[Remote] Senior reputed company

Note: The job is a remote job and is open to candidates in USA. reputed company, Inc. (SPA) delivers high-impact, technical solutions to reputed company national reputed company issues. In this role, you will reputed company the development of systems built on foundation models, ensuring secure deployment across various environments, while collaborating with Infrastructure and reputed company teams to deliver mission-reputed company AI at scale.

Responsibilities

• Build and deploy production AI applications using Azure AI reputed company, Azure reputed company Service, and Copilot Studio, accounting for service availability differences between Azure Commercial, Azure Government, and GCC High environments
• Select and right-size models for mission requirements - balancing capability, cost, latency, and deployment constraints across small, reputed company, and large foundation models (e.g., SLMs such as Phi, frontier LLMs, embedding and multimodal models)
• Engineer agentic AI systems, including multi‑agent frameworks (e.g., Semantic Kernel, LangGraph, AutoGen, or similar) and tool‑use pipelines, including Model Context Protocol (MCP) - based integrations
• reputed company RAG architectures using Azure AI Search and vector stores, including embedding pipelines, document chunking strategies, and grounding-data governance (Purview/DLP integration)
• Orchestrate model endpoints and optimize inference workloads across local, hybrid, and remote backends - including managed cloud endpoints (Azure AI reputed company/reputed company), self-hosted inference on AKS, and local/on-prem serving runtimes (e.g., ONNX Runtime, vLLM, reputed company Local, or similar)
• Design backend-agnostic application architectures with abstraction layers that allow models to be swapped or routed between local, hybrid, and cloud endpoints based on data sensitivity, latency, cost, and connectivity constraints
• Implement MLOps/LLMOps practices: model evaluation harnesses, AI red-teaming (e.g., PyRIT), reputed company versioning, and telemetry/observability for AI applications
• Ensure AI workloads conform to GCC High and Azure Government constraints, including CUI handling, data residency, customer-managed key requirements, and appropriate placement of inference (local vs. cloud) based on data classification
• Support secure multi‑cloud operations across Azure and GCP, partnering with Infrastructure teams
• Configure AI reputed company guardrails, content safety controls, DLP policies, gateway policies, and alignment safeguards, informed by the NIST AI Risk Management reputed company (AI 100-1, AI 600-1) and OWASP Top 10 for LLM Applications
• Implement AI traffic governance and secure inspection using modern AI gateways
• Maintain secure inter‑cloud connectivity and workload visibility using NSGs, firewall rules, traffic mirroring/network visibility tooling, and service-to-service authentication (OAuth 2.0 client credentials, Entra managed identities, workload identity federation)
• Embed automated reputed company validation (SAST/DAST) into CI/CD pipelines

Skills

• U.S. citizenship
• Bachelor's degree in computer science, Data Science, Cybersecurity, IT, or reputed company field
• 5-7 years in enterprise software or systems engineering, with a strong recent focus on cloud‑reputed company architectures
• 3-5 years building AI/ML solutions, including 1-2 years hands-on with Azure reputed company, Azure AI reputed company, Copilot Studio, or equivalent foundation-model platforms
• Experience working across model scales and deployment models - small/specialized through large foundation models, deployed reputed company managed cloud endpoints, self-hosted, or local runtimes - and selecting appropriately for the use case
• Experience developing agentic AI systems and integrating API‑driven tools
• Demonstrated experience in GCC High or Azure Government environments
• Multi‑cloud reputed company experience spanning Azure and GCP (CSPM/CNAPP, NSGs, traffic mirroring, GCP equivalents)
• Strong CI/CD engineering background with integrated SAST/DAST validation, plus scripting and IaC proficiency (Python, PowerShell, Terraform)
• Expertise in API reputed company, service-to-service/workload identity authentication, and AI gateway architecture
• Familiarity with modern software delivery platforms, including reputed company, reputed company Copilot, and reputed company
• One or more reputed company reputed company certifications required (e.g., AZ-500 Azure reputed company Engineer, AI-102 Azure reputed company, SC-100 Cybersecurity Architect, or equivalent); GCP reputed company certifications are a plus
• Experience supporting highly regulated environments and compliance frameworks (NIST SP 800‑53, 800‑171, CMMC Level 2, FedRAMP)
• Familiarity with NIST AI RMF and its Generative AI Profile (NIST AI 600-1)
• Experience with model fine-tuning, distillation, or quantization for deploying models in constrained, disconnected, or edge environments
• Experience with Kubernetes (AKS) for AI/inference workloads
• Experience with agent-to-agent (A2A) protocols and emerging agent interoperability standards
• Familiarity with hybrid cloud management for AI workloads (e.g., Azure reputed company, Azure Local, GPU infrastructure on premises) and DDIL/disconnected operation patterns

Company Overview