• Develop applications to include user interfaces, workflows, and APIs supporting DHS geospatial systems. • Design, build, and maintain applications that integrate with geospatial data platforms, databases, and enterprise systems. • Support development and maintenance of geospatial applications across cloud and on-premise environments. • Develop and maintain scripts and automated workflows to support data processing, validation, and integration. • Support integration of geospatial data services, including REST-based services and APIs. • Collaborate with cross-functional teams to translate mission and business requirements into technical solutions. • Perform testing, debugging, and troubleshooting to ensure application performance, reliability, and scalability. • Participate in system design, development, and implementation activities across the software development lifecycle. • Support deployment, configuration, and maintenance of geospatial applications and tools. • Ensure compliance with DHS standards, security requirements, and system architecture guidelines. • Contribute to documentation including system design, development processes, and application functionality.

We are looking for a Senior AI/GenAI Engineer with strong hands-on experience building and deploying production-grade AI solutions on Azure. This role is responsible for designing end-to-end AI architectures, leading technical decisions, and translating business needs into scalable, reliable, and secure GenAI systems. You will work closely with cross-functional teams to deliver AI-powered solutions (copilots, AI agents, RAG pipelines) that support both internal operations and client-facing services. Responsibilities - Design, build, and deploy production-grade GenAI solutions (AI agents, copilots, RAG pipelines) with a focus on scalability, reliability, and performance - Own end-to-end architecture of AI systems on Azure, including integration with enterprise data platforms and backend services - Lead the development of LLM-powered applications using Azure-native services and modern orchestration frameworks - Implement LLMOps practices, including monitoring, logging, evaluation, prompt/version management, and cost optimization - Translate business requirements into technical AI solutions and define scalable implementation strategies - Ensure security, governance, and compliance across all AI solutions - Optimize AI systems for latency, cost, and accuracy in production environments - Provide technical leadership, mentor engineers, and drive best practices in system design and code quality

We are looking for a Senior AI/GenAI Engineer with strong hands-on experience building and deploying production-grade AI solutions on Azure. This role is responsible for designing end-to-end AI architectures, leading technical decisions, and translating business needs into scalable, reliable, and secure GenAI systems. You will work closely with cross-functional teams to deliver AI-powered solutions (copilots, AI agents, RAG pipelines) that support both internal operations and client-facing services. Responsibilities - Design, build, and deploy production-grade GenAI solutions (AI agents, copilots, RAG pipelines) with a focus on scalability, reliability, and performance - Own end-to-end architecture of AI systems on Azure, including integration with enterprise data platforms and backend services - Lead the development of LLM-powered applications using Azure-native services and modern orchestration frameworks - Implement LLMOps practices, including monitoring, logging, evaluation, prompt/version management, and cost optimization - Translate business requirements into technical AI solutions and define scalable implementation strategies - Ensure security, governance, and compliance across all AI solutions - Optimize AI systems for latency, cost, and accuracy in production environments - Provide technical leadership, mentor engineers, and drive best practices in system design and code quality

We are looking for a Senior AI/GenAI Engineer with strong hands-on experience building and deploying production-grade AI solutions on Azure. This role is responsible for designing end-to-end AI architectures, leading technical decisions, and translating business needs into scalable, reliable, and secure GenAI systems. You will work closely with cross-functional teams to deliver AI-powered solutions (copilots, AI agents, RAG pipelines) that support both internal operations and client-facing services. Responsibilities - Design, build, and deploy production-grade GenAI solutions (AI agents, copilots, RAG pipelines) with a focus on scalability, reliability, and performance - Own end-to-end architecture of AI systems on Azure, including integration with enterprise data platforms and backend services - Lead the development of LLM-powered applications using Azure-native services and modern orchestration frameworks - Implement LLMOps practices, including monitoring, logging, evaluation, prompt/version management, and cost optimization - Translate business requirements into technical AI solutions and define scalable implementation strategies - Ensure security, governance, and compliance across all AI solutions - Optimize AI systems for latency, cost, and accuracy in production environments - Provide technical leadership, mentor engineers, and drive best practices in system design and code quality