ML & GenAI Platform Engineer

San Jose, CA, US • Posted 30+ days ago • Updated 18 days ago

Full Time

On-site

$150000-160000/yr

Fitment

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Job Details

Skills

Management
Microsoft Certified Professional
Real-time
Evaluation
Workflow
Data Engineering
Machine Learning Operations (ML Ops)
Testing
Lifecycle Management
Regulatory Compliance
Optimization
Communication
Decision-making
Python
Generative Artificial Intelligence (AI)
Orchestration
LangChain
LangSmith
Cloud Computing
Machine Learning (ML)
Databricks
Docker
Kubernetes
Vector Databases
Microsoft Azure
Continuous Integration
Continuous Delivery
DevOps
Artificial Intelligence
Computer Science
Data Science

Summary

What you know

Deploy, scale, and operate ML and Generative AI systems in cloud-based production environments (Azure preferred).
Build and manage enterprise-grade RAG applications using embeddings, vector search, and retrieval pipelines.
Implement and operationalize agentic AI workflows with tool use using frameworks such as LangChain and LangGraph.
Develop reusable infrastructure and orchestration for GenAI systems using Model Context Protocol (MCP) and AI Development Kit (ADK).
Design and implement model and agent serving architectures including APIs, batch inference, and real-time workflows.
Establish best practices for observability, monitoring, evaluation, and governance of GenAI pipelines in production.
Integrate AI solutions into business workflows with data engineering, application teams, and business stakeholders.
Drive adoption of MLOps / LLMOps practices including CI/CD automation, versioning, testing, and lifecycle management.
Ensure security, compliance, reliability, and cost optimization of AI services deployed at scale.

Important attributes for this role

Strong ownership mindset and platform thinking
Ability to lead AI platform delivery from concept to production
Clear communication and ability to translate AI concepts to business stakeholders
Strong decision-making in architecture and platform design
Enterprise mindset for reliability, security, and governance

What you'll do

8 10 years of experience in ML Engineering, AI Platform Engineering, or Cloud AI Deployment roles.
Strong proficiency in Python with experience building production-grade AI/ML services.
Proven experience deploying and supporting GenAI applications in real-world enterprise environments.
Hands-on experience with RAG systems, embeddings, vector search, and retrieval pipelines.
Experience with orchestration frameworks including LangChain, LangGraph, and LangSmith.
Strong knowledge of model serving, inference pipelines, monitoring, and observability for AI systems.
Experience working with cloud AI ecosystems (Azure AI, Azure ML, Databricks preferred).
Familiarity with containerization and deployment tools (Docker, Kubernetes, REST APIs).
Exposure to vector databases such as Pinecone, Weaviate, FAISS, or Azure Cognitive Search.
Experience deploying agentic AI systems with tool integrations in production.
Strong understanding of CI/CD pipelines and DevOps practices for AI platforms.
Familiarity with enterprise governance frameworks for Responsible AI.

Education

Bachelor's degree in Computer Science, Engineering, Data Science, or related field (required).
Master's degree is a plus.

Compensation

$150-$160K/ PA

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: RTX153458
Position Id: 2026-14663
Posted 30+ days ago

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