Artificial Intelligence Engineer

Daman; Austin (TX); Hybrid; USD 120,000 - 150,000; Full time

Job summary

A leading tech company is looking for an experienced AI Engineer to design and scale machine learning solutions. You will work with AWS SageMaker and Amazon Bedrock. The ideal candidate will have a degree in Computer Science or related field along with 5+ years of experience in AI/ML engineering. This is a hybrid position based in Austin, TX, offering a long-term contract. Ideal candidates should have solid programming skills in Python and familiarity with MLOps practices, aimed at creating secure AI applications.

Qualifications

• 5+ years of experience in AI/ML engineering or applied machine learning.
• Strong hands-on experience with AWS SageMaker including training jobs and endpoints.
• Proven experience working with Amazon Bedrock for Generative AI use cases.

Responsibilities

• Design, develop, and deploy machine learning and generative AI models.
• Build and integrate Generative AI applications using Amazon Bedrock.
• Optimize model performance, scalability, and cost on AWS.

Skills

AWS SageMaker

Amazon Bedrock

Python

Machine Learning

MLOps

NLP

Deep Learning

Education

Bachelor’s or Master’s degree in Computer Science, AI, Data Science

Tools

Docker

Kubernetes

PyTorch

TensorFlow

scikit-learn

AWS S3

AWS Lambda

AWS API Gateway

AWS EC2

AWS CloudWatch

Job description

AI Engineer

Location: Hybrid – Austin, TX (3 Days in office)

Job Type: Long-term Contract

We are seeking an experienced AI Engineer with strong hands‑on expertise in AWS SageMaker and Amazon Bedrock to design, develop, deploy, and scale machine learning and generative AI solutions. The ideal candidate will work closely with data scientists, cloud engineers, and business stakeholders to build secure, production‑grade AI systems on AWS.

Key Responsibilities

• Design, develop, and deploy machine learning and generative AI models using AWS SageMaker.
• Build and integrate Generative AI applications using Amazon Bedrock (Claude, Titan, Llama, etc.).
• Develop end‑to‑end ML pipelines including data ingestion, training, tuning, deployment, and monitoring.
• Implement model inference, batch processing, and real‑time endpoints using SageMaker.
• Optimize model performance, scalability, and cost on AWS.
• Apply MLOps best practices including CI/CD, model versioning, monitoring, and retraining.
• Integrate AI/ML services with backend systems, APIs, and microservices.
• Ensure security, compliance, and governance using AWS IAM, encryption, and logging.
• Collaborate with cross‑functional teams to translate business requirements into AI solutions.
• Stay current with AWS AI/ML service updates and emerging GenAI best practices.

Required Skills & Qualifications

• Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related field.
• 5+ years of experience in AI/ML engineering or applied machine learning.
• Strong hands‑on experience with AWS SageMaker (training jobs, endpoints, pipelines).
• Proven experience working with Amazon Bedrock for Generative AI use cases.
• Proficiency in Python and ML libraries (PyTorch, TensorFlow, scikit‑learn).
• Experience with LLMs, prompt engineering, embeddings, and RAG architectures.
• Strong understanding of ML algorithms, deep learning, and NLP.
• Experience with AWS services such as S3, Lambda, API Gateway, EC2, ECR, CloudWatch.
• Knowledge of containerization and orchestration (Docker, Kubernetes preferred).
• Familiarity with MLOps tools and practices.

Seniority Level

Mid‑Senior level

Employment Type

Contract

Job Function

Information Technology

Industries

IT Services and IT Consulting