1

Temporary Observability Engineer Jobs in California

AI Engineer

Pleasanton, CA

$116K - $159K/yr

Contribute to MLOps workflows including CI/CD, model lifecycle management, observability, and cloud ... temporary roles are not eligible for the above benefits. Compensation Pay Range: $110k - $130k ...

Sr Production Engineer

La Honda, CA · On-site

$156K - $208K/yr

Observability: Familiarity with Google Cloud Observability and OpenTelemetry standards. * Migration ... For temporary assignments lasting 13 weeks or longer, AllSTEM Connections is pleased to offer major ...

Sr Production Engineer

La Honda, CA · On-site

$156K - $208K/yr

Observability: Familiarity with Google Cloud Observability and OpenTelemetry standards. * Migration ... For temporary assignments lasting 13 weeks or longer, AllSTEM Connections is pleased to offer major ...

Software Engineer

Folsom, CA · On-site +1

$75.50 - $102/hr

Temporary Salary: $75.50-102 Hourly $ 75.50 - $102 / hour Start Date: Jun 29, 2026 Are you ready to ... Instrument the entire AI platform with comprehensive observability, including dashboards, audit ...

Instrument and monitor LLM applications in production using observability tools, tracking cost ... temporary roles are not eligible for the above benefits. Compensation Pay Range: $130k - $155k ...

Engineering Manager

Pleasanton, CA · On-site

$180K - $210K/yr

Ensure seamless production handoffs with strong documentation, observability, and SLAs * Drive ... temporary roles are not eligible for the above benefits. Compensation Pay Range: $180k - $210k ...

Staff Site Reliability Engineer

San Jose, CA · Hybrid

$66.75 - $88.75/hr

You view change as an opportunity and setbacks as temporary. You maintain composure and focus in ... Hands-on experience with Systems Kickstart using PXE and monitoring and observability tools like ...

Observability & Reliability: Utilize Dynatrace, Grafana, and CloudWatch to ensure high availability ... For temporary assignments lasting 13 weeks or longer, AllSTEM Connections is pleased to offer major ...

next page

Showing results 1-20

Temporary Observability Engineer information

What engineers make $300,000 a year?

Senior observability engineers with extensive experience, specialized skills in monitoring tools, cloud environments, and automation can earn $300,000 or more annually. High compensation is often associated with roles in large tech companies, leadership positions, or those with expertise in areas like distributed systems and performance optimization.

What engineers make $500,000?

Senior engineers in high-demand fields such as software, data engineering, and cloud infrastructure can earn $500,000 or more annually, especially with extensive experience, specialized skills, and stock options. Roles in tech giants or startups with equity and bonuses often reach this compensation level.

What are Temporary Observability Engineers?

Temporary Observability Engineers are professionals hired on a short-term basis to design, implement, and optimize monitoring, logging, and alerting solutions within an organization's IT infrastructure. Their main goal is to ensure system reliability and visibility by setting up tools and processes that track application performance, detect issues, and provide actionable insights. These engineers often work on specific projects or to fill a gap during peak periods, focusing on improving how systems are observed and managed. They collaborate with development, operations, and security teams to ensure seamless integration of observability practices. After their contract ends, they may provide documentation and training to help permanent staff maintain and evolve the observability setup.

What jobs pay $10,000 a month without a degree?

A Temporary Observability Engineer can potentially earn $10,000 a month through contract work, especially if they have specialized skills in monitoring, logging, and cloud platforms. High-demand tech roles often prioritize experience and certifications over formal degrees, and remote or freelance opportunities can offer such compensation levels for skilled professionals.

What are some typical challenges Temporary Observability Engineers face when quickly integrating into ongoing projects?

Temporary Observability Engineers often join teams with established systems and workflows, which can make ramping up quickly a challenge. They may need to familiarize themselves with existing monitoring tools, dashboards, and alerting configurations in a short time, while also understanding the team's priorities and pain points. Communication is key, as collaborating with DevOps, SREs, and developers helps ensure observability improvements are aligned with ongoing initiatives. Flexibility, adaptability, and strong documentation skills are especially valuable in this fast-paced, project-based environment.

What are the key skills and qualifications needed to thrive as a Temporary Observability Engineer, and why are they important?

To thrive as a Temporary Observability Engineer, you need strong knowledge of monitoring, logging, and tracing concepts, along with experience in cloud environments and a relevant technical degree or equivalent experience. Familiarity with tools like Prometheus, Grafana, ELK Stack, and APM solutions, as well as scripting languages such as Python or Bash, is typically required. Excellent problem-solving skills, adaptability, and clear communication help professionals quickly integrate into teams and address incidents effectively. These skills ensure the reliability, performance, and visibility of systems, which is critical for rapid troubleshooting and maintaining service health.

What jobs pay 400 an hour?

