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Senior Generative AI Engineer

SalesforcePlano, TX🇺🇸United States

Why this role stands out

At Salesforce, you can drive innovation as a Senior Generative AI Engineer, leveraging your expertise in LLMs and microservices to build cutting-edge AI solutions. This hybrid role offers incredible growth potential within a renowned tech leader, perfect for experienced engineers passionate about shaping the future of AI. Apply today to join a dynamic team and contribute to groundbreaking projects!

Quick overview

SeniorityMid Senior
Work modeHybrid
LocationPlano, TX, United States
DockerFastAPIMicroservicesMongoDBNeo4jMLOpsAgileAzureGenerative AIGitHub ActionsKubernetesLLMPython

Job description

Required Qualifications
Core Software Engineering
  • 8+ years of experience in software engineering with strong expertise in Python.
  • Hands-on experience designing and developing microservices-based architectures using FastAPI or similar Python frameworks.
  • Experience building scalable, secure, and production-grade APIs.

Cloud & Data Platforms
  • Strong experience with Microsoft Azure, including AI, data, and application services.
  • Expertise in MongoDB and NoSQL database design, optimization, and data modeling.
  • Experience deploying and managing cloud-native applications and containerized workloads.

Generative AI & Agentic Systems
  • Proven experience developing Generative AI solutions using modern LLM frameworks.
  • Hands-on experience building AI Agents, multi-agent systems, and autonomous workflows.
  • Strong understanding of Retrieval-Augmented Generation (RAG) architectures, including:
    • Knowledge RAG
    • Graph RAG
    • Hybrid retrieval systems
    • Context-aware retrieval pipelines
  • Experience designing enterprise knowledge bases, semantic search solutions, and context-building frameworks.

Large Language Models
  • Strong understanding of Large Language Models (LLMs) and Small Language Models (SLMs).
  • Experience with model selection, prompt engineering, grounding strategies, fine-tuning approaches, and inference optimization.
  • Familiarity with model performance, latency, cost optimization, and governance considerations.

AI Evaluation & Observability
  • Hands-on experience implementing Agentic Evaluation frameworks, including tools such as DeepEval.
  • Experience designing evaluation metrics for:
    • Retrieval quality
    • Hallucination detection
    • Answer relevance
    • Agent task completion
    • Safety and reliability
  • Experience with AI observability and monitoring platforms, particularly Arize AI, for production monitoring, tracing, and model performance analysis.

Preferred Qualifications
  • Experience with vector databases and embedding models.
  • Familiarity with LangChain, LangGraph, Semantic Kernel, LlamaIndex, or similar AI orchestration frameworks.
  • Experience building enterprise AI applications with governance, security, and compliance considerations.
  • Knowledge of MLOps/LLMOps practices, CI/CD pipelines, and model lifecycle management.
  • Experience working in Agile product development environments.

Key Responsibilities
  • Design and develop scalable AI-powered microservices and APIs using Python and FastAPI.
  • Build and maintain enterprise-grade RAG and Graph RAG solutions.
  • Develop intelligent agentic workflows that leverage organizational knowledge and business context.
  • Optimize knowledge retrieval, context orchestration, and response quality for AI applications.
  • Implement evaluation frameworks and monitoring solutions using DeepEval and Arize.
  • Deploy, monitor, and maintain AI applications on Azure.
  • Collaborate with product, engineering, and business teams to translate use cases into production-ready AI solutions.

Must have existing hands on experience
  • Azure AI Foundry
  • Azure OpenAI Service
  • Semantic Kernel
  • LangGraph
  • Neo4j or Graph Databases
  • Vector Databases (Azure AI Search, Pinecone, Weaviate, Qdrant)
  • Kubernetes and Docker
  • GitHub Actions / Azure DevOps

This version is targeted at a Senior Generative AI Engineer (7-10+ years of experience).

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