AI/ML - Lead Engineer

Prodapt•Richardson, TX

About The Position

Prodapt is the largest specialized player in the Connectedness industry. As an AI-first strategic technology partner, Prodapt provides consulting, business reengineering, and managed services for the largest telecom and tech enterprises building networks and digital experiences of tomorrow. Prodapt has been recognized by Gartner as a Large, Telecom-Native, Regional IT Service Provider. A “Great Place To Work® Certified™” company, Prodapt employs over 6,000 technology and domain experts in 30+ countries. Prodapt is part of the 130-year-old business conglomerate The Jhaver Group, which employs over 32,000 people across 80+ locations globally. The engineer will contribute across data migration assessment, application modernization strategy, AI use-case discovery, and reference architecture definition, supporting the foundation for future implementation phases on Google Cloud Platform (GCP).

Requirements

7+ years of experience as a Full-Stack Engineer (Java and/or Python)
Strong hands-on experience with: Java (Spring Boot, REST APIs, microservices) Python (scripting, data processing, automation)
Practical exposure to AI/ML engineering (early-stage experience acceptable), including: Model integration Prompt-based workflows AI service consumption via APIs
Experience writing Python and shell scripts for: Data analysis, profiling, and validation Automation and batch processing Integration testing and tooling
Experience with cloud platforms (GCP preferred; AWS/Azure acceptable)
Solid understanding of data pipelines, APIs, and integration patterns
Experience contributing to architecture discussions, assessments, and strategy documents

Nice To Haves

Exposure to Agentic AI, AI orchestration, or multi-agent frameworks
Familiarity with: Pandas, NumPy, PySpark, or similar data libraries SQL and cloud-native data warehouses (BigQuery preferred)
Experience with DevOps tools (CI/CD, containers, IaC)
Knowledge of security and compliance considerations in regulated environments
Utility, energy, or large-enterprise modernization experience is a plus

Responsibilities

Analyze existing applications and services to assess AI-readiness and modernization opportunities.
Contribute to defining AI-enabled application patterns, including agent-based workflows and orchestration concepts.
Develop lightweight POCs, scripts, and prototypes to validate AI use cases and data flows during assessment.
Support current-state analysis of data sources, pipelines, APIs, and legacy platforms.
Assist in defining migration approaches to GCP-based data architecture.
Develop Python- and Java-based utilities/scripts for: Data profiling and validation Transformation logic testing Migration feasibility assessment
Contribute to reconciliation, rollback, and recovery strategy definition.
Participate in use-case discovery workshops with business and IT stakeholders.
Help define reference architecture concepts (high-level) for modernized applications.
Evaluate technology stacks, frameworks, and DevOps tooling for AI-enabled platforms.
Support creation of the Technology Proposal and Implementation Playbook.
Assist in building conceptual execution roadmaps (phases, milestones, dependencies).
Support definition of security, compliance, and governance guardrails for AI and data platforms.
Contribute to Phase 0 deliverables and client-ready documentation.