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Gen AI Developer

Roles & Responsibilities

  • Strong Python programming skills with AI/ML libraries such as PyTorch or TensorFlow
  • Experience with Azure AI services (Azure OpenAI, Azure ML) and/or AWS AI/ML services (Bedrock, SageMaker, Comprehend, Rekognition)
  • Proficiency in cloud architecture, DevOps practices, and Infrastructure as Code (Terraform, AWS CloudFormation)
  • Familiarity with LLM orchestration frameworks (LangChain, Semantic Kernel, Prompt Flow) and vector databases (Azure AI Search, OpenSearch, Pinecone, FAISS)

Requirements:

  • Solution Architecture Design: Design and architect GenAI solutions using Azure AI (Azure OpenAI, Azure ML) and/or AWS AI/ML services (Bedrock, SageMaker, Comprehend, Lex); implement cloud-native architectures for LLM-based applications, including multi-cloud or hybrid deployments; define and manage MLOps pipelines using Azure ML Pipelines or AWS SageMaker Pipelines.
  • Development Implementation: Develop and fine-tune LLMs using frameworks like Hugging Face Transformers, LangChain, Semantic Kernel, or AWS LangChain SDK; implement prompt engineering, retrieval-augmented generation (RAG), and vector search; build APIs and microservices to expose GenAI capabilities.
  • Production Deployment: Deploy GenAI models using AKS, Azure Container Apps, Amazon EKS, or Fargate; monitor and optimize model performance, latency, and cost; implement observability, logging, and alerting for AI workloads across both platforms.
  • Collaboration and Documentation: Collaborate with data scientists, DevOps, and product managers; document architecture and procedures; provide mentorship and conduct code reviews for junior developers.

Job description


Job Description:

Job Role: Gen AI Developer
Job Location: Milwaukee, WI / Remote
Job Type: Full Time
Salary Range: $120000 to $140000/Annum


Must Have Technical/Functional Skills

Looking for a highly skilled Generative AI Developer with deep expertise in designing, developing, and deploying GenAI solutions on Microsoft Azure and/or AWS. The ideal candidate will have hands-on experience in production-grade AI/ML systems, a strong understanding of LLM architectures, and the ability to architect scalable, secure, and cost-effective GenAI solutions across both cloud platforms.
Roles & Responsibilities
Key Responsibilities:
1. Solution Architecture & Design
• Design and architect GenAI solutions using Azure AI (Azure OpenAI, Azure ML) and/or AWS AI/ML services (Bedrock, SageMaker, Comprehend, Lex).
• Implement cloud-native architectures for LLM-based applications, including multi-cloud or hybrid deployments.
• Define and manage MLOps pipelines for model training, deployment, and monitoring using Azure ML Pipelines or AWS SageMaker Pipelines.
2. Development & Implementation
• Develop and fine-tune LLMs using frameworks like Hugging Face Transformers, LangChain, Semantic Kernel, or AWS LangChain SDK.
• Implement prompt engineering, retrieval-augmented generation (RAG), and vector search using Azure AI Search, Amazon Kendra, or OpenSearch.
• Build APIs and microservices to expose GenAI capabilities using Azure Functions, AWS Lambda, or containerized services.
3. Production Deployment
• Deploy GenAI models using Azure Kubernetes Service (AKS), Azure Container Apps, Amazon EKS, or Fargate.
• Monitor and optimize model performance, latency, and cost in production environments using Azure Monitor, AWS CloudWatch, and custom telemetry.
• Implement observability, logging, and alerting for AI workloads across both platforms.
4. Collaboration & Documentation
• Collaborate with cross-functional teams including data scientists, DevOps, and product managers.
• Document architecture, design decisions, and operational procedures.
• Provide mentorship and conduct code reviews for junior developers.
________________________________________
Required Skills & Qualifications:
Technical Skills:
• Strong programming skills in Python, with experience in AI/ML libraries (e.g., PyTorch, TensorFlow).
• Deep knowledge of Azure AI services (Azure OpenAI, Azure ML, Cognitive Services) and/or AWS AI/ML services (Bedrock, SageMaker, Comprehend, Rekognition).
• Experience with cloud architecture, DevOps, and Infrastructure as Code (Terraform, AWS CloudFormation).
• Familiarity with LLM orchestration frameworks: LangChain, Semantic Kernel, Prompt Flow.
• Experience with vector databases: Azure AI Search, Amazon Open Search, Pinecone, FAISS.
Soft Skills:
• Strong analytical and proble m-solving skills.
• Excellent communication and collaboration abilities.
• Ability to work in a fast-paced, agile environment.






Diverse Lynx LLC is an Equal Employment Opportunity employer. All qualified applicants will receive due consideration for employment without any discrimination. All applicants will be evaluated solely on the basis of their ability, competence and their proven capability to perform the functions outlined in the corresponding role. We promote and support a diverse workforce across all levels in the company.

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