Gen AI Engineer

Lares IT Solutions Inc.
Dallas, TX, United States
13 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Amazon Web Services Software Applications Cloud Computing Computer Programming Python (Programming Language) Machine Learning Tensorflow Software Engineering Management of Software Versions Google Cloud Pytorch
+16 more
Retrieval-Augmented Generation Large Language Models Multi-Agent Systems Prompt Engineering IT Architecture Generative AI Cloudformation AI Platforms Kubernetes Information Technology Machine Learning Operations Restful APIs Terraform Automation Anywhere Docker Microservices

Job description

We are seeking an experienced Gen AI Engineer in Artificial Intelligence, Computer Science, Machine Learning, Data Science, or a related discipline to lead the design and implementation of next-generation Generative AI solutions. The ideal candidate will have extensive experience architecting enterprise AI platforms using AWS Bedrock and Google Vertex AI, with a proven track record of building scalable, production-grade AI applications powered by Large Language Models (LLMs).

This role requires a strong technical leader who can collaborate with cross-functional teams to define AI strategy, architect cloud-native AI solutions, and drive innovation using the latest Generative AI technologies., * Design and architect enterprise-grade Generative AI solutions using AWS Bedrock and Google Vertex AI.

  • Develop AI-powered applications leveraging foundation models, LLMs, and AI agents.
  • Build scalable Retrieval-Augmented Generation (RAG) architectures using vector databases.
  • Lead AI platform strategy, architecture reviews, and technology roadmap initiatives.
  • Collaborate with engineering, data science, and business teams to translate business requirements into AI solutions.
  • Evaluate and integrate foundation models from Anthropic, Amazon Nova, Meta Llama, Google Gemini, and other leading providers.
  • Develop secure, scalable, and highly available AI architectures following enterprise best practices.
  • Build AI workflows using LangChain, LlamaIndex, and prompt engineering techniques.
  • Design and implement MLOps pipelines for model deployment, monitoring, versioning, and governance.
  • Optimize AI workloads for performance, scalability, reliability, and cost.
  • Mentor engineering teams and establish AI architecture standards and best practices.
  • Stay current with emerging AI technologies and recommend innovative solutions to improve business outcomes.

Requirements

  • 10+ years of software engineering, machine learning, or AI development experience.
  • 5+ years of hands-on experience with AWS Bedrock.
  • 5+ years of hands-on experience with Google Vertex AI.
  • Strong experience designing enterprise-scale AI and ML architectures.
  • Deep understanding of Large Language Models (LLMs), Foundation Models, and Generative AI.
  • Strong programming experience in Python.
  • Experience building Retrieval-Augmented Generation (RAG) applications.
  • Experience with AI orchestration frameworks such as LangChain or LlamaIndex.
  • Strong knowledge of prompt engineering, AI agents, embeddings, and vector databases.
  • Experience with cloud platforms including AWS and Google Cloud Platform (Google Cloud Platform).
  • Experience implementing MLOps pipelines, model deployment, monitoring, and governance.
  • Strong understanding of REST APIs, microservices, Docker, and Kubernetes., * Experience with multi-agent AI systems and autonomous AI workflows.
  • Experience with vector databases such as Pinecone, FAISS, Weaviate, or OpenSearch.
  • Experience with ML frameworks including TensorFlow or PyTorch.
  • Knowledge of Responsible AI, AI governance, security, and compliance.
  • Experience with CI/CD pipelines, Infrastructure as Code (Terraform/CloudFormation), and Kubernetes.
  • AWS Certified Machine Learning Specialty, AWS Solutions Architect, Google Professional Machine Learning Engineer, or equivalent cloud certifications are highly preferred.

Preferred Skills

  • AWS Bedrock
  • Google Vertex AI
  • Generative AI
  • Large Language Models (LLMs)
  • RAG (Retrieval-Augmented Generation)
  • AI Agents
  • LangChain
  • LlamaIndex
  • Python
  • Prompt Engineering
  • Vector Databases
  • MLOps
  • Docker
  • Kubernetes
  • AWS
  • Google Cloud Platform (Google Cloud Platform)

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