AWS AI Engineer

Hudson Manpower is seeking a Senior AWS AI Engineer to design and deploy production‑grade retrieval augmented generation (RAG) systems and AI/ML services on AWS. This remote‑friendly role, based in Temple, TX, delivers a competitive base salary, comprehensive health coverage, retirement savings with company match, and strong opportunities for professional growth. You will collaborate across teams to build secure, scalable AI solutions that power enterprise use cases, while benefiting from a culture that values hands‑on impact, clear communication, and continuous learning.

Benefits

• Competitive base salary
• Medical, dental, and vision insurance coverage
• Optional life and disability insurance
• 401(k) with company match and potential profit sharing
• Paid vacation time
• Paid bench time to explore innovation and learning
• Training allowance for ongoing skills development
• Referral bonuses

Responsibilities

• Contribute hands‑on expertise with AWS services such as Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3 to build and maintain AI workloads
• Lead the implementation of AWS cloud infrastructure, ML/AI platform services, and related components
• Develop and deploy LLM applications including Retrieval-Augmented Generation using LangChain and similar frameworks
• Design cloud‑native microservices, APIs, and serverless functions to enable intelligent automation and real‑time data processing
• Partner with internal stakeholders to translate business goals into secure, scalable AI systems
• Own the software release lifecycle, supporting CI/CD pipelines, GitHub SDLC practices, and infrastructure as code with Terraform
• Advance reusable platform components for AI/ML operations and streamline workflows
• Document technical decisions and produce clear references for teammates and internal customers
• Communicate effectively in English, with strong verbal and written skills

Requirements

• 7 years of hands‑on software engineering experience with a strong focus on Python
• Proficiency with AWS services, particularly Bedrock or SageMaker
• Experience fine‑tuning large language models or building datasets and deploying ML models to production
• Familiarity with AWS organizations and policy guardrails (SCP, AWS Config)
• Solid track record implementing RAG architectures and using LangChain
• Experience with Infrastructure as Code best practices and building Terraform modules for AWS
• Strong background in Git‑based version control, code reviews, and DevOps workflows
• Proven success delivering production‑ready software with integrated release pipelines

Technologies

• Python, Bedrock, SageMaker, Lambda, Step Functions, DynamoDB, S3, ECS
• LangChain, Transformers, PyTorch, TensorFlow
• Terraform, Terraform Sentinel, AWS Config, SCP (Service Control Policies)
• Git, GitHub, Hugging Face
• Node.js, Golang (Go)

Top Skills

• Must Have: Extensive experience with AWS services including Bedrock, SageMaker, ECS and Lambda; demonstrated ability to implement RAG architectures and work with ML tooling such as Transformers, PyTorch, TensorFlow, and LangChain; strong Infrastructure as Code discipline with Terraform modules for AWS
• Nice To Have: Cloud certifications, data privacy and compliance best practices (PII handling, secure model deployment), data science background or familiarity with structured and unstructured data, exposure to FinOps and cloud cost optimization, experience with Hugging Face and Node.js, policy as code development (Terraform Sentinel)