Senior Ai Platform Developer

Job title- Senior AI Platform Developer

Location- Hybrid - Woodlawn, MD (Local to the Area Required)

USC only

United States Citizen or Permanent Residents, with the ability to obtain a Public Trust**

Overview

Our client is looking for a Senior AI Platform Developer to design, develop, and support a secure, scalable, and governed Enterprise AI Gateway. The role focuses on integrating multiple LLM providers, building reusable AI services and Retrieval-Augmented Generation (RAG) solutions, and implementing enterprise security, Responsible AI, monitoring, and cost-management controls.

Description:

• Design, develop, and maintain enterprise AI gateway APIs, microservices, and shared AI platform capabilities.
• Integrate and orchestrate multiple LLM providers, AI platforms, and enterprise data sources.
• Build RAG solutions using embeddings, vector databases, and enterprise search.
• Develop reusable AI components, SDKs, and standardized integration patterns.
• Implement authentication, authorization, audit logging, data protection, and application security controls.
• Enforce AI governance, Responsible AI, compliance, and risk-management standards.
• Monitor platform performance, availability, usage, reliability, and operational costs.
• Build and maintain CI/CD pipelines and cloud-native deployments using Docker and Kubernetes.
• Troubleshoot production issues and optimize platform scalability, performance, and resilience.
• Collaborate with architecture, security, operations, and application teams to deliver enterprise AI capabilities.

Requirements:

• 5+ years of software engineering experience, including 2+ years developing AI, ML, or Generative AI solutions.
• Strong programming skills in Python, Java, C#, or TypeScript, with experience building REST APIs, microservices, and cloud-native enterprise applications.
• Knowledge of LLMs, prompt engineering, RAG, embeddings, vector databases, AI orchestration, and agentic AI frameworks.
• Experience with Azure or AWS cloud services, production deployments, and enterprise AI gateways, AI platforms, or shared AI services.
• Proficiency in Docker, Kubernetes, CI/CD pipelines, monitoring, logging, troubleshooting, and production support.
• Understanding of OAuth 2.0/OIDC, identity management, API security, and access controls.
• Familiarity with Responsible AI, AI governance, data privacy, and regulatory compliance.
• Experience supporting enterprise-scale or highly regulated environments.
• Strong analytical, problem-solving, communication, and cross-functional collaboration skills.
• Azure or AWS cloud, AI, or architecture certifications are preferred.