Forward Deployed AI Engineer

Vibehackers; India; On-site; INR 1,800,000 - 4,000,000; Full time

Job summary

Vibehackers invites a Forward Deployed AI Engineer to collaborate with enterprise clients to design, build, deploy, and scale production-grade AI solutions featuring Generative AI, Agentic AI, LLMs/SLMs, and RAG.

You will bridge business needs and engineering, deliver AI-powered applications, intelligent automation, and modern AI platforms, while guiding customers through PoCs, deployments, and workshops.

Qualifications

• Senior-level software/AI engineering experience with enterprise deployments.
• Proficient Python development and API design.
• Hands-on experience with LLMs, agent systems, and RAG pipelines.
• Experience in client-facing roles and Agile environments.

Responsibilities

• Design, develop, and deploy enterprise AI solutions with Generative AI, Agentic AI, LLMs/SLMs, and RAG.
• Work directly with customers to translate business problems into scalable AI solutions.
• Develop AI-powered applications for conversational AI, intelligent automation, and AI-assisted SDLC.
• Build production-ready AI workflows using platforms such as LangGraph, LangChain, CrewAI, AWS Bedrock, Azure AI Foundry, and Google Gemini Enterprise.
• Design agent orchestration frameworks integrating enterprise systems, APIs, databases, and external tools.
• Optimize AI solutions for accuracy, latency, scalability, reliability, and cost efficiency.
• Build robust APIs, microservices, and AI services following software engineering best practices.
• Collaborate across Product, Engineering, Data Science, and DevOps; participate in customer workshops, PoCs, technical discussions, and deployments.
• Evaluate emerging AI technologies and contribute to continuous improvement.

Skills

Python

LLMs/Agentic AI

Generative AI

RAG

Prompt Engineering

AI Agents

Agile / DevOps

Tools

LangGraph

LangChain

CrewAI

LlamaIndex

Docker

Kubernetes

AWS Bedrock

Azure AI Foundry

Google Gemini Enterprise

Job description

Uses agentic and generative AI platforms (LangChain, LangGraph, CrewAI) to build production AI workflows and developer-facing AI services; focused on building AI dev tools and integrations.

About the Role

Client-facing Forward Deployed AI Engineer who designs, builds, and deploys production-grade generative and agentic AI solutions for enterprise customers, bridging business requirements and engineering to scale AI-powered applications and automation.

Job Description

Role

A Forward Deployed AI Engineer responsible for partnering with enterprise customers to design, build, deploy, and scale production-grade AI solutions focused on Generative AI, Agentic AI, LLMs/SLMs, and RAG. The role acts as a bridge between business stakeholders and engineering teams to deliver AI-powered applications, intelligent automation, and modern AI platforms.

Key Responsibilities

• Design, develop, and deploy enterprise AI solutions leveraging Generative AI, Agentic AI, LLMs/SLMs, and RAG.
• Work directly with customers to understand business problems and translate them into scalable AI solutions.
• Develop AI-powered applications for conversational AI, intelligent automation, and AI-assisted SDLC.
• Build production-ready AI workflows using platforms such as LangGraph, CrewAI, LangChain, Azure AI Foundry, AWS Bedrock, and Google Gemini Enterprise.
• Design agent orchestration frameworks integrating enterprise systems, APIs, databases, and external tools.
• Optimize AI solutions for accuracy, latency, scalability, reliability, and cost efficiency.
• Build robust APIs, microservices, and AI services following software engineering best practices.
• Collaborate across Product, Engineering, Data Science, and DevOps; participate in customer workshops, PoCs, technical discussions, and deployments.
• Evaluate emerging AI technologies and contribute to continuous improvement.

Requirements

• Senior-level experience in Software Engineering, AI Engineering, or Machine Learning (posting lists “713 years” of experience; interpreted as senior/multiple years).
• Strong programming expertise in Python.
• Hands-on experience with LLMs, Agentic AI, Generative AI, RAG, Prompt Engineering, and AI Agents.
• Experience with orchestration frameworks such as LangGraph, LangChain, CrewAI, LlamaIndex, or similar.
• Familiarity with AI platforms like AWS Bedrock, Azure AI Foundry, and Google Gemini Enterprise.
• Experience with PyTorch, TensorFlow, and Hugging Face or other modern AI frameworks.
• Understanding of vector databases, embeddings, semantic search, and AI workflows.
• Experience with Docker, Kubernetes, REST APIs, CI/CD, and cloud platforms (AWS, Azure, or GCP).
• Strong communication skills and experience working directly with enterprise clients.
• Experience working in Agile development environments.

Preferred Skills

• Experience with MLOps/LLMOps and AI deployment frameworks.
• Exposure to PEFT, LoRA, QLoRA, or model optimization techniques.
• Knowledge of distributed computing and enterprise AI infrastructure.

Skills