AI Engineer

Job Description – AI Engineer (US)

Job Title: AI Engineer

Location: United States (Onsite/Hybrid/Remote)

Experience: 3–8+ Years

Employment Type: Full-Time

Job Summary

We are looking for a talented AI Engineer to design, develop, and deploy AI-powered solutions that solve complex business challenges. The ideal candidate should have hands-on experience in machine learning, deep learning, Generative AI, and Large Language Models (LLMs), along with strong software engineering skills to build scalable AI applications.

Key Responsibilities

Design, develop, and deploy AI/ML models for production environments.

Build and optimize Generative AI and LLM-based applications.

Develop Retrieval-Augmented Generation (RAG) pipelines using vector databases.

Fine-tune foundation models for domain-specific use cases.

Develop AI agents and workflow automation solutions.

Build REST APIs and integrate AI models into enterprise applications.

Collaborate with product managers, data scientists, and software engineers.

Monitor model performance, optimize inference, and ensure scalability.

Implement MLOps best practices for model deployment and monitoring.

Stay updated with the latest AI research and emerging technologies.

Required Technical Skills

Programming Languages

Python (Expert)

SQL

Java or C++ (Preferred)

Artificial Intelligence & Machine Learning

Machine Learning

Deep Learning

Neural Networks

Supervised & Unsupervised Learning

Reinforcement Learning (Preferred)

Generative AI

Large Language Models (LLMs)

Prompt Engineering

Fine-tuning LLMs

Retrieval-Augmented Generation (RAG)

AI Agents

Function Calling

Multi-Agent Systems

Frameworks & Libraries

PyTorch

TensorFlow

Scikit-learn

Hugging Face Transformers

LangChain

LlamaIndex

OpenAI SDK

DSPy (Preferred)

LLM Models

GPT Models

Llama

Claude

Gemini

Mistral

Vector Databases

Pinecone

Weaviate

ChromaDB

FAISS

Milvus

Cloud Platforms

AWS (SageMaker, Bedrock)

Microsoft Azure AI

Google Cloud Vertex AI

MLOps & Deployment

Docker

Kubernetes

MLflow

Kubeflow

GitHub Actions

CI/CD Pipelines

Databases

PostgreSQL

MongoDB

Redis

API Development

FastAPI

Flask

REST APIs

GraphQL (Preferred)

Data Engineering

Pandas

NumPy

Apache Spark (Preferred)

ETL Pipelines

DevOps & Version Control

Git

GitHub

Jenkins

Terraform (Preferred)

Required Qualifications

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.

3–8+ years of experience in AI/ML development.

Strong experience deploying AI models into production.

Experience with cloud-based AI services (AWS, Azure, or GCP).

Knowledge of software engineering best practices and scalable architecture.

Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications

Experience building enterprise AI copilots or AI assistants.

Experience with multimodal AI (text, image, audio).

Knowledge of NLP, computer vision, or speech AI.

Experience with distributed training and model optimization.

Familiarity with AI governance, security, and responsible AI practices.

Key Skills

Python

Machine Learning

Deep Learning

Generative AI

Large Language Models (LLMs)

Prompt Engineering

RAG

LangChain

LlamaIndex

Hugging Face

PyTorch

TensorFlow

FastAPI

Docker

Kubernetes

AWS / Azure / GCP

Vector Databases (Pinecone, FAISS, Weaviate, Milvus)

MLOps

Git

SQL

REST APIs

This JD aligns well with current AI Engineer hiring requirements across US technology companies, particularly for roles focused on Generative AI, enterprise AI applications, and production-grade LLM systems.