AI Engineer II

Share job

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world.

NEXT is the research and incubation arm of Microsoft Security AI (MSECAI), building the next generation of AI native security products, and we're looking to hire an AI Engineer II. In the 18 months since our founding, we’ve driven the science behind Microsoft Security Copilot and delivered both foundational and specialized models. We pursue long horizon bets while landing near term impact, taking ideas from 0→1 prototypes to MVPs and then 1→N platform integration across Defender, Sentinel, Entra, Intune, and Purview. Our culture blends ambition and scientific rigor with curiosity, humility, and customer obsession; we invest in new knowledge, collaborate across world class scientists and engineers, and tackle the immense challenge of protecting millions of customers.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Required/minimum qualifications:

• Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • OR equivalent experience.
• Proficiency in C#/.NET and Python, API/microservice design, testing, and code quality practices
• Experience building on Azure, including but not limited to AKS, Container Apps, Functions, or App Service; plus Storage/Cosmos/SQL/ADX, Service Bus/Event Hubs, Key Vault, Managed Identity; basic networking
• Experience with distributed systems fundamentals: concurrency, messaging, resilience patterns, performance, and telemetry/observability
• Experience with CI/CD and infrastructure-as-code experience (GitHub Actions/Azure DevOps; Docker/Kubernetes; Bicep/Terraform)
• 2+ years working with Machine Learning (ML)/Artificial Intelligence (AI) systems (e.g., Large Language Models (LLMs)/Generative AI (GenAI), retrieval/Retrieval-Augmented Generation (RAG), model serving, experimentation platforms, data pipelines) including establishing evaluation metrics and improving model quality.

Other Requirements
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:

Microsoft Cloud Background Check:
- This position will be required to pass the Microsoft background and Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Additional or preferred qualifications:

• Security domain exposure (SIEM/SOAR/XDR/EDR, incident response, threat intel) and KQL/Azure Data Explorer
• Agentic AI in production: tool orchestration, permissions/policy checks, and human-in-the-loop approval workflows
• Vector search and data pipelines: Azure AI Search, Cosmos DB vector, Postgres+pgvector; Spark/Synapse/Data Factory; streaming ETL
• Observability depth: SLOs, OpenTelemetry tracing, cost/latency/error budgeting; A/B and canary strategies; incident response and postmortems
• Performance tuning for inference (batching, caching, model hosting/quantization) and multi-tenant, multi-region services
• Track record shipping SDKs/libraries and shared platform components used by other teams What makes a great AI Engineer here
• End-to-end owner: you build it, you run it—from prototype to reliable production service
• Security-first and responsible AI by default: privacy, safety, and compliance built into designs and code
• Pragmatic builder: chooses the simplest approach that meets reliability and safety bars; automates where it matters
• Data-driven and curious: instruments metrics, runs experiments, and iterates quickly based on evidence
• Collaborative communicator: clear designs/docs, thoughtful code reviews, and a habit of raising the engineering bar

Software Engineering IC3 - The typical base pay range for this role across the U.S. is USD $100,600 - $199,000 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $131,400 - $215,400 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

Microsoft will accept applications for the role until September 22, 2025.

#MSFTSecurity #MSECAI #AI #PrincipalTPM #TechnicalProgramManager #SecurityAI #GenerativeAI #Cybersecurity #ResponsibleAI #Azure

• Design, build, and operate AI-powered cloud services and APIs in Azure using C#/.NET and Python (AKS, Container Apps, Functions, App Service)
• Implement LLM/RAG/agentic workflows: retrieval, grounding, function/tool calling, and safe automation for investigation and remediation with human-in-the-loop controls
• Build data and indexing pipelines: embeddings, vector search (Azure AI Search, Cosmos DB vector, Postgres+pgvector), and connectors to Microsoft security data (Defender, Sentinel) and ADX/Kusto
• Add evaluation, safety, and observability: golden datasets, automated regressions, prompt/response guardrails and content filters, prompt-injection/jailbreak defenses, metrics/dashboards/alerts
• Optimize inference and service performance/cost: batching, caching, streaming, model selection/routing, multi-region deployment, and fallback strategies
• Ship securely: threat modeling, least-privilege access, Managed Identity/Key Vault, encryption, data minimization, consent/policy enforcement, and audit logging
• Own CI/CD and IaC: GitHub Actions or Azure DevOps; Docker/Kubernetes; Bicep/Terraform; canary/ring deployments, safe rollbacks; participate in on-call and improve SLOs
• Contribute to reusable SDKs/services for RAG, agent runtime, and tool/action APIs; write high-quality documentation and conduct code/design reviews
• Collaborate with researchers, PMs, and partner teams to translate scenarios into production features with clear KPIs (precision/recall, MTTD/MTTR, latency, cost)