AI Engineer - Applied AI ($350-400k)
- Source: LinkedIn
- TekVizor
- On-site
- New York City
- Full-Time
- Mid level
Job Description
AI Engineer - Applied AI - Building AI for fintech
📍 New York, NYC (4 days in the NYC office)
🕒 Full-Time Employee position
🌍 U.S. Citizenship, Green Card
💰 $350,000 - $400,000
About the Role
Hiring a Senior AI Engineer for an early-stage, high-growth AI FinTech company. We’re building an enterprise-grade platform and we need highly curious, hard-working self-starters.
This role is for senior-level builders who design, architect, and ship production-grade AI systems.
You will own the design and delivery of complex, multi-service AI architectures involving agent orchestration, secure workflows and real-world operational constraints.
What You Will Do
- Own the architecture, design, and implementation of full AI systems, including: Multi-Agent, distributed system architecture, workflow, agent orchestration, tool use, code execution, retrieval, KV cache management, routing, batching, multi-step planning loops.
- Proven experience designing and deploying complex agentic systems using LLMs.
- Hands-on design with multi-agent orchestration, routing, and tool orchestration.
- Your work goes far beyond prompts or app-level features. You will architect platforms and sustainable AI infrastructure.
- You will build real, production agents—not prototypes relying solely on framework abstractions.
- Design knowledge graph analytics enabling agents to perform contextual reasoning.
- End-to-End AI System Design.
Desired Qualifications
- 3+ years building and deploying Agentic, ML / LLM-powered systems in production environments.
- Degree in Computer Science or similar.
- Build APIs, microservices, and distributed workflows.
- Work across cloud environments (AWS, Azure, GCP)
- Ability to integrate data pipelines, messaging systems, and storage layers.
- You are as comfortable with backend architecture as with LLM integration.
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Skills
- microsoft-graph
- amazon-web-services
- microsoft-azure
- google-cloud-platform
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