AI/ML Architect - 174829

Piper Companies; Sparks (NV); On-site; USD 150,000 - 200,000; Full time

Benefits offered by this job

PTO

Paid Holidays

Medical

Dental

Vision

401(k)

Sick Leave

Job summary

Piper Companies seeks an experienced AI/ML Architect to lead the design, deployment, and scaling of enterprise AI, machine learning, and Generative AI solutions. You will drive AI strategy, architect cloud-native platforms, and build production-ready solutions leveraging AWS, Databricks, and modern AI frameworks.

The ideal candidate has a strong background in cloud architecture, MLOps, and large-scale data platforms, with hands-on experience delivering enterprise-grade AI applications.

Qualifications

• 7+ years in software engineering, cloud architecture, data engineering, or related fields.
• 3+ years designing and implementing AI/ML and Generative AI in cloud environments.
• Proven experience delivering enterprise-scale AI applications from concept to production.

Responsibilities

• Design and implement scalable AI/ML and Generative AI solutions within AWS environments.
• Develop enterprise architecture standards for AI platforms, model deployment, and governance.
• Ensure high availability, security, performance, and scalability of AI systems.
• Architect and deploy autonomous AI agents and multi-agent workflows.
• Build production-ready conversational AI and agent-based systems.
• Design integrations between AI services, enterprise tools, and business applications.
• Develop end-to-end data pipelines and ML workflows using Databricks.
• Implement scalable data processing solutions utilizing Spark, Delta Lake, and MLflow.
• Support model training, deployment, monitoring, and lifecycle management.
• Establish MLOps standards, model governance, monitoring, and compliance frameworks.

Skills

AWS

Python

Databricks

MLOps

Terraform

CI/CD

AI/ML

Tools

Spark

Delta Lake

MLflow

SageMaker

Job description

AI/ML Architect

Location: Sparks, MD
Type: Full-Time, Exempt

Overview

We are seeking an experienced AI/ML Architect to lead the design, deployment, and scaling of enterprise AI, machine learning, and Generative AI solutions. This role will drive AI strategy, architect cloud-native AI platforms, and build production-ready solutions leveraging AWS services, Databricks, and modern AI frameworks. The ideal candidate has a strong background in cloud architecture, machine learning, Generative AI, MLOps, and large-scale data platforms, with hands‑on experience building enterprise‑grade AI applications.

Key Responsibilities

AI & Cloud Architecture

• Design and implement scalable AI/ML and Generative AI solutions within AWS environments.
• Develop enterprise architecture standards for AI platforms, model deployment, and governance.
• Ensure high availability, security, performance, and scalability of AI systems.

Agentic AI Solutions

• Architect and deploy autonomous AI agents and multi‑agent workflows.
• Build production‑ready conversational AI and agent‑based systems.
• Design integrations between AI services, enterprise tools, and business applications.

Data & Machine Learning Platforms

• Develop and optimize end‑to‑end data pipelines and machine learning workflows using Databricks.
• Implement scalable data processing solutions utilizing Spark, Delta Lake, and MLflow.
• Support model training, deployment, monitoring, and lifecycle management.

Generative AI & Analytics

• Integrate Generative AI capabilities into enterprise applications.
• Enable natural language interactions with enterprise data and reporting platforms.
• Develop intelligent solutions that automate insights, recommendations, and decision‑making processes.

MLOps & Governance

• Establish MLOps standards, model governance, monitoring, and compliance frameworks.
• Implement model registries, traceability, telemetry, and deployment automation.
• Ensure AI solutions meet security, operational, and regulatory requirements.

Technical Leadership

• Serve as the technical lead for AI and machine learning initiatives.
• Mentor engineering teams and provide architecture guidance.
• Partner with product, engineering, and business stakeholders to deliver AI‑driven solutions.

Experience

Required Qualifications

• 7+ years of experience in software engineering, cloud architecture, data engineering, or related technical disciplines.
• 3+ years of experience designing and implementing AI/ML and Generative AI solutions in cloud environments.
• Proven experience building enterprise‑scale AI applications from concept through production deployment.

Technical Expertise

• Strong hands‑on experience with AWS AI and machine learning services.
• Deep knowledge of Databricks, Spark SQL, Delta Lake, and MLflow.
• Experience building conversational AI systems and agent‑based architectures.
• Strong Python development skills.
• Experience with Infrastructure as Code (IaC), preferably Terraform.
• Understanding of modern MLOps practices, model governance, and CI/CD pipelines.

Preferred Experience

• Experience with GenAI frameworks such as LangGraph, CrewAI, or similar agent orchestration tools.
• Experience integrating AI systems with enterprise platforms and business applications.
• Familiarity with cloud‑native application architecture and containerized environments.

Required Certifications

• AWS Certified Solutions Architect – Associate
• AWS Certified AI Practitioner

Preferred Certifications

• AWS Certified Solutions Architect – Professional
• AWS Certified Generative AI Developer – Professional
• Databricks Machine Learning Professional or Data Engineer Professional
• AWS Certified Machine Learning – Specialty

Compensaiton

• Salary: $150,000 - $200,000
• Benefits: PTO, Paid Holidays, Medical, Dental, Vision, 401(k), Sick Leave (as required by law).

Keywords:
AI/ML Architect, AI Architect, ML Architect, AWS, Amazon Web Services, Amazon Bedrock, Bedrock, Bedrock AgentCore, Generative AI, GenAI, Artificial Intelligence, Machine Learning, Machine Learning Architecture, Cloud Architecture, Enterprise Architecture, AI Strategy, Large Language Models, LLM, Foundation Models, AI Agents, Agentic AI, Multi‑Agent Systems, Conversational AI, LangGraph, CrewAI, Strands SDK, Agent Orchestration, Databricks, Databricks Lakehouse, Databricks Data Intelligence Platform, Spark, Apache Spark, Spark SQL, Delta Lake, MLflow, Databricks Model Serving, MLOps, Model Governance, Model Registry, Model Deployment, Model Monitoring, SageMaker, Amazon SageMaker, Data Engineering, Data Pipelines, ETL, ELT, Data Architecture, Data Analytics, Data Platform, Predictive Analytics, Business Intelligence, QuickSight, Generative BI, AWS AI Services, Cloud AI, Cloud ML, Python, PySpark, Terraform, Infrastructure as Code, IaC, API Integration, REST APIs, Microservices, Cloud Infrastructure, Scalable Architecture, AI Solutions, Enterprise AI, Production AI, AI Governance, AI Security, LLMOps, RAG, Retrieval Augmented Generation, Prompt Engineering, Fine Tuning, Vector Databases, Embeddings, CI/CD, Automation, Cloud Migration, Data Governance, Data Modeling, Serverless Architecture, Solution Architecture, Technical Leadership, Technical Architecture, AI Platform Engineering, Software Engineering, Cloud Engineering, Systems Design, Enterprise Data Platforms