In the field of observability engineering, highly specialized consultants or contractors with extensive experience and advanced skills in monitoring, logging, and cloud infrastructure can command rates of $400 an hour or more. Such roles often require certifications, expertise in tools like Prometheus or Grafana, and work on complex, high-stakes projects, typically in freelance or contract capacities. These high rates are usually associated with senior-level professionals working in demanding environments or on critical systems.
What are the most commonly searched types of Observability Engineer jobs in California? The most popular types of Observability Engineer jobs in California are:
What are popular job titles related to Temporary Observability Engineer jobs in California? For Temporary Observability Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Temporary Observability Engineer jobs in California look for? The top searched job categories for Temporary Observability Engineer jobs in California are:

$116K - $159K/yr

Other

Medical, Retirement

Posted 16 days ago


Job description

About the Role

Senior AI Engineer - Generative AI & LLMs

At Avathon, we are building cutting-edge AI solutions that transform operations across asset-intensive industries such as Supply Chain, Logistics, Energy, Mining, Aerospace, and Industrial Manufacturing. As an AI Engineer, you will play a critical role in designing, developing, and deploying scalable AI systems with a strong focus on Generative AI, Large Language Models (LLMs), and production-grade machine learning applications.

This role is ideal for someone with strong engineering depth who can bridge research and production-building robust AI platforms, optimizing LLM workflows, and delivering high-impact solutions across forecasting, route optimization, anomaly detection, predictive maintenance, and intelligent automation.

With 3-5 years of hands-on industry experience, you are expected to bring expertise in AI system design, ML engineering, LLM deployment, and scalable software development within fast-paced startup environments.

You Will
  • Design, build, and deploy production-grade AI/ML systems with strong emphasis on Generative AI and LLM-powered applications
  • Develop and optimize end-to-end LLM pipelines including RAG architectures, fine-tuning, prompt orchestration, evaluation, and observability
  • Build scalable backend services and APIs for AI applications using modern engineering best practices
  • Implement and productionize transformer-based models and GenAI workflows for enterprise use cases
  • Design vector search systems, embedding pipelines, and retrieval frameworks for knowledge-intensive applications
  • Partner closely with Product, Engineering, and Business teams to translate operational challenges into scalable AI solutions
  • Drive experimentation, benchmarking, model evaluation, and performance optimization with scientific rigor
  • Improve inference efficiency, latency optimization, cost management, and reliability of deployed AI systems
  • Establish guardrails, hallucination detection, monitoring, and responsible AI practices for production deployments
  • Contribute to MLOps workflows including CI/CD, model lifecycle management, observability, and cloud deployment
  • Stay current with the latest advancements in LLMs, agentic systems, foundation models, and applied AI engineering
You'll Have
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field
  • 3-5 years of hands-on industry experience in AI Engineering, Machine Learning Engineering, Applied AI, or related roles
  • Strong experience building and deploying LLM-based applications in production environments
  • Solid expertise with Python and modern AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, or similar
  • Strong understanding of transformer architectures, LLM fine-tuning, prompt engineering, RAG systems, and vector databases
  • Experience building scalable APIs and backend systems supporting AI workflows
  • Familiarity with cloud platforms such as AWS, GCP, or Azure
  • Strong software engineering fundamentals including system design, debugging, performance optimization, and production reliability
  • Experience with containerization, deployment pipelines, and collaborative engineering environments
  • Strong analytical thinking, ownership mindset, and ability to work in ambiguous, fast-moving startup environments
  • Strong communication skills and ability to work cross-functionally with technical and business stakeholder
Preferred Qualifications
  • Exposure to Retrieval-Augmented Generation (RAG), vector databases, or embedding-based search systems
  • Familiarity with LLM observability and evaluation tools (e.g., Langfuse, LangSmith, Arize Phoenix, Weights & Biases)
  • Hands-on experience with practical LLM deployment -- prompt versioning, cost/latency tracking, guardrails, or hallucination detection
  • Exposure to LLM evaluation frameworks (e.g., RAGAS, DeepEval) or LLM-as-judge evaluation patterns
  • Basic understanding of MLOps practices and model lifecycle management
  • Experience working on applied AI projects in academic, internship, or startup settings
  • Interest in industrial AI and asset-intensive environments
  • Industry exposure in one or more of the following domains: Mining, Oil & Gas, Aerospace, Supply Chain, Logistics, or Renewable Energy
Interview Process

As part of the interview process, you will be asked to complete a technical assessment.

Benefits & Perks

What are the benefits and perks at Avathon? Below are some highlights we offer to our U.S. full-time employees -- we'd love to connect and share more!

  • Evolving culture with the opportunity to drive new ideas and technology
  • Stock Option Grants
  • Medical Coverage and Parental Leave Plans
  • 401k with Employer Match
  • Monthly Technology Allowance
  • Newly renovated office space located near Pleasanton, CA -- including fully stocked beverage and snack areas

Contract and temporary roles are not eligible for the above benefits.

Compensation

Pay Range: $110k - $130k salary annually. Pay for this position is based on a number of factors including geographic location and may vary depending on job-related knowledge, skills, and experience.

Location: This role is not remote. Candidates must be based in the Bay Area, CA and are expected to report to our Pleasanton office 5 days a week.