI adoption. Architect scalable frameworks for LLM integration, RAG, and predictive modeling, ensuring cost-efficiency, scalability, and ethical AI standards. Data Integration & APIs: Design high-performance, secure API services (RESTful, GraphQL) and event-driven architectures to connect disparate systems and power real-time AI applications. AI & Data Governance: Establish guardrails for data privacy, compliance, and security regarding AI training data, model inputs, and API access management. Cross-Functional Leadership: Collaborate with executive leadership, data scientists, and product teams to translate business goals into production-ready AI and integration strategies. 8+ years of experience in software architecture, system integration, or machine learning engineering, with at least 2-3 years dedicated to productionizing AI/LLM solutions. Preferred experience in Azure Databricks Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility. Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law. Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.

What you’ll do

Define the technical blueprint and roadmap for enterprise AI adoption, focusing on LLMs, RAG, and predictive analytics. Design high-performance API services and event-driven architectures to power real-time AI applications.

Requirements

Requires 8+ years of experience in software architecture or ML engineering, with 2-3 years specifically in productionizing AI/LLM solutions. Preferred experience with Azure Databricks is desired.

Listed skills

• Dedicated · Preferred
• Software · Preferred
• Microsoft Azure · Preferred
• Technical · Preferred
• Leadership · Preferred
• Data analysis · Preferred
• Compliance · Preferred
• Development · Preferred
• Time · Preferred
• future · Preferred
• Integration · Preferred
• efficiency · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• AI Architecture
• LLM Integration
• RAG
• Predictive Analytics
• API Design
• RESTful APIs
• GraphQL
• Event-Driven Architecture
• Data Governance
• Azure Databricks
• System Integration
• Machine Learning Engineering

Job areas

• Data & Analytics
• Technology
• Software
• Consulting
• Engineering

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