Applied AI Engineer

PCC Talent Acquisition Portal•South Gate, CA

6d•Onsite

About The Position

The Applied Artificial Intelligence Engineer will build and deploy practical AI applications that improve commercial performance - including quoting, pricing, contract review, pipeline management, capacity planning, and forecasting. This role is focused on the front end of the business, partnering directly with Sales, Finance, Operations, Quality, and Engineering leadership to turn data into faster, better decisions. This role will build solutions that are embedded in daily workflows and deliver measurable business outcomes.

Requirements

Databricks (SQL, Delta Lake, Model Serving, Unity Catalog)
AI capabilities: LLM APIs, LLM agent development, prompt engineering, RAG workflows
Strong SQL and Python (or equivalent)
Familiarity with APIs, Git, and application deployment
Data exploration and analysis
ETL/ELT workflows
Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Artificial Intelligence, Data Science, Mathematics, Statistics, Physics, or related discipline.
3-6 years developing complex applications
2+ years of AI/ML experience
Experience with CRM and/or CPQ systems strongly preferred
Experience supporting commercial or revenue operations is a plus
Experience with fine-tuning models for specific tasks
Experience with vector databases, embeddings, evaluation frameworks, AI observability, and production LLM application architectures.
Manufacturing analytics
Quality analytics and root-cause analysis
ERP systems (Syteline, Infor, SAP, Oracle, Epicor, etc.)
Strong business translator—turns commercial problems into scalable solutions
Drives adoption—not just delivery
Focused on building tools that are actively used and that deliver P&L results

Nice To Haves

Master's degree preferred.

Responsibilities

Partner with Sales, Finance, Operations, Quality, and Engineering to identify high-value AI use cases for analysis, summarization, and action recommendation. Examples include, but not limited to: Market and opportunity summaries, Guided quoting and pricing guardrails, deal books, similar deal insights, Pipeline and forecast intelligence dashboards, SIOP inputs, Daily sales TOC dashboard, Contract Review, Quality disposition and RCCA, OCR extraction of records in varying format into centralized database
Build and deploy AI-enabled applications using Databricks
Integrate data across CRM, CPQ, ERP, and contract systems
Embed tools directly into commercial workflows (not standalone dashboards)
Lead pilots end-to-end (design → test → launch → sustain)
Train users and drive adoption within real business routines
Ensure accuracy, governance, and compliance (AS9100 / ITAR / DFARS)
Align with Corporate and Division IT on AI standards and controls
Report measurable improvements in revenue, margin, and forecast performance
Creating evaluations and using observability tools to measure and monitor performance