Senior Engineering Consultant

verizon

Hyderabad 6 Years Exp Posted 1h ago

Design scalable, enterprise-grade architecture for AI/ML systems, Generative AI models, and autonomous multi-agent frameworks (e.g., LangGraph, CrewAI, AutoGen).
Define standards for Model Context Protocol (MCP), RAG architectures, prompt engineering, and LLM fine-tuning/evaluation.
Assess technical feasibility, select model architectures, and define data pipelines for complex, structured, and unstructured datasets.

Programmatically integrate state-of-the-art LLM APIs (e.g., OpenAI, Anthropic Claude, Google Gemini) into enterprise workflows.
Develop, train, and validate statistical models, optimization algorithms, and machine learning pipelines using Python, R, or C++.
Implement MLOps, AI observability, and tracing tools to monitor model drift, token usage efficiency, latency, and system performance in production.

Act as a trusted technical advisor to cross-functional leaders, product managers, and external clients.
Translate unstructured business problems into actionable mathematical and computational models.
Communicate complex technical concepts, model outputs, and risk assessments to both technical teams and non-technical business executives.

Champion enterprise AI safety, ethical AI, data governance, and secure coding practices.
Mentor junior AI engineers and data scientists on modern development workflows, including the effective leverage of AI coding assistants (e.g., GitHub Copilot, Cursor).

Languages & Frameworks: Fluent in Python, SQL, and Deep Learning frameworks (PyTorch, TensorFlow).
Generative AI & Agentic AI: Hands-on experience with orchestration frameworks (LangChain, LlamaIndex, LangGraph), vector databases (Pinecone, Qdrant, Milvus), and agentic workflows.
Cloud & Infrastructure: Cloud AI platforms (AWS Bedrock/SageMaker, GCP Vertex AI, or Azure OpenAI/AI Foundry).
- MLOps & Deployment: Experience with Docker, Kubernetes, CI/CD for AI models, MLflow, and API integration (REST, gRPC).