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Stellar Ai Jobs (NOW HIRING)

Saris AI

Senior AI Product Manager

San Francisco, CA · On-site

$149K - $196K/yr

About Saris We're a San Francisco & Montreal based applied AI startup that's building the future of ... Work with a stellar team of engineers, builders, and leaders; including repeat YC founders with a ...

Stellar Cyber

Regional Sales Manager MSSP- West

$240K - $320K/yr

Join Stellar Cyber, one of the fastest-growing global leaders in AI-driven cybersecurity, trusted by global enterprises, government agencies, and over 30% of the world's top MSSPs. Our Open XDR ...

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How much do stellar ai jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for stellar ai in the United States is $58.15, according to ZipRecruiter salary data. Most workers in this role earn between $47.12 and $70.91 per hour, depending on experience, location, and employer.

How does a Stellar AI professional typically collaborate with cross-functional teams in a product development environment?

As a Stellar AI professional, you will frequently work alongside product managers, software engineers, and data scientists to design and deploy AI-driven solutions. Collaboration often involves participating in sprint meetings, sharing progress on model development, and integrating AI outputs with product features. Open communication and problem-solving with other departments are key, as you'll need to ensure that your AI models align with business goals and technical requirements. This cross-functional teamwork helps to accelerate innovation and ensures that AI solutions add real value to the organization.

What is the difference between Stellar Ai vs Data Analyst?

AspectStellar AiData Analyst
Required CredentialsDegree in Computer Science, Data Science, or related field; experience with AI toolsBachelor's in Statistics, Mathematics, or related field; proficiency in data analysis software
Work EnvironmentTech companies, AI startups, data-driven organizationsBusiness, finance, healthcare, and other industries analyzing data
Employer & Industry UsagePrimarily in AI and tech sectorsAcross various industries including finance, marketing, healthcare
Common Search & Comparison IntentUnderstanding AI-specific roles and skillsAnalyzing data and insights for decision-making

Stellar Ai focuses on developing and implementing AI solutions, requiring skills in machine learning and programming. Data Analysts interpret data to inform business decisions, often using statistical tools. While both roles work with data, Stellar Ai is more technical and AI-centric, whereas Data Analysts focus on data interpretation and reporting.

What is a Stellar AI?

A Stellar AI typically refers to an artificial intelligence system designed to analyze, interpret, or predict data related to stars and celestial phenomena. In astronomy and astrophysics, Stellar AI can be used for tasks such as identifying star types, detecting exoplanets, and automating data analysis from telescopes. These AI systems help researchers process vast amounts of astronomical data more efficiently and make discoveries that might be missed by humans. The use of AI in stellar research is rapidly growing as datasets become larger and more complex.

What are the key skills and qualifications needed to thrive as a Stellar AI engineer, and why are they important?

To thrive as a Stellar AI Engineer, you need strong skills in machine learning, data analysis, and software development, typically supported by a degree in computer science or a related field. Experience with AI frameworks (such as TensorFlow or PyTorch), programming languages (like Python), and cloud computing platforms is commonly required. Problem-solving abilities, creativity, and effective communication are vital soft skills for this role. These competencies ensure the successful design and deployment of AI solutions that address complex business challenges and foster innovation.
What cities are hiring for Stellar Ai jobs? Cities with the most Stellar Ai job openings:
Infographic showing various Stellar Ai job openings in the United States as of August 2026, with employment types broken down into 74% Full Time, 22% Part Time, and 4% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $120,942 per year, or $58.1 per hour.

Lead Engineer AI Agent Platform - Nashville, TN - 100% Onsite (5 Days Onsite/week) - Contract - CTS

Stellar Consulting Solutions

Nashville, TN • On-site

$99K - $130K/yr

Other

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Stellar Consulting Solutions is a boutique business & technology consulting company headquartered in Atlanta, GA. We deliver high quality, agile, and experienced workforce for niche technology projects of any scale. We help forward thinking clients to solve specific problems by understanding their needs and align talent that can move fluidly
to match skill supply and demand on a real-time basis.

Stellar Consulting has a unique combination of technical and digital skills to recruit, engage, and retain qualified talent. We have a stellar reputation for striving to achieve high ethical standards. Our use of Innovative techniques and industry best practices has made us one of the fastest growing boutique firms delivering to enterprise business.

Job Title: Lead Engineer AI Agent Platform

Job Location: Nashville, TN - 100% Onsite (5 Days Onsite/week)

Job Type: Contract
Job Description:-

Lead Engineer AI Agent Platform

About the Role:-

We are building a next-generation enterprise AI platform that enables teams to design, deploy, and scale intelligent agents across digital, marketing, and operational workflows.

This platform provides standardized infrastructure, model access, orchestration, evaluation, and governance, enabling teams to rapidly build AI-powered capabilities in a secure, scalable, and production-ready way.

We're looking for Lead Engineers who can both:-

Build high-quality AI agents and workflows

Lead the evolution of the platform powering them at scale

This role sits at the intersection of Agentic AI, platform engineering, and enterprise systems, with strong emphasis on security, CI/CD, observability, and rigorous validation of AI systems.

What You'll Do:-

Build and deploy AI agents and agentic workflows for real-world business use cases.

Design and evolve core platform capabilities for agent development, orchestration, and runtime.

Develop RAG pipelines, tool integrations, and structured reasoning systems.

Enable flexible usage across multiple LLM providers and model libraries.

Implement secure, scalable, and observable architectures for AI systems.

Establish robust CI/CD pipelines for agent lifecycle (build, test, deploy, rollback).

Define and implement agent testing & evaluation strategies, including:

o Automated evaluation pipelines

o Agentic testing models and simulation-based validation

o Continuous quality, accuracy, and regression testing

Build and enforce LLM observability and evaluation frameworks (this is core to the role).

Drive platform standards, reusable components, and engineering best practices.

Partner across teams and external partners to scale adoption of the platform.

What We're Looking For:-

Core Engineering Skills:-

8+ years of software engineering experience.

Strong experience with Google Cloud Platform (Vertex AI, GKE, BigQuery, APIs).

Experience with distributed systems and scalable platform design.

AI / Agentic Systems:-

Hands-on experience with:

o LLMs, embeddings, and RAG architectures

o Agentic workflows and AI-driven systems

Experience working with multiple model providers / model ecosystems.

Strong familiarity with agent frameworks such as LangChain, LangGraph, or similar ecosystems.

Platform, Security & DevOps:-

Strong experience with:

o CI/CD pipelines and automation for production systems

o Secure system design (authentication, authorization, data access controls)

o API-first and microservices architectures

Experience designing highly observable systems (metrics, tracing, logging).

Ability to manage performance, cost, and reliability trade-offs in AI workloads.

Evaluation, Observability & Testing (Must-Have):-

Hands-on experience with LLM evaluation frameworks and observability tooling.

Experience designing:

o Model evaluation and benchmarking pipelines

o Test harnesses for agent workflows

o Continuous validation / regression testing for AI systems

o Simulation or scenario-based testing for agent behavior

Nice to Have:-

Experience with AI governance / Responsible AI practices.

Familiarity with enterprise-scale AI platforms or shared developer platforms.

Retail or domain experience (digital, marketing, operations).

Why This Role:-

Work on a foundational AI platform initiative with enterprise-wide impact.

Define how AI agents are built, governed, and scaled across the organization.

Influence both hands-on engineering and long-term platform direction.


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