AI/ML Engineer

Triunity Software•Texas, TX

About The Position

Triunity Software is seeking an AI/ML Engineer to join its team in New Jersey and develop artificial intelligence and machine learning solutions. The role focuses on building, deploying, and supporting enterprise-grade LLM and Generative AI applications, including Retrieval-Augmented Generation (RAG) systems. The engineer will work on cloud-based services, APIs, data pipelines, and event-driven workers, while addressing production quality, observability, cost, security, and compliance needs. The position includes ownership and support of live AI applications, including incident management, root-cause analysis, regression management, and production enhancements. The role works in a fast-paced, innovative environment on client projects and with industry experts. Triunity describes its work as product development, staff augmentation, and consulting services for business sectors including healthcare, pharma, banking, and finance. Compensation is $100,000–$110,000 per year. The posting lists performance-based bonus, health insurance, and training and development benefits.

Requirements

At least 5 years of overall software engineering experience.
At least 2 years of hands-on LLM/Generative AI development experience.
Demonstrated experience deploying at least one enterprise-grade AI/LLM application into production.
Experience owning and supporting live AI applications, including incident management, root-cause analysis, regression management, and production enhancements.
Strong proficiency in Python 3.11 or later, including asynchronous programming, type annotations, and automated testing.
Hands-on experience with LLM/Generative AI application development.
Strong experience with RAG, embedding models, indexing strategies, and retrieval optimization.
Experience with at least one LLM orchestration framework: LangGraph, LangChain, LlamaIndex, Semantic Kernel, AutoGen, or Amazon Bedrock Agents.
Expertise in LLM evaluation methodologies, golden datasets, evaluation metrics, and LLM-as-a-judge techniques.
Experience developing cloud-based services, REST APIs, data pipelines, and event-driven workers.
Knowledge of AI observability, tracing, structured logging, quality monitoring, and cost optimization.
Exposure to enterprise security, compliance, and governance requirements.
Exposure to enterprise security and compliance reviews.

Nice To Haves

Experience with FastAPI, Pydantic, PostgreSQL, Aurora PostgreSQL, and vector extensions.
Experience with AgentCore and Agentic AI.
Experience with Kubernetes, Helm, Terraform, and CI/CD.
Experience with Apache Kafka and event-driven architecture.
Experience with Datadog and OpenTelemetry.
Experience with Document AI, OCR, intelligent document processing, and human-in-the-loop workflows.
Experience in financial services, insurance, healthcare, or other regulated industries.

Responsibilities

Develop LLM and Generative AI applications, including RAG solutions, embedding models, indexing strategies, and retrieval optimization.
Develop cloud-based services, REST APIs, data pipelines, and event-driven workers.
Evaluate LLM applications using evaluation methodologies, golden datasets, evaluation metrics, and LLM-as-a-judge techniques.
Monitor and optimize AI applications using observability, tracing, structured logging, quality monitoring, and cost optimization practices.
Deploy enterprise-grade AI/LLM applications to production.
Own and support live AI applications, including incident management, root-cause analysis, regression management, and production enhancements.
Address enterprise security, compliance, and governance requirements.