AI & Data Solutions Architect (CPG/Retail)

Fractal Analytics•Texas, IL

19h•Hybrid

About The Position

Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner. Note: This position is not eligible for Immigration Sponsorship at this time. Coverage: Multiple U.S. accounts (deep focus on 2–3 strategic clients). Travel: Frequent travel required. Location Preference: Dallas or Chicago (flexible based on candidate). We’re looking for a Principal AI & Data Solutions Architect to drive growth across our CPG/Retail portfolio in the U.S. This role sits at the intersection of thought leadership, solutioning, and hands-on technical execution. You will operate as a trusted advisor and AI/Data leader to clients—partnering closely with account teams to shape opportunities, define engineering roadmaps, and solve complex business problems using modern data and AI foundations. This is not a pure delivery role. The focus is on driving growth through technical depth, client engagement, and high-impact solutioning, with selective involvement in execution when needed. You’ll work deeply with 2–3 strategic clients, while supporting a broader set of accounts across the region.

Requirements

Deep technologist with strong expertise in data engineering, AI/ML, and solution architecture
Proven ability to operate in a client-facing, consultative role
Strong mix of: Pre-sales / solutioning, Technical leadership, Hands-on problem solving
Experience ~15–20 years of experience across: Data engineering and platform architecture, AI/ML or advanced analytics environments, Enterprise solutioning and consulting
Strong experience working with global clients in a consulting or services environment
Exposure to CPG/Retail
Expertise in: Data platforms (data lakes, warehouses, modern data stack), Distributed processing (Spark, etc.), AI/ML ecosystems and AIF concepts
Strong experience with cloud platforms (AWS, Azure, or GCP)
Programming experience in Python, PySpark, Java, or Scala
Solid understanding of: Data modeling, ETL/ELT, Data governance, security, and compliance
Strong ability to translate business problems into technical solutions
Excellent client communication and executive presence
Ability to influence without authority across client and internal teams

Responsibilities

Act as a trusted technical advisor to client stakeholders across AI, data, and engineering
Drive account growth through thought leadership, proactive idea generation, and solution shaping
Partner with account and sales teams during pre-sales, including discovery, solutioning, and proposal development
Translate business problems into scalable, high-impact AI/data solutions
Define and drive end-to-end data and AI architecture (data platforms, pipelines, ML/AI systems, AIF)
Develop engineering roadmaps aligned to client business objectives
Design scalable, enterprise-grade solutions across data platforms, cloud ecosystems, and AI/ML frameworks
Ensure solutions balance performance, scalability, cost, and maintainability
Go beyond strategy—operate at depth when required (architecture reviews, solution design, problem-solving)
Step into delivery challenges when needed and help unblock teams
Guide and mentor architects and engineering teams across global delivery
Work closely with: Account leaders and sales teams, India-based delivery teams, Data science, engineering, and platform teams
Act as the bridge between business, solutioning, and execution
Stay current with advancements in AI, data engineering, and cloud technologies
Drive adoption of modern data platforms, multi-cloud architecture, and AI frameworks
Evaluate and introduce new tools, frameworks, and accelerators