Senior AI/ML Engineer

Responsibilities

• Design, develop, and operate enterprise AI systems including Generative AI, Agentic AI, and intelligent automation workloads
• Lead the architecture and implementation of scalable backend systems for AI model serving, inference, and orchestration
• Build and enhance enterprise AI platforms supporting model development, deployment, evaluation, and governance
• Establish and manage end-to-end MLOps, LLMOps, and Agentic Ops practices, including automated CI/CD pipelines
• Design and implement Generative AI solutions using LLMs, Retrieval-Augmented Generation (RAG), and vector search
• Build Agentic AI systems capable of multi-step reasoning, tool usage, and multi-agent orchestration
• Develop high-performance, cloud-native backend applications using microservices and distributed architectures
• Establish observability frameworks for monitoring model performance, agent effectiveness, and operational telemetry
• Collaborate with cross-functional teams of scientists and engineers to establish technical standards and best practices

Requirements

• Bachelor's degree in Computer Science, Engineering, AI, Data Science, or a related field
• 12+ years of experience in software engineering, AI engineering, or backend systems development
• Proven experience implementing MLOps and LLMOps in enterprise production environments
• Hands-on experience with Large Language Models (LLMs), RAG, embeddings, and vector databases
• Proficiency in Python and modern backend development frameworks
• Experience developing cloud-native applications on Azure, AWS, or Google Cloud Platform
• Strong expertise in designing scalable distributed systems, APIs, and microservices
• Solid understanding of containerization, Kubernetes, and deployment automation

Preferred Qualifications

• Experience with AI orchestration frameworks such as LangChain, LangGraph, or LlamaIndex
• Experience building enterprise-scale AI platforms and reusable engineering frameworks
• Knowledge of distributed computing technologies like Kafka, Spark, or Databricks
• Experience in highly regulated industries such as healthcare or financial services
• Expertise in AI observability, prompt monitoring, and evaluation frameworks

Benefits

• Comprehensive health plans and wellness coverage for you and your loved ones
• Financial benefits including retirement planning support
• Emotional support resources to help manage stress and build resilience
• Opportunities for continuous professional development and career advancement