Lead AI Platform Architect for Agentic AI on AWS

ARCHER; Jersey City (NJ); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Health Care Coverage

On-Site Health And Wellness Centers

Retirement Savings Plan

Backup Childcare

Tuition Reimbursement

Mental Health Support

Financial Coaching

Commission-Based Pay (Eligible Roles)

Discretionary Incentive Compensation

Job summary

ARCHER leads the architecture and delivery of scalable agentic AI platforms and cloud-native AWS services for enterprise Finance workflows. This role drives evaluation, observability, security, reliability, and cost management while mentoring engineers and guiding technical direction across teams.

Requires five+ years in applied software engineering, advanced Python, and a track record shipping production LLM applications with agentic workflows, tool integrations, and RAG.

Qualifications

• Requires at least five years of applied software engineering experience.
• Advanced Python skills and track record of architecting and shipping production LLM applications with agentic workflows.
• Experience with tool integrations, RAG, and enterprise AI tools.
• Proven technical leadership and safe, effective use of enterprise-approved AI development tools.
• Experience with AWS cloud-native services and responsible AI practices.

Responsibilities

• Lead architecture and hands-on delivery of scalable agentic AI platforms.
• Establish standards for evaluation, observability, security, reliability, and cost management.
• Mentor engineers and influence technical direction across teams.

Skills

Python

Generative AI

Agentic AI

Large Language Models

AWS

Amazon Bedrock

Google Vertex AI

LangChain

LangGraph

Retrieval-Augmented Generation

Vector Databases

Semantic Search

Prompt Management

Cloud-Native Architecture

Kubernetes

Technical Leadership

Job description

ARCHER leads the architecture and delivery of scalable agentic AI platforms and cloud-native AWS services for enterprise Finance workflows. This role drives evaluation, observability, security, reliability, and cost management while mentoring engineers and guiding technical direction across teams.

Requires five+ years in applied software engineering, advanced Python, and a track record shipping production LLM applications with agentic workflows, tool integrations, and RAG.