Forward Deployed Engineer – Advanced AI Systems

Position Overview

We are seeking a highly skilled and dynamic Forward Deployed Engineer (FDE) – Advanced AI Systems to bridge the gap between cutting-edge AI engineering and enterprise-scale production deployment. In this individual contributor role, you will work closely with stakeholders to design, build, deploy, and productionize advanced AI solutions, including Large Language Models (LLMs), Agentic workflows, and robust Retrieval-Augmented Generation (RAG) pipelines.

The ideal candidate possesses a strong blend of AI/ML expertise, solid full-stack software engineering fundamentals, DevOps discipline, and exceptional communication skills to drive successful project delivery.

Key Responsibilities

AI Engineering & Architecture

Advanced AI Development: Design, develop, and optimize robust AI solutions using production-grade Python.

LLM & RAG Integration: Implement, fine-tune, and orchestrate Large Language Models (LLMs) alongside advanced Retrieval-Augmented Generation (RAG) pipelines to ensure high-accuracy contextual outputs.

Agentic AI Frameworks: Build autonomous and semi-autonomous systems leveraging modern Agentic AI frameworks and multi-agent implementations.

Deployment & Full-Stack Software Engineering

AI Productionization: Take prototypes and scale them into production-ready, enterprise-grade AI products, ensuring reliability, low latency, and scalability.

Full-Stack Development: Write clean, modular, and testable code across the full application stack to build end-to-end user-facing AI applications.

DevOps & MLOps: Set up, maintain, and automate robust CI/CD pipelines and follow rigorous DevOps practices to ensure seamless software delivery and model monitoring.

Stakeholder Delivery & Collaboration

Project Delivery: Act as the technical spearhead on client/internal engagements, ensuring the successful end-to-end delivery of complex AI/ML solutions.

Stakeholder Management: Translate complex technical concepts into clear, actionable business insights for both internal leadership and external stakeholders.

Required Technical Skills & Qualifications

Experience: 5+ years of hands-on software engineering, with a strong focus on deploying AI/ML solutions at scale.

Programming: Strong, undisputed core proficiency in Python.

AI/ML Domain: Hands-on experience with LLM APIs, vector databases, embeddings, and prompt engineering. Proven experience deploying RAG systems.

Agentic AI: Familiarity with or hands-on experience implementing frameworks such as LangChain, CrewAI, AutoGen, or similar advanced orchestrators.

Full-Stack & Cloud: Solid grounding in full-stack architecture, API development (FastAPI/Flask), front-end integration, and cloud infrastructure.

DevOps/MLOps: Practical experience with Git, Docker, Kubernetes, CI/CD tools (e.g., Jenkins, GitHub Actions), and automated testing frameworks.