Forward Deployed Engineer (Agentic AI)

Job Description: Forward Deployed Engineer (Agentic AI)

Experience: 15+ Years
Location: Bangalore, Work from office
Role Type: Individual Contributor / Technical Leadership

Role Overview

We are seeking a highly experienced Forward Deployed Engineer (FDE) to work directly with client stakeholders, business teams, and enterprise architects to identify AI transformation opportunities and deliver production-grade Agentic AI solutions.

This role combines solution consulting, enterprise architecture, hands-on development, and technical delivery ownership. The ideal candidate will partner with client teams to understand current technology landscapes, analyze existing implementations, and design and build AI-powered solutions that seamlessly integrate with existing enterprise systems using MCP (Model Context Protocol) servers, Agentic AI frameworks, MuleSoft APIs, Azure Cloud, Spring AI, and React-based applications.

The candidate will own the complete lifecycle from discovery and architecture through development, deployment, and production rollout.

Key Responsibilities

Client Engagement & Solution Discovery

• Work closely with client business and technology teams to understand current architecture, applications, APIs, workflows, integrations, and operational challenges.
• Conduct discovery workshops to identify AI and automation opportunities.
• Translate business requirements into scalable AI solution architectures.
• Act as the primary technical advisor for enterprise AI transformation initiatives.

Architecture & Solution Design

• Design end-to-end Agentic AI solutions aligned with enterprise architecture standards.
• Architect AI ecosystems leveraging LLMs, RAG, MCP Servers, vector stores, enterprise APIs, and cloud-native services.
• Define integration patterns between AI agents and existing enterprise systems.
• Establish security, governance, observability, scalability, and performance standards.

Agentic AI & MCP Implementation

• Design and build autonomous and multi-agent systems using modern Agentic AI frameworks.
• Develop and integrate MCP Servers to securely connect AI agents with enterprise tools, APIs, databases, and knowledge repositories.
• Build AI orchestration workflows involving task planning, tool usage, reasoning, and execution.
• Implement human-in-the-loop workflows and AI governance mechanisms.

Enterprise Integration

• Leverage MuleSoft API Management Platform for enterprise-grade integrations.
• Design and implement reusable APIs and integration services.
• Connect AI solutions with CRM, ERP, document repositories, workflow systems, and third-party platforms.
• Define API security, authentication, and authorization mechanisms.

Full Stack Development

• Lead hands-on development activities across backend, frontend, and cloud platforms.
• Build AI-enabled microservices using Spring Boot and Spring AI.
• Develop intuitive React-based applications and AI copilots.
• Implement scalable cloud-native architectures on Azure.

Delivery Ownership

• Own end-to-end technical delivery from architecture through production deployment.
• Lead technical design reviews and code reviews.
• Mentor engineering teams and establish engineering best practices.
• Drive DevOps, CI/CD, testing, deployment, monitoring, and support readiness.

Required Technical Skills

AI & Agentic AI

• Enterprise GenAI and Agentic AI solution design.
• Multi-Agent Systems.
• AI Orchestration Frameworks.
• RAG Architecture.
• Prompt Engineering.
• Vector Databases.
• Agent Governance and Observability.
• MCP (Model Context Protocol) Server Development and Integration.

Backend Technologies

• Java 17+
• Spring Boot
• Spring AI
• Microservices Architecture
• REST APIs
• Event-Driven Architecture
• API Security

Frontend Technologies

• React JS
• TypeScript
• Modern UI Frameworks
• State Management Libraries

Integration Technologies

• MuleSoft Anypoint Platform
• API Management
• API Gateway
• Enterprise Integrations
• OAuth2/JWT/SAML

Cloud & DevOps

• Microsoft Azure
• Azure OpenAI
• Azure AI Services
• Azure Kubernetes Service (AKS)
• Azure Functions
• Azure API Management
• Docker
• Kubernetes
• GitHub Actions / Azure DevOps

Data & AI Infrastructure

• Azure AI Search
• Vector Databases
• SQL / NoSQL Databases
• Knowledge Graphs
• Enterprise Knowledge Platforms

Desired Experience

• 15+ years of enterprise software engineering and architecture experience.
• 5+ years designing cloud-native enterprise platforms.
• 3+ years delivering Generative AI or Agentic AI solutions.
• Proven experience engaging directly with C-Level executives, business stakeholders, and enterprise architects.
• Experience in BFSI, Wealth Management, Capital Markets, or Financial Services environments is highly preferred.
• Experience modernizing legacy applications and integrating AI capabilities into existing ecosystems.

Key Success Metrics

• Successful AI adoption and business value realization.
• Production deployment of enterprise-grade Agentic AI solutions.
• Reduction in manual effort through intelligent automation.
• Scalable and secure integration of AI with enterprise systems.
• High stakeholder satisfaction and measurable business outcomes.