Senior AI Engineer

Title: Sr. AI Engineer
Location: Pittsburgh, PA or New York, NY (4 Days onsite, 1 Day Remote)
Duration: 6+ months of contract on W2 (possibility of an extension)
Job Description:
We are seeking a Senior AI Engineer with strong experience in AI/ML, Generative AI, and banking domain. The ideal candidate will design and develop AI/ML solutions, build Generative AI applications, and work with large-scale data ecosystems.

Key Responsibilities:
Design and develop AI/ML solutions using supervised, unsupervised, deep learning, NLP, time series forecasting, and anomaly detection.
Build Generative AI applications leveraging LLMs, prompt engineering, fine-tuning, Retrieval-Augmented Generation (RAG), and AI agent frameworks.
Develop and maintain end-to-end AI pipelines: data ingestion, preprocessing, model training, deployment, monitoring, and continuous improvement.
Work with large-scale data ecosystems including ETL, data lakes, data warehouses, streaming platforms, and tools like Spark, Databricks, or Microsoft Fabric.
Implement MLOps best practices: CI/CD pipelines, model governance, explainability, monitoring, Docker-based containerization, and Kubernetes orchestration.
Deploy AI models through APIs and microservices, ensuring seamless integration with enterprise applications, systems, and cloud platforms.
Utilize cloud-based AI services on Azure or AWS, including Azure Machine Learning and Amazon SageMaker.
Collaborate with business and technology stakeholders to translate business requirements into scalable AI solutions.

Required Skills:
5+ years of relevant AI/ML experience; 10+ years overall.
Strong programming in Python and SQL.
Hands-on experience with ML libraries: Scikit-learn, TensorFlow, PyTorch, Hugging Face, SpaCy, NLTK.
Experience with Generative AI: LLMs, prompt engineering, fine-tuning, RAG, AI agent frameworks.
Banking domain experience (mandatory).
MLOps: CI/CD, model governance, explainability, monitoring, Docker, Kubernetes.
Cloud AI: Azure ML, AWS SageMaker.
Experience deploying AI models via APIs/microservices.

Nice to Have:
Java Spring Boot, Angular.
LangChain / Semantic Kernel orchestration.
Knowledge graphs, synthetic data, AI copilots.

Additional Details:
This is a hybrid role – 4 days onsite per week.
Candidates must be authorized to work in the US without sponsorship ( or ).
Interviews will be virtual.

If you are a strong AI/ML engineer with banking domain experience and are open to a hybrid onsite role, please apply with your updated resume.

How to Apply:
Please send your updated resume and best time for a call. We look forward to connecting!