Role: Senior AI Engineer

Location: Princeton, NJ- Onsite

Full Time Job

Experience Required: 5+ Years Relevant Experience

About the Role

We are seeking a highly skilled and experienced AI Engineer to join our growing team. The ideal candidate will have strong expertise in designing, developing, and deploying AI solutions, with hands-on experience in Generative AI, Large Language Models (LLMs), machine learning frameworks, and cloud-based AI platforms. This role requires collaboration with cross-functional teams and alignment with stakeholders.

Key Responsibilities

Design, develop, and deploy AI solutions for business-critical applications.
Build and optimize Generative AI applications using Large Language Models (LLMs).
Develop and maintain end-to-end machine learning pipelines, including data preprocessing, model training, evaluation, and deployment.
Fine-tune and customize foundation models for specific business use cases.
Implement Retrieval-Augmented Generation (RAG) architectures and vector database solutions.
Integrate AI solutions with existing enterprise applications and APIs.
Monitor model performance, troubleshoot issues, and continuously improve AI systems.
Collaborate with product, engineering, and business teams to translate requirements into scalable AI solutions.
Stay updated with emerging AI technologies, frameworks, and industry best practices.
Ensure adherence to security, compliance, and responsible AI standards.

Required Skills & Qualifications

Bachelor's or Master's degree in Computer Science with major in Artificial Intelligence, Data Science, or a related field.
5+ years of hands-on experience in AI/ML engineering and solution development.
Strong proficiency in Python and AI/ML libraries such as TensorFlow, PyTorch, Scikit-learn, and Hugging Face.
Experience working with Large Language Models (OpenAI, Claude, Llama, Gemini, etc.).
Hands-on experience with RAG frameworks, vector databases (Pinecone, Weaviate, Chroma, FAISS, etc.), and prompt engineering.
Experience with LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks.
Knowledge of cloud platforms such as AWS, Azure, or GCP and their AI services.
Experience building and deploying scalable AI applications using Docker, Kubernetes, and CI/CD pipelines.
Familiarity with REST APIs, microservices architecture, and software engineering best practices.
Strong understanding of data structures, algorithms, and system design principles.
Excellent problem-solving, communication, and stakeholder management skills.

Preferred Qualifications

Experience with AI agents, autonomous workflows, and multi-agent systems.
Exposure to MLOps tools and frameworks.
Experience in enterprise AI deployments and production-grade systems.
Knowledge of model evaluation, AI governance, and responsible AI practices.
Experience working with distributed teams and US-based clients.

What We Offer

Opportunity to work on cutting-edge AI and Generative AI initiatives.
Exposure to global clients and challenging business problems.
Collaborative and innovation-driven work environment.
Career growth opportunities in a rapidly evolving AI ecosystem.

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