AWS AI Engineer

Hudson Manpower offers a competitive base salary plus a robust benefits package, including medical, dental, and vision coverage, optional life and disability insurance, a 401(k) with company match and potential profit sharing, paid vacation, paid bench time, a training allowance, and referral bonuses. This role is based in Harrisburg, PA with remote work options, supporting a security‑conscious enterprise environment focused on scalable AI solutions.

Benefits

• Competitive base salary
• Medical, dental, and vision insurance
• Optional life and disability insurance
• 401(k) with company match and optional profit sharing
• Paid vacation time
• Paid bench time
• Training allowance
• Referral bonuses

Responsibilities

• Operate hands-on with AWS services such as Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3 to implement scalable cloud solutions.
• Drive the end-to-end implementation of AWS cloud services spanning infrastructure, machine learning workloads, and AI platform services for enterprise-scale automation and governance.
• Develop LLM driven applications, including retrieval augmented generation pipelines built with LangChain and related tooling.
• Design and build cloud-native microservices, APIs, and serverless components to enable intelligent automation and real-time data processing.
• Partner with internal stakeholders to interpret business goals and translate them into secure, scalable AI solutions.
• Own the software release lifecycle, including CI/CD pipelines, GitHub-based SDLC practices, and infrastructure as code using Terraform.
• Contribute to the evolution of reusable platform components for AI/ML operations and workflows.
• Produce and maintain technical documentation for the team and internal customers.
• Demonstrate strong written and spoken English communication skills.

Requirements

• Seven or more years of hands-on software engineering experience with a strong emphasis on Python.
• Experience with AWS services, notably Bedrock or SageMaker.
• Hands-on experience fine-tuning large language models or building datasets and deploying ML models to production.
• Experience with AWS Organizations and policy guardrails, including SCPs and AWS Config.
• Proven ability to implement retrieval-augmented generation architectures using LangChain and related frameworks.
• Strong background in infrastructure as code and building Terraform modules for AWS cloud.
• Solid Git-based version control, code reviews, and DevOps workflows.
• Track record of delivering production-ready software with release pipeline integration.
• AWS or other cloud certifications.
• Policy as code development experience, such as Terraform Sentinel.
• Experience with Hugging Face, and either Node.js or Golang.
• Exposure to FinOps and cloud cost optimization.
• Data science background or experience working with structured and unstructured data.
• Awareness of data privacy and compliance best practices, including PII handling and secure model deployment.