AI Engineer

Persistent Systems•New York, NY

12d

About The Position

Persistent Systems is looking for an AI Engineer to design, build, and deploy secure AI applications that help employees find information, automate work, analyze data, and make better decisions. You'll work closely with business and technical teams to turn ideas into reliable AI solutions using modern generative AI, retrieval-augmented generation (RAG), and agent-based technologies. This role covers the full software development lifecycle—from planning and prototyping to deployment, monitoring, and ongoing improvements. We're looking for someone who enjoys solving real business problems, understands both the opportunities and limitations of AI, and can explain technical concepts to both technical and non-technical audiences.

Requirements

2–5 years of experience in software engineering, machine learning, data engineering, or AI engineering
Bachelor’s degree in computer science, engineering, data science, mathematics, or a related field (or equivalent experience)
Strong Python programming skills
Experience building generative AI applications using LangChain, LangGraph, or similar frameworks
Experience with RAG systems, prompt engineering, and AI application development
Experience using at least one major AI platform such as Azure AI Foundry, AWS Bedrock, Google Vertex AI, or Databricks
Familiarity with SQL and enterprise data systems
Strong communication and problem-solving skills
Ability to obtain or hold a U.S. Security Clearance

Nice To Haves

Experience with multiple AI frameworks, cloud platforms, or agent SDKs
Experience deploying open-source models with Hugging Face or Ollama
Familiarity with FastAPI, Docker, Kubernetes, MLflow, and MLOps/LLMOps
Experience evaluating and monitoring AI systems in production
Knowledge of Power BI, Tableau, Microsoft Copilot Studio, or Power Platform
Data engineering experience with Azure Data Factory, AWS Glue, or Databricks
Experience with deep learning (PyTorch or TensorFlow) and traditional machine learning (scikit-learn, XGBoost)
Experience working in regulated or security-sensitive environments
Microsoft Azure AI certifications (AI-103, AI-200, AI-300)
AWS Certified Generative AI Developer – Professional
Google Cloud Professional Machine Learning Engineer
Databricks Certified Generative AI Engineer Associate

Responsibilities

Design, build, test, deploy, and maintain AI-powered applications
Develop RAG systems, AI agents, and conversational AI solutions
Work with business, engineering, IT, security, and data teams to identify AI use cases and deliver production-ready solutions
Build secure data ingestion, retrieval, and search pipelines
Evaluate AI models, frameworks, SDKs, and cloud services based on performance, cost, security, and business needs
Develop Python APIs and services using tools like FastAPI, Docker, and Kubernetes
Implement AI safety, security, governance, and monitoring practices
Create evaluation frameworks to measure AI quality, accuracy, latency, cost, and reliability
Connect AI solutions to enterprise databases and analytics platforms
Document solutions, mentor teammates, review code, and promote engineering best practices