AWS Architect

Artifintech; Charlotte (NC); On-site; USD 91,000 - 124,000; Full time

Job summary

Artifintech is seeking an AWS Architect for a 12-month engagement in Charlotte, NC. The role requires U.S. work authorization and offers multiple billing options (W-2, 1099, C2C) with a bill rate of $78/hour.

You will design and deploy cloud-optimized optimization workflows on AWS (Batch on Fargate, Lambda, Step Functions, S3) and collaborate with ML/DL tools; strong MILP modeling and Terraform are used.

Qualifications

• Formulate and tune MILP models using Pyomo, PuLP, and solvers (Gurobi, HiGHS, CBC) to optimize budgets/resources.
• Deploy optimization workflows as scalable AWS microservices using Terraform.
• Ingest predictive asset-health outputs to feed optimization models.
• Build deterministic run harnesses with auditable outputs and explainability.

Responsibilities

• Formulate MILP models for optimization under budget/resource constraints.
• Package workflows as AWS microservices (Batch on Fargate, Lambda, Step Functions) with Terraform.
• Ingest asset-health data to feed optimization models.

Skills

MILP formulation

Mathematical modeling

Pyomo

PuLP

Gurobi

Tools

AWS (Batch, Fargate, Lambda, Step Functions, S3)

Terraform

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Job Title: AWS Architect
Location: Charlotte, NC
Duration: 12 Months + Extension
Bill Rate: $78/hour
Job Type: W-2, 1099, C2C
Client: To Be Discussed Later
Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EAD

Job Description:

• Mathematical Modeling: Formulate and tune Mixed-Integer Linear Programming (MILP) models using Python frameworks (Pyomo, PuLP) and solvers (Gurobi, HiGHS, CBC) to handle budget, resource, and portfolio constraints.
• Cloud Architecture & Deployment: Package optimization workflows as scalable cloud microservices on AWS (AWS Batch on Fargate, Lambda, Step Functions, S3) using Terraform.
• Data Integration: Ingest predictive asset-health outputs (Probability of Failure, Remaining Useful Life) to feed optimization models.
• Deterministic Execution & Explainability: Build robust run harnesses for reproducible results, diagnostic tools (constraint relaxation/infeasibility analysis), and auditable outputs (shadow prices, binding constraints).
• AI-Assisted Engineering: Utilize GitHub Copilot, Spec-Driven Development (SDD), and AI agents to enhance software delivery and build scenario-explanation tools.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.