Automation Test Analyst

About Vialto Labs (VLabs)

Vialto Labs (VLabs)is responsible forredesigning how work is delivered in the tax and immigration service lines, as well as driving operational efficiency acrossVialto’sfunctional areas using AI. The team builds and deploys novel AI-enabled solutions that directly improve productivity and increase delivery quality for our clients.VLabsis 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,VLabsworks alongside serviceline,product, and platform leaders.

About the Role

We are seeking anexperienced 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 deepexpertisein 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,establishingarchitectural standards, and enabling teams to deliver high-impact, enterprise AI capabilities. You will be able to thinkatsystem and platform level, not just application level, translate complex AI capabilities into scalable enterprise solutionswhilst balancinginnovation 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

Agentic & GenAI 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

AIOps & Observability

• Architect intelligent operations platformsleveraginglogs, metrics, traces, and events

• Define strategies foranomaly detection, alert correlation, and automated remediation

• Establish observability standards usingOpenTelemetry(OTEL)and modern monitoring toolslikeTempo,Loki,Prometheus,Grafana, etc.

Cloud & Platform Engineering

• Lead architecture for AI solutions onMicrosoft Azure

• Design cloud-native systems usingcontainers (Docker, Kubernetes)

• Define data architecture acrossPostgreSQL, Cosmos DB, SQL Server, and telemetry pipelines

Engineering & Delivery Enablement

• Guide teams on backend architecture usingPython andFastAPI

• Define CI/CD, DevOps, and automation strategies using ADO and GitHub

• Establish standards for testing, evaluation, and performance optimization of AI systems

Security, Governance & Responsible AI

• Define enterprise standards forAI 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

Operational Excellence

• Driveimprovements 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

Leadership & Collaboration

• Partner with SRE, platform, data, and application teams

• Mentor engineers and guide architectural decision-making

• Influence AI strategy and roadmap across the organization

• Applystrong communicationand stakeholder management skills

Required Qualifications/ Background

• 10+ years of experience in software engineering, cloud architecture, or platform engineering

• 3+ years designing and delivering AI/ML or GenAI systems in production

• Strongexpertisein 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

• Expertisein secure AI system design and governance

• Experience with CI/CD, DevOps, and automation practices

PreferredQualifications/ Background

• Experience with:

• Azure AI services, Azure Monitor, and observability platforms

• OpenTelemetry instrumentation, Tempo, Grafana,

• Evals withArizePhoenix

• 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

Additional Information:

Location: Bangalore

We are an equal opportunity employer that does not discriminate on the basis of any legally protected status.

Please note, AI is used as part of the application process.