Mphasis is seeking a Senior AI Software Engineer to bridge enterprise customers and product engineering teams through the deployment and operationalization of AI-powered solutions. The role focuses on Azure AI platforms, agentic workflows, custom integrations, AI transformation enablement, platform observability, and executive communication.

Responsibilities:

Work directly with customer stakeholders to understand business challenges and identify AI transformation opportunities
Translate business requirements into technical solutions and implementation roadmaps
Conduct workshops, discovery sessions, architecture reviews, and solution demonstrations
Act as a trusted advisor to business and technology leadership
Lead deployment and adoption of Azure AI Platform capabilities
Configure and operationalize Azure OpenAI, AI Gateway, Agentic AI frameworks, and enterprise integrations
Build reusable accelerators, deployment patterns, and implementation playbooks
Support onboarding of business units and engineering teams
Develop custom integrations, APIs, workflows, and automation solutions
Build proof-of-concepts (PoCs), MVPs, and production-ready solutions
Integrate AI services with Jira, ServiceNow, GitLab, Azure DevOps, Confluence, and enterprise applications
Customize agentic workflows and orchestration frameworks to meet client-specific requirements
Drive adoption of AI-powered SDLC capabilities
Requirements-to-Code Automation
Test Automation
Developer Productivity Acceleration
Intelligent Incident Management
Knowledge Assistants and Copilots
AI-Driven Operations (AIOps)
Implement monitoring, observability, and operational excellence practices
Define KPIs and adoption metrics
Troubleshoot production platform issues and partner with engineering teams on remediation
Leverage AIOps capabilities to improve reliability, performance, and operational efficiency
Gather customer feedback and communicate requirements to product engineering teams
Identify gaps, enhancement opportunities, and platform scalability requirements
Contribute to product roadmap discussions and feature prioritization
Create reference architectures and best practices
Present solution architecture, adoption progress, ROI metrics, and transformation outcomes to customer leadership
Prepare executive-ready presentations, architecture documents, and implementation updates
Serve as a key liaison between customer stakeholders, engineering teams, and program leadership

Requirements:

8–15 Years
- Azure Cloud
- Azure OpenAI
- Azure AI Foundry
- Azure API Management
- Kubernetes / AKS
- Microservices Architecture
- REST APIs
- Python, C#, Java, or Node.js
- GitHub / GitLab
- CI/CD Pipelines
- Infrastructure as Code (Terraform, Bicep)
- Generative AI
- LLM Integration
- Prompt Engineering
- RAG Architectures
- AI Agents and Workflows
- MCP Concepts
- Vector Databases
- AI Governance
- Azure Monitor
- Application Insights
- OpenTelemetry
- Logging & Telemetry
- Incident Management
- Root Cause Analysis
- Automation & Self-Healing Concepts

Senior AI Software Engineer

Key skills

About this role

Responsibilities:

Requirements: