AI Engineer (Only on W2)

We are seeking a highly skilled Applied AI Engineer with deep expertise in modern AI frameworks and workflows. You will design, develop, and deploy advanced AI models and intelligent systems, focusing on Trace Evaluation, Spec-Based Development, Language Model Evaluation, Graph DB, and AWS Knowledge Base integration. As a hands-on technical leader, you will collaborate with cross-functional teams to deliver enterprise-grade Gen AI solutions.

Bachelor’s degree in Computer Science, Data Science, AI/ML, or related technical field (Master’s preferred).

Advanced proficiency in Python, big data technologies (e.g., Spark, Hadoop), and data manipulation libraries (e.g., Pandas, NumPy).

Solid knowledge of classical ML algorithms, deep learning architectures, LLMs, generative AI, and reinforcement learning.

Hands-on experience with Microsoft Azure, Azure OpenAI, and AWS cloud platforms.

Strong understanding of Spec-Based Development, Git, and CI/CD best practices.

Expertise in prompt engineering, vector databases (AWS KnowledgeBase/Elastic), and multimodal models.

Proven experience with cloud-native AI development (AWS SageMaker, Bedrock, MLFlow on EKS).

Strong programming skills in Python and ML libraries (Transformers, LangChain, etc.).

Deep understanding of GenAI architectural patterns and Evaluation Frameworks (DeepEval).

Demonstrated ability to work in cross-functional agile teams.

Github Code Repository Link required for each candidate. Thorough vetting is mandatory.

Preferred Qualifications:

Experience in financial, regulatory technology, or enterprise automation.

Familiarity with MLOps tools (MLflow, Kubeflow, Weights & Biases).

Contributions to open-source AI projects or research publications.

Experience with containerization and orchestration (Docker, Kubernetes).

Experience with Spark is optional but preferred.