Ops SRE Support Engineer VLabs - Manager

Company Description

Vialto Partners is a market leader in Global Mobility Services. Our purpose is to “Connect the World.” We are unique and the only stand-alone global mobility business. This presents a rare opportunity for our clients, stakeholders and colleagues.

Our teams help companies streamline and effectively manage their global mobility programs in a cost-efficient and compliant manner. Our services focus on providing cross-border compliance and risk assessment for tax, immigration, business travel, rewards and compensation, and remote work.

Working at Vialto Partners is about getting the chance to be part of a global and dynamic team. Globally, Vialto Partners has over 8,000 staff worldwide and continues to grow. You will work with clients from a range of industries and different geographical locations. We believe in connecting the world and supporting our colleagues to do the same in their careers by undertaking assignments and opportunities globally that broaden their skills and ultimately benefit our clients.

About Vialto Labs (VLabs)

Vialto Labs (VLabs) is responsible for redesigning how work is delivered in the tax and immigration service lines, as well as driving operational efficiency across Vialto’s functional areas using AI. The team builds and deploys novel AI-enabled solutions that directly improve productivity and increase delivery quality for our clients. VLabs is accountable for rapidly turning innovative experiments into production-ready deliverables at scale and embedding them into day-to-day operations. This team focuses on the highest-impact workflows, creating standardized, repeatable capabilities that can be deployed globally. Operating with a mandate for speed and measurable outcomes, VLabs works alongside service line, product, and platform leaders.

About The Role

We are seeking an experienced AI Architect to lead the design, development, and governance of enterprise-grade AI and AIOps solutions across cloud-native environments. This role will define the architecture for Generative AI, agentic systems, and intelligent operations platforms on Microsoft Azure, ensuring scalability, reliability, security, and responsible AI adoption.

The ideal candidate combines deep expertise in GenAI, Agentic Harness, Agentic Engineering, AI/ML systems, distributed architectures, observability, and cloud engineering, with hands-on experience building production-grade GenAI and AIOps solutions. You will play a critical role in shaping AI strategy, establishing architectural standards, and enabling teams to deliver high-impact, enterprise AI capabilities. You will be able to think at system and platform level, not just application level, translate complex AI capabilities into scalable enterprise solutions whilst balancing innovation with reliability, security, and governance.

Key Responsibilities

AI & Solution Architecture

• Define end-to-end architecture for Generative AI, agentic systems, and AIOps platforms
• Design scalable, secure, and resilient AI systems across cloud and hybrid environments
• Establish reference architectures, design patterns, and best practices for AI systems
  
  

• Architect multi-agent systems, orchestration workflows, and tool integration frameworks
• Define patterns for RAG, retrieval pipelines, and knowledge integration
• Design evaluation frameworks, guardrails, and Responsible AI controls
• Guide implementation of agent frameworks and workflow orchestration
• Design patterns for implementation with Agentic Harness
  
  

• Architect intelligent operations platforms leveraging logs, metrics, traces, and events
• Define strategies for anomaly detection, alert correlation, and automated remediation
• Establish observability standards using Open Telemetry (OTEL) and modern monitoring tools like Tempo, Loki, Prometheus, Grafana, etc.
  
  

• Lead architecture for AI solutions on Microsoft Azure
• Design cloud-native systems using containers (Docker, Kubernetes)
• Define data architecture across PostgreSQL, Cosmos DB, SQL Server, and telemetry pipelines
  
  

• Guide teams on backend architecture using Python and FastAPI
• Define CI/CD, DevOps, and automation strategies using ADO and GitHub
• Establish standards for testing, evaluation, and performance optimization of AI systems
  
  

• Define enterprise standards for AI security, privacy, and compliance
• Implement Responsible AI practices including:
• Prompt safety
• Data protection
• Access control
• Model governance
• Ensure auditability and reliability of AI-driven systems
  
  

• Drive improvements in MTTR, MTTD, reliability, and operational efficiency
• Define SLIs, SLOs, and error budgets for AI-powered services
• Architect automation for incident response and root-cause analysis
  
  

• Partner with SRE, platform, data, and application teams
• Mentor engineers and guide architectural decision-making
• Influence AI strategy and roadmap across the organization
• Apply strong communication and stakeholder management skills
  
  

• 10+ years of experience in software engineering, cloud architecture, or platform engineering
• 3+ years designing and delivering AI/ML or GenAI systems in production
• Strong expertise in Python and backend system design
• Experience architecting solutions on Microsoft Azure
• Deep understanding of:
• Distributed systems
• Cloud-native architecture
• Observability and SRE principles
• Experience with Docker, Kubernetes, and microservices architecture
• Strong experience with APIs, service design, and system integration
• Experience designing agentic AI systems and orchestration frameworks
• Experience with evaluation frameworks and AI system quality measurement
• Strong understanding of AIOps, telemetry pipelines, and operational intelligence
• Experience with logs, metrics, traces, and event correlation
• Expertise in secure AI system design and governance
• Experience with CI/CD, DevOps, and automation practices
  
  

• Experience with:
• Azure AI services, Azure Monitor, and observability platforms
• Open Telemetry instrumentation, Tempo, Grafana,
• Evals with Arize Phoenix
• RAG, vector databases, and retrieval systems
• Multi-agent systems and advanced orchestration
• Familiarity with:
• MCP, tool calling, plugins, and reusable agent capabilities
• OCR, document intelligence, and unstructured data processing
• Experience with KQL, SQL, or analytics query languages
• Exposure to GenAI-assisted development workflows