AI Architect

TechDigital Group; Hoboken (NJ); On-site; USD 120,000 - 180,000; Full time

Job summary

TechDigital Group is seeking an AI/ML architect to design multi-agent workflows and data models, while monitoring performance and inference costs to meet business goals.

You will work on privacy, security, and compliance, ensuring responsible AI deployment and alignment with financial budgets. Lead engineering teams through architectural trade-offs and delivery strategies.

Qualifications

• Proficiency in building AI/ML workflows and frameworks.
• Experience with cloud AI services and data pipelines.
• Strong programming skills in Python and Java.
• Knowledge of model deployment and inference cost management.

Responsibilities

• Designing multi-agent workflows using Lang Chain or Lang Graph and architectural design patterns.
• Designing data models.
• Tracking model performance, managing inference costs, and latency.
• Guarding privacy, stopping data leaks, and mitigating model hallucinations.
• Aligning AI choices with business goals and budgets.
• Guiding engineering teams through design trade-offs and execution.

Skills

AI & ML

LLMs

RAG pipelines

AWS

Google Cloud

Azure

Kubernetes

Python

Java

Data governance

Tools

Docker

Lang Chain

Lang Graph

Job description

Skill Set

• AI & Machine Learning: Mastery of deep learning frameworks like PyTorch or TensorFlow, large language models (LLMs), and retrieval-augmented generation (RAG) pipelines.
• Cloud & Infrastructure: Experience with cloud services AWS Saga Maker, Google Cloud AI, Microsoft Azure AI Docker, Kubernetes
• Data Management: Knowledge of data pipelines, ETL processes, vector databases, and data governance.
• Programming: Proficiency in core languages such as Python & Data Engineering Libraries and Java.

Job Description

• Designing multi-agent workflows using frameworks like Lang Chain or Lang Graph and architectural design patterns
• Designing data models
• Tracking model performance, managing inference costs, and handling latency tracking.
• Security & Compliance: Guarding privacy, stopping data leaks, and mitigating model hallucinations.
• Aligning technical AI choices with real business goals and financial budgets.
• Guiding engineering teams through design trade-offs and project execution