Description

Own the end-to-end delivery of enterprise GenAI and Agentic AI solutions, from data preparation and model refinement to production deployment and governance.

This role is on-site.

Responsibilities

• Build and refine complex analytics and AI models, including LLM-based solutions, forecasting, and custom non-ML algorithms using SAS, R, and Python.
• Design and implement scalable, production-ready architectures for GenAI applications, ensuring robustness, reliability, and risk awareness.
• Define and enforce quality frameworks, optimization standards, and monitoring strategies for model accuracy, stability, and compliance.
• Develop reusable customizations, IP assets, and accelerators for ML, deep learning, and LLM workflows while mentoring team members.
• Collaborate with cross-functional teams to align analytics delivery with business strategy, presenting insights and driving continuous improvement.

Required Skills

• 5+ years of experience building enterprise GenAI and Agentic AI solutions, including RAG, AI agents, conversational AI, and enterprise search.
• Hands-on expertise with orchestration frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI) and vector databases (Pinecone, Weaviate, Milvus, pgvector, FAISS, ChromaDB, Azure AI Search).
• Strong proficiency in Python, SAS, and data extraction from diverse environments for advanced modeling.
• Experience integrating GenAI with cloud platforms (Azure OpenAI, AWS Bedrock, Vertex AI, OpenAI, Anthropic, Gemini) and enterprise APIs.
• Command of AI governance, LLMOps, evaluation, observability, guardrails, model safety, and cloud-native deployment.
• Proficiency with CI/CD tools (Github Actions, Jenkins), infrastructure as code (Terraform), and containerization (Helm, Kubernetes).
• Ability to define reference architectures, lead solutioning discussions, and collaborate with enterprise architects and stakeholders.
• Bachelor's degree in a relevant technical field.

Preferred Skills

• Exposure to open-source LLM ecosystems (Hugging Face, PyTorch, LoRA, QLoRA, PEFT) and model fine-tuning.
• Experience with frontend frameworks (React, Angular, Typescript) for building AI-driven user interfaces.

Key Skills

Education

Bachelor's degree