AI/ML Engineer
CCS, LLC
Plano, TX, United States
4 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Compensation
$135,200.0 - $156,000.0
Working hours
Regular working hours
Job source
Tech stack
Artificial Intelligence
Amazon Web Services
Amazon S3
Cloud Engineering
Continuous Integration
Python (Programming Language)
OpenAI
Pinecone
Qdrant
Data Ingestion
LangChain
Retrieval-Augmented Generation
+17 more
Large Language Models
Prompt Engineering
Llamaindex
Cloudformation
Git Flow
HuggingFace
Weaviate
Ray Serve
Milvus
Machine Learning Operations
Api Design
Terraform
Data Pipelines
Serverless Computing
OpenSearch
Docker
Microservices
Job description
- Cloud Architecture & Infrastructure, Design scalable, secure AWS architectures
- LLM & GenAI Platforms, Lead integration of API-based and self-hosted LLMs, implement RAG solutions
- Prompting & Evaluation, Develop prompt engineering strategies, reusable templates, and evaluation frameworks
- Vector Databases & Retrieval Pipelines, Implement and maintain vector stores (OpenSearch, Pinecone, Milvus, Qdrant)
- Data Ingestion & Processing Pipelines
- Microservices & Serverless Systems
- Python Development & AI Tooling
- Security, Governance & Cross-Functional Leadership
Requirements
- Bachelor’s Degree
- 6+ years cloud architecture experience
- 3+ years building production GenAI/LLM systems on AWS.
- Strong Python and AWS expertise, including Lambda, ECS/EKS, S3, SageMaker, Docker and Kubernetes.
- Production experience with vector databases and designing ingestion + embedding pipelines for both batch and streaming workloads.
- Hands-on with prompt design, evaluation, LLM orchestration, and RAG implementation patterns.
- Experience deploying and operating model- serving or MCP - like server infrastructure (selfhosted or managed).
- Proficient with IaC and delivery tooling, including Terraform/CloudFormation, GitOps, and CI pipelines.
- Experience with model-serving infrastructure, such as Amazon SageMaker, NVIDIA Triton, Ray Serve, or similar platforms.
- Hands-on experience with GenAI libraries and frameworks, including LangChain, LlamaIndex, Hugging Face, and OpenAI APIs.
- Deep operational expertise with vector databases, such as Pinecone, Milvus, Weaviate, or Qdrant.
- AWS Solutions Architect, AWS DevOps Engineer, or equivalent industry certifications.
Benefits & conditions
- Bonus based on performance
- Dental insurance
- Health insurance
- Vision insurance
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Prepare application
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