AWS Cloud Engineer

We are in Critical need of AWS Cloud Engineer for Long Term Contract Role - Remote

Role : AWS Cloud Engineer

Location : Remote

Duration : Long Term

Job Description

• AI Software Engineer who has actually built AI/ML applications. 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.
• Will be part of a high-impact team pushing the boundaries of cloud-native AI in a real-world enterprise setting. We re looking for candidates who have architected, developed, and supported AI/ML services in production environments.
• This is a builder s role within our Public Cloud AWS Engineering team.

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.

SUPERVISORY RESPONSIBILITIES: None
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.

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).

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