Level

Together AI

Senior Software Engineer, Observability

Together AI is hiring a Senior Software Engineer, Observability in San Francisco, United States. It pays $200k-$280k a year and Level rates it ; you can apply on Together AI.

Level's read on this job

  • Builds AI ●●●● is how Level rates this software engineer role: the job is building AI systems.
  • Pay on this posting starts 19% higher than the typical software engineer posting on Level.
  • The posting mentions Cursor, Elevenlabs and Decagon among its tools and skills.
  • Level classes it as a senior role.
  • Together AI has 84 other open roles on Level.

AI in this role

cursorelevenlabsdecagon
fine-tuning

About the Role

Together AI is building the AI Acceleration Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art AI cloud infrastructure.

The AI Infrastructure team at Together AI is at the forefront of building and scaling the foundational systems that power our generative AI platform. The storage and observability team is crucial for designing, implementing, and maintaining robust distributed storage solutions, ensuring seamless data access and management. They are also responsible for developing comprehensive observability platforms, providing critical insights into system performance and GPU utilization, and proactively identifying and resolving issues.

Responsibilities

  • Design and implement a scalable observability platform (metrics, logs, traces) using tools like Prometheus, Grafana, ClickHouse, ClickStack, and OpenTelemetry, including telemetry data pipelines and log aggregation workflows.
  • Develop automated monitoring, alerting, and anomaly detection systems, including SLIs/SLOs, runbooks, and predictive analytics for critical services.
  • Build and deploy custom observability tools and infrastructure-as-code using Go, Python, Terraform, Ansible, and Helm.
  • Collaborate with engineering teams to enhance distributed tracing and application monitoring, and lead incident response with post-mortem analysis.
  • Define observability best practices.

Requirements

  • Expertise in observability platforms (Prometheus, Grafana, ClickStack, OpenTelemetry) and cloud-native monitoring services (AWS, GCP, Azure).
  • Strong programming skills in Go, Python, or similar languages, with proficiency in infrastructure-as-code tools (Terraform, Ansible, Helm).
  • Experience designing, operating, and scaling large-scale distributed systems and pipelines for high-volume data ingestion and real-time querying.
  • Deep understanding of containerization (Docker) and orchestration (Kubernetes).
  • Knowledge of microservices architecture, service mesh technologies, CI/CD pipelines, and GitOps workflows.
  • Expertise in managing databases (PostgreSQL, MongoDB, Redis) and time-series databases with high-cardinality data.

Preferred

  • Experience monitoring AI/ML infrastructure, GPU clusters, and custom metrics for model performance and training pipelines.
  • Background in high-frequency, low-latency systems monitoring, chaos engineering, and reliability testing.
  • Contributions to open-source observability projects.
  • Familiarity with security monitoring and compliance frameworks.

About Together AI

Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month.

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $200,000 - $280,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

 

How we rate this

Senior Software Engineer, Observability at Together AI rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Fine-tuningCursorElevenlabsDecagon

Also common in software engineer jobs at this level

Pay

This job starts at
$200k
Typical software engineer job
$168k

This posting starts 19% above the typical software engineer job. See software engineer jobs

Questions you could be asked

  1. Walk me through fine-tuning a model: what data did you use, and how did you check the result?
  2. Walk me through how you've used Cursor in your day-to-day work.
  3. What are the limits of Elevenlabs that you've run into, and how did you work around them?
  4. What's a project where you used Decagon hands-on?
  5. How would you decide a model or AI system is ready to ship?

Adapt your resume

  • List these exact terms on your resume: Fine-tuning, Cursor, Elevenlabs, and Decagon. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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