Senior AI/ML Engineer

Key Responsibilities

Design and architect scalable, secure, and high-performing AI/ML solutions utilizing Agentic AI frameworks, Agent-to-Agent (A2A) architectures, and Model Context Protocol (MCP).

Lead the development of enterprise Generative AI applications, including Retrieval-Augmented Generation (RAG), vector search, embeddings, prompt engineering, and context engineering.

Architect and deploy AI/ML workloads on Microsoft Azure, ensuring scalability, security, performance, and cost optimization.

Design and optimize data architectures leveraging Azure AI Search, Cosmos DB, Redis, Blob Storage, and Iceberg-based data platforms.

Develop and manage cloud-native services using Azure Functions, Azure Container Apps, and distributed microservices architectures.

Define best practices for system reliability, observability, scalability, and performance optimization.

Ensure AI solutions comply with healthcare and data privacy regulations, including HIPAA, GDPR, and other applicable compliance standards.

Provide technical leadership through architecture reviews, code reviews, mentoring, and engineering best practices.

Collaborate with cross-functional teams, including product, compliance, security, and operations stakeholders.

Research emerging AI technologies and evaluate innovative approaches to enhance enterprise AI capabilities.

Required Qualifications

Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.

8+ years of software engineering experience, including significant experience in AI/ML and Generative AI solution development.

Strong expertise in:

Generative AI, LLMs, and Natural Language Models (NLMs)

Multi-agent systems and Agentic AI architectures

MCP Protocol and agent orchestration frameworks

Vector embeddings, prompt engineering, context engineering, and LLM fine-tuning

Advanced proficiency in Python and experience developing production-grade AI applications.

Hands-on experience with Microsoft Azure services for AI and cloud-native application deployment.

Strong knowledge of Azure AI Search, Redis, Cosmos DB, and distributed data storage solutions.

Experience designing microservices, serverless applications, and scalable cloud-native architectures.

Knowledge of AI security, governance, and compliance requirements within regulated industries.

Excellent problem-solving, communication, and stakeholder management skills.

Proven experience mentoring engineers and leading technical initiatives.

Preferred Qualifications

Master’s degree in Computer Science, AI/ML, Data Science, or a related field.

Microsoft Azure certifications such as:

Azure Solutions Architect Expert

Azure AI Engineer Associate

Experience with frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen, or similar AI orchestration platforms.

Experience implementing MLOps, LLMOps, and CI/CD pipelines for AI workloads.

Healthcare industry experience with regulated data environments and compliance frameworks.

Contributions to open-source AI projects, technical publications, patents, or industry presentations