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# AI Foundation Model Engineer

- **Company:** Niche IT Software Solutions LLC
- **Location:** Jersey City, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Continuous Integration, Data Security, Monitoring of Systems, Python (Programming Language), Machine Learning, Open Source Technology, Tensorflow, Runbook, Search Technologies, Software Deployment, Enterprise Software Applications, Cloud Platform System, Pytorch, Large Language Models, Model Validation, Build Management, AI Platforms, Kubernetes, HuggingFace, Machine Learning Operations, Terraform, Docker, Databricks
- **Published:** July 30, 2026
- **Apply:** https://www.dice.com/job-detail/e2bdc246-288c-4cb8-8d54-39cb900ee675

## About the Role

· Strong hands-on experience with LLMs, transformers, GenAI, RAG, embeddings and vector databases.

· Advanced Python skills and experience with PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, Semantic Kernel or similar frameworks.

· Production deployment experience using APIs, containers, Kubernetes, CI/CD and monitoring tools.

· Practical AWS AI/cloud experience, preferably with Bedrock, SageMaker, OpenSearch, Lambda and EKS/ECS.

· Working knowledge of Terraform/IaC, MLOps/LLMOps, model evaluation, inference optimization and secure data handling.

Preferred Experience

· Banking, risk, compliance, financial crime or enterprise technology experience.

· Experience with Kendra, Azure OpenAI, Vertex AI, Databricks, vLLM, Triton, MLflow, Kubeflow or model gateways.

· Knowledge of LoRA, PEFT, instruction tuning, quantization, model governance and private/open-source LLM deployments.

Alternate Titles: LLM Engineer, GenAI Engineer, AI Platform Engineer, RAG Engineer, Applied ML Engineer or NLP Engineer.

## Description

We are seeking a Senior AI Foundation Model Engineer to build and deploy secure, scalable, enterprise-grade AI solutions using LLMs, RAG and agentic workflows. The role involves developing production AI applications and reusable services for an AWS-hosted, cloud-agnostic AI platform., · Build LLM applications, RAG pipelines, knowledge assistants, document intelligence solutions and workflow agents.

· Develop embeddings, semantic search, reranking, grounding and citation capabilities.

· Deploy and manage AI services using APIs, Docker, Kubernetes, CI/CD and cloud-native infrastructure.

· Collaborate on Terraform/IaC, environment promotion, release controls and rollback procedures.

· Optimize models and inference for accuracy, latency, throughput, token usage, reliability and cost.

· Implement LLMOps/MLOps covering evaluation, monitoring, observability, feedback loops and continuous improvement.

· Ensure security, privacy, Responsible AI, governance and audit readiness.

· Maintain production documentation, runbooks and release records.


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