Forward Deployed Solution Engineer - Applied AI FDE

Vibehackers; Hyderabad, Ahmedabad District; On-site; INR 4,200,000 - 6,200,000; Full time

Job summary

Vibehackers seeks an experienced Forward Deployed Software Engineer to deliver AI-native GenAI solutions for enterprise customers. You’ll own end-to-end builds from backend services and LLM pipelines to front-end integrations, creating reusable tooling and reference implementations.

You will collaborate with customers in production environments, travel up to 30%, and drive patterns that accelerate enterprise AI adoption across platforms.

Qualifications

• 8+ years of software engineering experience with 2+ years in customer-facing or embedded roles.
• Strong backend and system architecture experience; production AI-native software.
• Proficiency across backend (Python, Node.js, Java), frontend (React, Angular), and APIs (REST/GraphQL).

Responsibilities

• Deliver production-grade, AI-native solutions in agile sprints.
• Build full-stack systems: APIs, orchestration pipelines, vector DB integrations, UI components.
• Work onsite with customers to adapt, deploy, and iterate solutions.
• Codify reusable assets (libraries, prompts, SDKs) for future engagements.
• Influence platform teams with field-tested insights and tooling improvements.
• Ensure performance, observability, security, and integration with legacy systems.

Skills

Full-stack development

Backend systems

LLM tooling

LangChain

Semantic Kernel

REST/GraphQL

Python

Node.js

React

Angular

Java

AWS

Azure

GCP

CI/CD

Distributed systems

Performance observability

SDK development

DevOps

Tools

LangChain

Semantic Kernel

REST/GraphQL

Docker

Kubernetes

AWS

CI/CD

Job description

Directly building production GenAI solutions and developer tooling using LLM frameworks (LangChain, Semantic Kernel) and vector search — clear vibe-coding and AI dev tools focus.

About the Role

Build and deliver production-grade, AI-native enterprise solutions as a Forward Deployed Software Engineer by embedding with customers, owning full-stack implementations from backend services and LLM pipelines to front-end integrations, and codifying reusable patterns and tooling to scale GenAI across the platform.

Job Description

Role

You will act as a Forward Deployed Software Engineer (Applied AI FDE) partnering deeply with strategic customers to design, implement, and deliver solution-ready GenAI applications. You will own end-to-end builds—backend services, LLM pipelines, data orchestration, and front-end integrations—and produce reference implementations and reusable assets that accelerate enterprise AI adoption.

Key Responsibilities

• Deliver production-ready AI-enabled solutions in agile, end-to-end sprints.
• Implement full-stack systems: APIs, orchestration pipelines, vector DB integrations, and UI components.
• Operate in the field alongside customers to adapt, deploy, and iterate solutions in live environments.
• Codify reusable assets (libraries, prompts, scaffolds, SDKs) to accelerate future engagements.
• Influence platform and product teams by feeding back field-tested insights and shaping developer experience.
• Integrate with legacy systems, ensure performance and observability, and ship resilient, secure systems.

Requirements

• 8+ years of software engineering experience, including 2+ years in customer-facing or embedded roles.
• Strong backend and system architecture experience; emphasis on production AI-native software.
• Engineering depth across backend (Python, Node.js, Java), frontend (React, Angular), and APIs (REST/GraphQL).
• Familiarity with LLM tooling and practices (LangChain, Semantic Kernel, prompt chaining, vector search, context management).
• Experience with performance observability, debugging distributed systems, and tuning for latency.
• DevOps fluency: deploying on AWS, Azure, or GCP with CI/CD, containers, and infrastructure-as-code.
• Platform mindset: experience contributing to shared SDKs, tools, and documentation to raise organizational velocity.
• Field readiness: able to travel up to 30% and embed onsite with customers.

Preferred Qualifications

• Experience integrating AI into SaaS platforms such as ServiceNow or Salesforce.
• Track record of production deployments in secure, regulated enterprise environments.
• Contributions to developer experience tooling, frameworks, or reusable AI scaffolds.

What Success Looks Like

• Solutions you ship convert to scaled, production deployments across customers.
• Reusable libraries, prompts, and scaffolds you author power multiple engagements.
• Your field experience influences platform roadmap and tooling, increasing engineering velocity.
• You deliver quickly and safely, producing resilient, secure systems trusted by architects and PMs.

Python Node.js Java React Angular REST GraphQL LangChain Semantic Kernel prompt chaining vector search context management vector DBs LLM frameworks AWS Azure GCP CI/CD containers infrastructure as code SDKs ServiceNow Salesforce

Skills

System Architecture Full-stack Development API Design Product-minded Engineering Systems Debugging Performance Observability DevOps Platform Thinking Customer Engagement Agile Delivery Documentation and SDK Development Integration with Legacy Systems