AWS Cloud Engineer – AI/ML, SageMaker

Title: AWS Cloud Engineer – AI/ML, SageMaker
Duration: 6+ Months
Location: Remote
KeySkills: AWS (Lambda, SageMaker, Bedrock, S3), AI/ML, Python, GoLang/ Node.js.

JOB DESCRIPTION:
We are hiring a Distinguished Cloud AI Software Engineer who has actually built AI/ML applications—not just read about them. You will operate as a trusted advisor in a hands-on capacity for the development of retrieval-augmented generation (RAG) systems, fine-tuning LLMs, and AWS-native microservices that drive automation, insight, and governance in an enterprise environment. You’ll design and deliver scalable, secure services that bring large language models into real operational use—connecting them to live infrastructure data, internal documentation, and system telemetry.

You’ll be part of a high-impact team pushing the boundaries of cloud-native AI in a real-world enterprise setting. This is not a prompt-engineering sandbox or a resume keyword trap. If you’ve merely dabbled in SageMaker, mentioned RAG on LinkedIn, or read about vector search—this isn’t the right fit. We’re looking for candidates who have architected, developed, and supported AI/ML services in production environments.

 DUTIES AND RESPONSIBILITIES:

• Design, develop, and maintain modular AI services on AWS using Lambda, SageMaker, Bedrock, S3, and related components—built for scale, governance, and cost-efficiency.
• Lead the end-to-end development of RAG pipelines that connect internal datasets (e.g., logs, S3 docs, structured records) to inference endpoints using vector embeddings.
• Design and fine-tune LLM-based applications, including Retrieval-Augmented Generation (RAG) using LangChain and other frameworks.
• Tune retrieval performance using semantic search techniques, proper metadata handling, and prompt injection patterns.
• Collaborate with internal stakeholders to understand business goals and translate them into secure, scalable AI systems.
• Own the software release lifecycle, including CI/CD pipelines, GitHub-based SDLC, and infrastructure as code (Terraform).
• Support the development and evolution of reusable platform components for AI/ML operations.
• Create and maintain technical documentation for the team to reference and share with our internal customers.
• Excellent verbal and written communication skills in English.

 REQUIRED KNOWLEDGE, SKILLS, AND ABILITIES:

• 10+ years of proven software engineering experience with a strong focus on Python and GoLang and/or Node.js.
• Demonstrated contributions to open-source AI/ML/Cloud projects, with either merged pull requests or public repos showing real usage (forks, stars, or clones).
• Direct, hands-on development of RAG, semantic search, or LLM-augmented applications, using frameworks and ML tooling like Transformers, PyTorch, TensorFlow, and LangChain—not just experimentation in a notebook.
• Ph.D. in AI/ML/Data Science and/or named inventor on pending or granted patents in machine learning or artificial intelligence.
• Deep expertise with AWS services, especially Bedrock, SageMaker, ECS, and Lambda.
• Proven experience fine-tuning large language models, building datasets, and deploying ML models to production.
• Demonstrated success delivering production-ready software with release pipeline integration.

TECHNICAL SKILLS
Must Have

• AWS services- Bedrock, SageMaker, ECS and Lambda
• Demonstrated contributions to open-source AI/ML/Cloud projects
• Demonstrated proficiency in Python and Golang coding languages
• Experience implementing RAG architectures and using frameworks and ML tooling like: Transformers, PyTorch, TensorFlow, and LangChain
• LLM (Large Language Model)
• Ph.D. in AI/ML/Data Science

Nice To Have
Demonstrated experience with AWS organizations and policy guardrails (SCP, AWS Config)
FinOps
 
NICE-TO-HAVES:

• Policy as Code development (i.e., Terraform Sentinel) to manage and automate cloud policies, ensuring compliance
• Experience optimizing cost-performance in AI systems (FinOps mindset).
• Awareness of data privacy and compliance best practices (e.g., PII handling, secure model deployment).
• Demonstrated experience with AWS organizations and policy guardrails (SCP, AWS Config).

Email your resume to: usjobs@mavensoft.com
To learn more about Mavensoft visit us online at http://www.mavensoft.com/