AI Architect
- NEW YORK, NY, United States
$152,000 to $155,000 USD / year
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Job details
- Pay
- $152,000 to $155,000 USD / year
- Posting language
- English
- Posted
Original job description
Immediate need for a talented AI Architect. This is a Fulltime opportunity with long-term potential and is located in New York City, New York(Hybrid).Please review the job description below and contact me ASAP if you are interested. Job Diva ID: 26-12615 Pay Range: $152000 - $155000/annum base + 10% + 5 % bonus. Employee benefits include, but are not limited to, health insurance (medical, dental, vision), 401(k) plan, and paid sick leave (depending on work location). Key Responsibilities: Architect & Scale AI Solutions: Design end-to-end AI/ML architectures, including scalable, secure, and production-ready systems using Machine Learning, Deep Learning, and Large Language Models (LLMs). Establish best practices for building robust and reusable AI platforms. Lead Generative & Agentic AI Innovation: Define and implement enterprise-grade Generative AI and Agentic AI solutions, including multi-agent systems, autonomous workflows, and LLM orchestration frameworks. Drive innovation in areas such as RAG, context engineering, and intelligent automation. Enterprise Impact & Transformation: Own and deliver scalable AI solutions across multiple business domains (marketing, supply chain, retail, operations), ensuring measurable business impact and alignment with organizational strategy. Technical Leadership & Governance: Act as a technical authority defining architecture standards, AI governance, model lifecycle management, and responsible AI practices. Ensure scalability, security, and compliance across all AI initiatives. Cross-functional Leadership: Collaborate with senior stakeholders, product leaders, data engineers, and platform teams to translate business problems into AI-driven solutions. Lead architecture discussions and influence key technical decisions. Mentorship & Capability Building: Mentor senior engineers and data scientists, drive knowledge sharing, and build a strong AI engineering culture. Lead communities of practice and contribute to organizational capability development. Additional Expectations (Architect Level): Define AI roadmap and contribute to organizational AI strategy Establish reusable frameworks, accelerators, and best practices Drive cost optimization and performance efficiency at scale Ensure ethical AI and responsible AI implementation Key Requirements and Technology Experience: Must have skills: 11-13 years of experience in AI/ML, with significant experience in designing and deploying large-scale AI systems Data Modeling, Generative & Agentic AI, Machine Learning, Python, Embeddings & Vector Databases Proven experience in architecting enterprise-grade AI/ML platforms and solutions Technical Expertise: AI/ML & Advanced Analytics: Strong expertise in Machine Learning, Deep Learning, and statistical modeling Experience designing scalable ML systems and production pipelines Generative AI & Agentic AI: Deep expertise in LLMs (GPT, Claude, Llama, Gemini) and their enterprise applications Strong experience in RAG architectures, prompt engineering, context engineering, embeddings, and vector databases Hands-on experience with agentic frameworks (LangGraph, CrewAI, AutoGen) and multi agent orchestration Architecture & Engineering: Strong system design and architecture skills for distributed AI systems Expertise in Python, SQL, and software engineering best practices Experience with microservices, APIs, and scalable backend systems MLOps & Platform Engineering: Strong experience in MLOps practices including CI/CD, model versioning, monitoring, and governance Hands-on experience with tools such as MLflow, Vertex AI, Kubeflow, or similar Cloud & Data Platforms: Deep experience with cloud platforms, especially GCP (Vertex AI, BigQuery) and/or Databricks Strong understanding of data lakes, data warehouses, and real-time data processing Soft Skills & Mindset: Strategic Leadership: Ability to align AI initiatives with business goals and drive long-term technology visio Ownership & Accountability: Takes end-to-end owners