Senior Forward Deployment Engineer_AI

Senior Forward Deployment Engineer Azure Agentic AI

Locations: Noida, Hyderabad, Chennai, Bengaluru, Pune
Experience:4-12 Years
Required AI Experience: Minimum 2 years in Generative AI / Agentic AI
Employment Type: Full-Time

Job Summary

We are looking for a Senior Forward Deployment Engineer to lead the design, development and deployment of enterprise Generative AI and Agentic AI solutions on Microsoft Azure.

The candidate will work directly with enterprise customers, lead technical discussions, design solution architectures, guide development teams and ensure AI solutions are secure, scalable, reliable and production-ready.

The role requires strong hands-on coding skills, Azure cloud architecture expertise, AI engineering knowledge, customer-facing technical leadership and experience delivering enterprise solutions into production.

Key Responsibilities

• Lead the complete delivery of enterprise Agentic AI solutions, from requirement gathering and architecture design to production deployment and operational handover.
• Conduct customer meetings, technical workshops, architecture reviews, demonstrations, POCs and pilot projects.
• Design AI solutions using Microsoft Foundry, Foundry Agent Service, Azure OpenAI and other Azure services.
• Design multi-agent architectures, including orchestration, planning, domain agents, tools, skills, RAG and human approval workflows.
• Integrate AI solutions with REST APIs, Microsoft Graph, databases, ITSM platforms, identity systems, monitoring tools and enterprise applications.
• Decide whether customer requirements should be handled through configuration, custom development or reusable platform features.
• Design production deployment architectures using Azure Container Apps, AKS, Azure Functions, API Management, Service Bus, Event Grid, Azure Storage and Azure AI Search.
• Ensure solutions meet requirements for security, scalability, availability, performance, reliability and disaster recovery.
• Design security and identity controls using Microsoft Entra ID, RBAC, managed identities, authentication, authorization and Key Vault.
• Define production readiness standards covering functionality, performance, security, evaluation, monitoring and operational support.
• Establish AgentOps practices for logging, tracing, telemetry, evaluation, quality monitoring and cost tracking.
• Troubleshoot complex production issues involving AI agents, LLMs, RAG, APIs, authentication, networking and Azure infrastructure.
• Optimize application reliability, response time, scalability, model performance and AI costs.
• Define and review CI/CD pipelines, release management, version control, rollback and deployment processes.
• Review technical designs, code, integration solutions and deployment plans prepared by engineering teams.
• Mentor and guide Forward Deployment Engineers and Associate Engineers.
• Develop reusable architecture patterns, integration solutions, deployment guides, runbooks and troubleshooting processes.
• Work with Product, Platform Engineering, Security, Cloud Architecture and Operations teams to improve platform capabilities.
• Lead technical escalations, customer enablement, operational handover and transition to support teams.

Required Technical Skills

• Strong programming skills in Python and experience reviewing production-quality code.
• Hands-on experience with Generative AI, LLMs, RAG, prompt engineering, tool calling and multi-agent architectures.
• Production experience with Microsoft Foundry / Foundry Agent Service, Azure OpenAI, and/or LangGraph/LangChain.
• Strong knowledge of Microsoft Azure architecture and Azure AI services.
• Experience integrating enterprise applications using REST APIs, Microsoft Graph, databases and ITSM platforms.
• Strong understanding of Microsoft Entra ID, OAuth, managed identities, RBAC, authentication, authorization and secrets management.
• Experience with Docker, containerized applications, Azure Container Apps and AKS.
• Knowledge of CI/CD, Git, release management, versioning and production operations.
• Experience with logging, monitoring, tracing, debugging, AI evaluation and production incident management.
• Strong understanding of RAG architecture, data retrieval, knowledge integration and agent quality evaluation.
• Knowledge of Responsible AI, guardrails, AI security, data protection and enterprise governance.
• Strong communication skills and the ability to lead technical discussions with senior customer stakeholders.

Preferred Skills

• Microsoft Foundry, Foundry Agent Service, Azure OpenAI and Azure AI Search.
• Azure Monitor, Application Insights, Agent Framework and Generative AI evaluation.
• OpenTelemetry, AgentOps and AI evaluation practices.
• MCP, A2A and Microsoft Graph.
• Terraform, Infrastructure as Code and Azure landing zones.
• Azure Container Apps, AKS, API Management, Service Bus, Event Grid, Storage, Key Vault and Cosmos DB.
• Enterprise networking, private endpoints and secure connectivity.
• ServiceNow, ITSM, CloudOps, SRE, AIOps and infrastructure automation.
• Experience designing secure, scalable and highly available production systems.
• Experience delivering POCs, pilots, MVPs and enterprise production rollouts.
• Exposure to multiple cloud platforms is an advantage.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Information Technology or a related field.
• 812 years of overall software engineering, cloud engineering, solution architecture or equivalent technical experience.
• Minimum 3 years of practical Generative AI / Agentic AI experience.
• Proven experience delivering enterprise technology or AI solutions into production.
• Experience leading customer-facing technical engagements and owning solution architecture.

Key Attributes

• Strong customer-facing communication and relationship-building skills.
• Ability to take ownership of technical delivery and business outcomes.
• Excellent architecture, analytical and problem-solving skills.
• Ability to work across AI engineering, Azure architecture, integrations, security and operations.
• Ability to balance reusable platform solutions with customer-specific requirements.
• Strong mentoring and technical leadership skills.