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AI Systems Architect

• Posted 28 days ago • Updated 1 minute ago

Full Time

$80/hr

Fitment

Dice Job Match Score™

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Job Details

Skills

Optimization
Caching
IaaS
Amazon Web Services
Microsoft Azure
Google Cloud Platform
Google Cloud
Python
Java
Stacks Blockchain
Vector Databases
Okapi BM25
Artificial Intelligence
Machine Learning (ML)
Generative Artificial Intelligence (AI)
Management
Microsoft Certified Professional
Servers
Evaluation
Reasoning
Kubernetes
Cloud Computing
IT Management
Mentorship
Orchestration
Real-time
Streaming

Summary

Role: AI Systems Architect

Location: SFO, CA & San Leandro, CA (Hybrid)

Duration: Contract for 12 + Months

Job Description

Required Experience:

Job Summary

We are seeking an experienced AI Systems Architect to design, build, and scale high-performance distributed AI systems. The ideal candidate will have deep expertise in GenAI, LLMs, and cloud-native architectures, along with hands-on experience in building enterprise-scale AI/ML platforms and agent-based systems.

Must-Have Skills

Strong experience in designing and implementing high-performance, large-scale distributed systems
Proven experience in implementing and deploying AI/ML platforms at scale
Expertise in building agent-based architectures, evaluation frameworks, and prompt/context engineering
Knowledge of MCP (Model Context Protocol) servers
Hands-on experience in LLM inference optimization, including batching and caching strategies
Strong experience with Kubernetes and cloud infrastructure (AWS/Azure/Google Cloud Platform)
Proficiency in at least one programming language (Python, Java, Go, etc.)
Expertise in designing agent data stacks & retrieval systems, including:
Vector databases
Hybrid search
Data freshness strategies
Memory systems
Graph reasoning
BM25 and advanced retrieval techniques

Key Responsibilities

Architect and deliver scalable, high-performance distributed systems
Design and deploy AI/ML and GenAI platforms at enterprise scale
Build and manage agent-based architectures, including:
Prompt and context engineering
MCP servers
Evaluation frameworks
Optimize LLM inference pipelines for latency, throughput, and efficiency
Design and implement agent data & retrieval systems (vector DBs, hybrid search, memory, graph-based reasoning)
Lead Kubernetes-based, cloud-native deployments
Provide technical leadership, architecture governance, and hands-on mentoring to engineering teams

Nice to Have

Experience with RAG (Retrieval-Augmented Generation) frameworks
Familiarity with multi-agent systems and orchestration frameworks
Exposure to real-time data pipelines and streaming architectures

Thanks & Regards,

Shiva Sarvepalli

Email: shiva.sarvepalli

100 Overlook Center, Suite 200

Princeton, NJ 08540.

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: 10235988
Position Id: 2026-39969
Posted 28 days ago

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