Job Description: Forward Deployed Engineer (Agentic AI)

Experience: 15+ Years
Location: 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
- Contemporary 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.

📌 Forward Deployed Engineer (Bengaluru)
🏢 Tech Mahindra
📍 Bengaluru