Forward Deployed AI Engineer

Straive; Chennai; Vor Ort; INR 900.000 - 1.500.000; Vollzeit

Zusammenfassung

Straive in Chennai, India, seeks an FDE to rapidly prototype, build, and deploy custom agentic workflows, RAG systems, and integrations into client environments, including Claude skills/tools and modern full-stack solutions.

You will be a hands-on developer, technical architect, and strategic communicator, leading client-facing discovery sessions, architecting solutions, and connecting LLM pipelines with legacy databases and enterprise software.

Aufgaben

• Technical Solution Delivery: Architect, build, and deploy production-ready AI solutions and modern full-stack integrations tailored to client needs.
• Rapid Prototyping: Turn ambiguous client requirements into working PoCs and transition to production-grade codebases.
• Technical Discovery & Architecture: Lead client-facing discovery sessions to map requirements and design integration strategies.
• Full-Stack & API Integration: Connect LLMs and AI pipelines with legacy databases, APIs, and enterprise software.
• Stakeholder Engagement: Act as the technical point of contact, presenting solutions and trade-offs to engineering teams and executives.

Jobbeschreibung

As an FDE, you will rapidly prototype, build, and deploy custom agentic workflows, RAG systems, and integrations directly into client environments. You are equal parts hands-on developer, technical architect, and strategic communicator.

Key Responsibilities

• Technical Solution Delivery: Architect, build, and deploy production-ready AI solutions, custom agentic workflows, Claude skills/tools, and modern full-stack integrations tailored to client needs.
• Rapid Prototyping: Rapidly turn ambiguous, raw client requirements into working proof-of-concepts (PoCs) and transition them into scalable, production-grade codebases.
• Technical Discovery & Architecture: Lead client-facing discovery sessions to map out technical requirements, evaluate customer system landscapes, and design integration strategies.
• Full-Stack & API Integration: Connect modern Large Language Models (LLMs) and custom AI pipelines with legacy customer databases, APIs, and enterprise software systems.
• Stakeholder Engagement: Act as the technical point of contact, presenting solutions, demonstrating product capability, and communicating technical trade-offs to both engineering teams and executive stakeholders.