Hybrid AI/ML Engineer – Data Products & RAG Systems

HTC Global Services, Inc.; Dearborn, Northern (MI, KY); Hybrid; USD 120,000 - 170,000; Full time

Benefits offered by this job

Hybrid and Workplace flexibility

Work-Life-Balance

Career development program

Rewards & Recognition program

Job summary

HTC Global Services, Inc. is seeking an AI/ML Engineer to build intelligent data products and production RAG systems across data platforms and cloud engineering.

You will design and implement architectures that handle large-scale structured and unstructured information with emphasis on quality, reliability, and observability. The role requires strong Python/SQL skills, experience with cloud platforms (GCP), and hands-on work with embeddings, vector retrieval, and security-aware development.

Qualifications

• 5+ years of experience building and operating production software, data, or machine learning systems.
• Strong Python and SQL skills.
• Experience with cloud platforms, managed data services, object storage, containers, and distributed workloads.
• Hands-on experience applying large language models to real products, including prompt design, structured outputs, tool use, evaluation, and production monitoring.
• Strong understanding of embeddings, vector retrieval, RAG architecture, model limitations, and techniques for improving answer quality and faithfulness.
• Experience with software engineering fundamentals, including testing, code review, version control, CI/CD, observability, and secure development practices.
• Demonstrated ability to diagnose difficult production problems using measurable evidence, experimentation, profiling, and disciplined root-cause analysis.
• Experience with workflow orchestration, job scheduling, or reliable batch execution frameworks.
• Experience with artificial intelligence and expert systems.
• Experience with GCP.
• Experience working with APIs and software testing.
• Experience with data analysis.

Responsibilities

• Architect, build, and operate reliable data products that ingest and transform diverse structured and unstructured information at enterprise scale.
• Create resilient orchestration and delivery patterns for batch and near-real-time workloads, including observability, alerting, and operational runbooks.
• Develop production Retrieval-Augmented Generation (RAG) systems that combine semantic retrieval, structured data, and grounded responses for engineering use cases.
• Design agentic AI workflows that decompose complex questions, select appropriate data sources and tools, validate results, and provide explainable answers with citations.
• Develop and evaluate embedding, document-understanding, and multimodal inference workflows while balancing quality, latency, scalability, and cost.
• Lead cloud architecture, containerization, infrastructure-as-code, and CI/CD practices for secure and repeatable deployment across environments.
• Own system reliability from design through production by investigating incidents, profiling performance, eliminating failure modes, and improving capacity planning.
• Deliver analytics experiences and decision-support tools that make complex technical data useful to engineers, program teams, and leadership.
• Establish data quality, lineage, validation, and governance practices to help users understand information sources and assess data reliability.
• Build incremental and restartable processing with checkpointing and recovery strategies to protect data integrity during long-running or partially failed workloads.

Skills

Python

SQL

Cloud platforms

Distributed workloads

AI/ML

LLMs & RAG

APIs

CI/CD

Observability

Tools

GCP

Docker

Kubernetes

Terraform

Object storage

Job description

HTC Global Services, Inc. is seeking an AI/ML Engineer to build intelligent data products and production RAG systems across data platforms and cloud engineering.

You will design and implement architectures that handle large-scale structured and unstructured information with emphasis on quality, reliability, and observability. The role requires strong Python/SQL skills, experience with cloud platforms (GCP), and hands-on work with embeddings, vector retrieval, and security-aware development.