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# AI Data Engineer

- **Company:** HTC Global Services, Inc.
- **Location:** Woodbridge Township, NJ, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon S3, Cloud Computing, Cloud Engineering, Code Review, Continuous Integration, Data Cleansing, Data Integration, DevOps, Amazon DynamoDB, Identity and Access Management, Python (Programming Language), Machine Learning, NoSQL, Search Technologies, Secure Coding, Software Engineering, SQL Databases, Unstructured Data, Management of Software Versions, AI Infrastructure, Large Language Models, Prompt Engineering, Generative AI, Amazon Relational Database Service, Containerization, Kubernetes, Information Technology, Deployment Automation, Machine Learning Operations, Virtual Agents, Cloudwatch, Api Gateway, Terraform, Software Version Control, Automation Anywhere, Microservices
- **Published:** June 25, 2026
- **Apply:** https://www.juju.com/job/00000000gb03ip

## About the Role

+ Bachelor's degree in Computer Science, Engineering, Data Science, AI, or related field

 + 5+ years of experience in Python and software development for AI/ML or cloud applications

 + 3+ years of experience in Machine Learning/Data Science (model training, evaluation, deployment)

 + 2+ years of experience with LLMs/Generative AI (prompt engineering, RAG, embeddings, vector databases)

 + Strong expertise in prompt engineering and enterprise prompt design patterns

 + Strong understanding of agentic AI patterns and orchestration frameworks

 + Experience with AWS services for AI/ML application development and deployment

 + Hands-on experience with Terraform and/or Scalr

 + Experience with APIs, microservices, and containerized deployments

 + Experience with SQL, NoSQL, vector databases, and data integration

 + Strong software engineering fundamentals (version control, testing, CI/CD, secure coding)

 + Experience presenting technical solutions to stakeholders

 + Strong problem-solving, communication, and collaboration skills

## Description

We are seeking a highly skilled AI Engineer to design, develop, and deploy enterprise-scale AI solutions that solve complex business problems. This role focuses on Generative AI, Large Language Models (LLMs), Prompt Engineering, Agentic AI systems, Machine Learning, Data Science, and AWS-based cloud engineering.

The ideal candidate will have hands-on experience building intelligent applications end-to-end, including data preparation, model development, prompt optimization, agentic workflow orchestration, deployment automation, infrastructure provisioning, monitoring, and production support. This role involves close collaboration with business stakeholders and technical teams to drive scalable and secure AI adoption.

Key Responsibilities

 + Design, develop, and deploy enterprise AI solutions using LLMs, prompt engineering, agentic AI frameworks, and machine learning techniques

 + Build intelligent applications such as RAG systems, AI copilots, conversational assistants, agent workflows, and NLP-driven solutions

 + Design and optimize prompts, including templates, chaining strategies, structured outputs, and response optimization

 + Develop and maintain data pipelines for structured and unstructured data supporting AI workflows

 + Implement retrieval pipelines, embeddings, vector search, orchestration logic, and memory strategies

 + Fine-tune, evaluate, and monitor AI/ML models for performance, scalability, reliability, and cost efficiency

 + Collaborate with stakeholders to translate business requirements into AI solutions

 + Build and manage AI infrastructure on AWS using services such as S3, Lambda, EKS/ECS, API Gateway, IAM, CloudWatch, RDS, DynamoDB, OpenSearch, and Bedrock

 + Provision infrastructure using Terraform/Scalr for secure and scalable deployments

 + Implement monitoring, observability, evaluation, and guardrails for AI systems

 + Partner with architecture, platform, DevOps, and governance teams to ensure compliance and operational standards

 + Lead technical design discussions, code reviews, and architectural decisions

 + Support MLOps/LLMOps practices including CI/CD, versioning, testing, and deployment automation

 + Communicate technical insights, risks, and business impact to stakeholders

 + Mentor junior engineers and contribute to reusable frameworks and standards


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