Senior ML Ops Engineer

About Aviso AI Aviso is a leading end-to-end revenue execution platform. We act as a compass to guide sales teams to maximize growth and minimize risk. Aviso’s predictive AI delivers revenue intelligence, drives team-wide actions and course corrections, and gives precise guidance so sellers and teams don’t get lost in the fog of CRM and other point tools.

With demonstrated results across Fortune 500 companies and industry leaders such as Honeywell, Lenovo, Netapp, Wiz, Armis, and RingCentral, Aviso works at the frontier of AI to help teams close more deals and drive more revenue.

Our revenue grew 100% year-on-year , underscoring both the accelerating demand for our platform and the differentiated value we provide to enterprise customers.

Aviso AI has generated

350 billion insights , analyzed

$400B in the pipeline , and helped customers win

$1640B in deals . Using Aviso AI, sales teams close, on average

20% more deals with 98%+ accuracy , reduce sales cycles by

25%+ , and cut spending on non-core CRM licenses by

30% .

Recognized by

Gartner, Forrester, and G2

as one of the top revenue intelligence platforms. Featured in

HBR, NYSE, and NASDAQ , driving the discussion on the impact of AI on sales. Aviso is backed by

Storm Ventures, Scale Venture Partners, Shasta Ventures, and other leading Silicon Valley investors.

The Role Multiple teams are building with LLMs using different frameworks. You'll build the unified observability and governance layer that works across all of them — tracing, cost attribution, token tracking, and policy enforcement. This is platform engineering for AI systems. You won't tune prompts or train models. You'll build infrastructure that helps teams ship AI features reliably with full visibility into performance, failures, and costs.

What You'll Do Design unified observability across LangChain, LlamaIndex, raw API calls, and future frameworks Build tracing, cost attribution, and token tracking systems Create dashboards and alerting for LLM-specific metrics Establish governance: model allow-lists, rate limiting, budget controls Work with application teams to instrument their services with minimal friction

Requirements Must Have

- 6-8 years in DevOps, Platform Engineering, SRE, or MLOps - Strong observability experience: distributed tracing, metrics, logging - Python proficiency; Docker and Kubernetes hands-on - Infrastructure-as-code (Terraform, Pulumi, or CloudFormation) - AWS experience (GCP/Azure acceptable) Preferred

- Exposure to LLM frameworks (LangChain, LlamaIndex, or similar) - Understanding of LLM concerns: tokens, rate limits, cost per call - Experience building internal platforms or developer tooling

Tech Stack AWS, Kubernetes (EKS), Terraform, OpenTelemetry, Grafana, Python, TypeScript LLM Providers: OpenAI, Anthropic | Frameworks: LangChain, LlamaIndex (varies by team)

Explore Aviso AI in Action Explore how Aviso AI transforms enterprise sales with AI-powered revenue intelligence: Sales Video

→

Watch Here Inbound Avatar (AI SDR for inbound)

→ Watch Demo AI Sales Engineer – Senna (Deal Support)

→ Watch Demo Sales SME AI Demo (Expert in a Box)

→ Watch Demo MIKI – On-Call AI Assistance

→ Watch Video Norman – Sales Coaching Avatar

→ Watch Video Customer Story – Lenovo

→ Watch Here Customer Story – NetApp

→ Watch Here Customer Story – BMC

→ Watch Here

Interested?

Apply now and be part of our mission to revolutionize revenue operations with AI.