Top 1 Llmops vector embedding quantum generative ai Jobs

AI Consultant
Hare and Turtle AI Solutions —Seattle, WA
- $70 - $90 an hour
- Full-time
- Azure
- System design
- Java
- Paid time off
- Parental leave
Quick Apply
1d

Check out these similar jobs

Based on your search for llmops vector embedding quantum generative ai jobs.

Business Growth Consultant – AI Solutions (SMB Market)
GMIC AI INC —Anaheim, CA
You will manage your *own field schedule and plan business visits independently.*. Our system is already being deployed in businesses such as *auto repair shops…
From $40,000 a year
Quick Apply
AI Solutions Consulting Lead
Crowe —Boston, MA
Relevant bachelor’s degree in business, engineering, computer science, information systems, data analytics, or a related field, or equivalent professional or…
$102,400 - $204,100 a year
Quick Apply
10d

I want to receive the latest job alert for llmops vector embedding quantum generative ai

By signing in to your account, you agree to SimplyHired's Terms of Service and consent to our Cookie and Privacy Policy.

Explore jobs in more locations

llmops vector embedding quantum generative ai jobs near

Ai Prompt Writer jobs in Remote

Hr Consultant jobs in Houston, Tx

Ai Prompt Consultant jobs in Afton, Mn

Ai Prompt Consultant jobs in Remote

Ai Prompt Consultant jobs in Minnesota

AI Consultant

Hare and Turtle AI Solutions
Seattle, WA

Quick Apply

Job Details

Full-time
$70 - $90 an hour
1 day ago

Benefits

Paid time off
Parental leave

Qualifications

AI models
TensorFlow
Software implementation
Generative models
SQL
Machine intelligence
AI-driven automation
Machine learning libraries
AI
Machine learning frameworks
Stakeholder relationship building
Generative AI
Stakeholder management

Full Job Description

Job Summary
We are seeking a highly experienced Senior AI Consultant / GenAI Solution Architect with strong expertise in designing, building, and deploying production-grade multi-agent GenAI systems for enterprise use cases. The ideal candidate will have deep hands-on experience in agentic AI frameworks, RAG architectures, observability integrations, enterprise AI governance, and Root Cause Analysis (RCA)-driven intelligent automation.

This role requires ownership of the complete lifecycle—from solution architecture and pilot execution to deployment and hypercare support—while working closely with technical teams, business stakeholders, and enterprise leadership.

Responsibilities

Design, architect, and deploy enterprise-scale multi-agent GenAI systems for complex business workflows.
Build intelligent agent ecosystems using frameworks such as LangChain, CrewAI, AutoGen, or equivalent agentic orchestration frameworks.
Tool calling
Memory orchestration
Reflection / critique loops
Context management
Knowledge retrieval pipelines
Design and operationalize AI personas, persona catalogs, system prompts, behavioral boundaries, and tone/authority controls within agent workflows.
Integrate persona adaptation mechanisms directly into agent orchestration flows, rather than post-response processing.
5 Whys
Ishikawa (Fishbone Analysis)
Fault Tree Analysis
Logs
Metrics
Traces
Events
Monitoring systems
Guardrails
PII protection
Access control
Auditability
Compliance enforcement
Policy-bound AI behavior
Collaborate with business stakeholders to translate enterprise use cases into scalable GenAI solutions.
Present technical outcomes in business-friendly language for leadership and customer-facing discussions.
Solution design
Proof of Concept
Pilot execution
Production deployment
Hypercare support
Work with cross-functional teams across architecture, engineering, operations, compliance, and customer success.

Skills

Strong proficiency in machine learning frameworks such as TensorFlow, Spark MLlib, or similar platforms.
Extensive experience with AWS cloud services for deploying scalable AI solutions.
Expertise in natural language processing (NLP), data mining, and big data analytics techniques.
Programming skills in Python, Java, C, Bash (Unix shell), VBA, and familiarity with Java for application development.
Knowledge of SQL databases along with experience in database design and linked data concepts.
Hands-on experience with ETL tools like Talend or similar for data integration workflows.
Familiarity with SAS analytics software and R programming for statistical analysis.
Understanding of model training processes including supervised and unsupervised learning approaches.
Ability to work with machine learning frameworks such as TensorFlow or similar platforms for model development and deployment.
Knowledge of quantum engineering principles relevant to advanced AI research is a plus. Join us as an AI Consultant to lead innovative projects that revolutionize how organizations utilize artificial intelligence!

Technical Skills

Strong hands-on experience with:
LangChain
CrewAI
AutoGen
Multi-agent orchestration frameworks
Deep expertise in:
RAG architectures
Tool calling
Agent memory systems
Reflection / critique loops
Context engineering
Prompt orchestration
Strong programming proficiency in Python (preferred for agentic AI workflows)
Experience with cloud AI ecosystems:
Azure OpenAI
AWS Bedrock
Google Vertex AI
Anthropic APIs
Experience integrating with observability platforms and enterprise monitoring systems
Knowledge of:
Responsible AI frameworks
AI safety guardrails
Security and compliance controls
Access governance
Audit mechanisms

Domain / Functional Skills

Hands-on experience in Root Cause Analysis (RCA) for complex systems:
IT Operations
Networking
Customer journey troubleshooting
Distributed systems
Experience embedding RCA reasoning into autonomous AI workflows
Experience designing enterprise AI personas and behavioral policy enforcement
Familiarity with regulated industry environments:
Telecom
BFSI / Finance
Healthcare

Leadership / Business Skills

Strong stakeholder management and communication skills
Ability to explain complex AI concepts to business stakeholders
Program ownership mindset with delivery accountability
Experience leading enterprise AI transformation initiatives

Experience Requirements

8–12 years of experience in:
AI / ML
Software Engineering
Data Science
Intelligent Automation
2–3+ years specifically in Generative AI / Agentic AI systems
Must have successfully delivered at least one production-grade or late-stage pilot multi-agent GenAI implementation

Preferred Qualifications

Experience in enterprise AI consulting engagements
Exposure to LLMOps / MLOps practices
Experience with enterprise architecture and integration patterns
Familiarity with vector databases, embeddings, and knowledge orchestration
Prior experience in customer-facing consulting or solution advisory roles

Pay: $70.00 - $90.00 per hour

Benefits:

Paid time off
Parental leave

Work Location: In person

Quick Apply

Refine Your Search

llmops vector embedding quantum generative ai jobs

AI Consultant

Check out these similar jobs

I want to receive the latest job alert for llmops vector embedding quantum generative ai

Explore jobs in more locations

Job Seeker Tools

Employer Tools

Browse

Stay Connected