Jobs at PDI Technologies

Designs and deploys AI-enabled platform capabilities, integrating LLMs, prompt engineering, RAG, embeddings, and intelligent workflows. Builds AI evaluation and validation frameworks alongside scalable QA automation for APIs, microservices, distributed systems, and platform services. Integrates automated testing into CI/CD pipelines, validates reliability and performance, and collaborates with engineering, product, data, and platform teams. Provides technical leadership on AI engineering, automation, and quality standards.

Develop and maintain PDI software products, participate in application design, troubleshoot and debug issues, perform engineering-level testing, and collaborate with Product Owners and QA Engineers in an Agile environment. The role includes estimating feature work, documenting solutions, assessing project risks, validating requirements, and applying software engineering fundamentals across web stacks and relational databases.

Lead and grow a ~20-person SRE organization supporting the Paylo platform. Set SRE vision, reliability roadmap, SLIs/SLOs, incident management, and multi-cloud infrastructure standards. Stay hands-on with architecture reviews, Kubernetes/Helm, GitOps (Argo), IaC (Terraform/OpenTofu), Jenkins pipelines, and Datadog observability while coaching managers and aligning reliability investments with business risk and compliance.

Assist in accounting activities including A/P and A/R functions, general ledger activities, and financial reporting for convenience retail and petroleum companies.

Design, build, test, and support PDI enterprise software as part of an agile team. Reproduce and troubleshoot customer issues, write safe T-SQL correction scripts, investigate defects across layers, lead small-to-medium projects, mentor junior engineers, collaborate with Architecture, DevOps, Product, and QA, and continuously improve code quality, performance, and engineering practices.

Analyze large datasets, build and optimize machine learning models, run A/B tests, and design ETL pipelines. Collaborate with data engineering, create automated tests, present findings to technical and non-technical stakeholders, and apply domain knowledge to feature engineering and modeling.

Design, build, test, and support enterprise software in an Agile team. Reproduce and troubleshoot customer issues, write safe T-SQL correction scripts, debug across layers (WinForms, services, stored procedures), collaborate with QA/Product, and continuously improve code quality and performance.

Senior data engineer responsible for designing, building, and optimizing scalable cloud-based data pipelines and lakehouse solutions on AWS. Lead complex integrations, implement data modeling and governance, promote engineering best practices, automate infrastructure and CI/CD, mentor engineers, and collaborate with stakeholders to deliver reliable analytics and BI solutions.

Design, build, and maintain AWS-native cloud data pipelines and ETL/ELT processes (S3, Glue, Redshift, AppFlow, Step Functions). Integrate enterprise apps (Salesforce, NetSuite), develop scalable data models, monitor pipeline performance, ensure data quality and governance, support CI/CD and IaC (Terraform), apply AI/ML for data quality/monitoring, and collaborate with stakeholders and peers.