Software Engineer - Applied AI | Selector · Teeming.ai
Selector
Selector AI is the industry leading AIOps platform designed to provide instant, real-time actionable insights for managing multi-domain network and application infrastructures. By bringing together multiple sources of data into one easy to use platform, IT teams can troubleshoot network issues faster, avoid downtime, reduce MTTR and improve efficiency.
Selector AI is the industry leading AIOps platform designed to provide instant, real-time actionable insights for managing multi-domain network and application infrastructures. By bringing together multiple sources of data into one easy to use platform, IT teams can troubleshoot network issues faster, avoid downtime, reduce MTTR and improve efficiency.
Product: AI-driven AIOps/observability platform with Network Language Model
Recent funding: Series B ~ $33M (Nov 2024); additional $32M round announced Feb 2026
Employees (approx.): 143
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Company Overview
Problem Domain
Network, infrastructure, and application observability/AIOps
Founded
2019
Industry
Software Development
Funding Track Record
Series A- March 2022
$28M
Series B- November 2024
$33M
- February 18, 2026
$32M
Round announced with participation from existing investors
Investor Signal
“Combination of venture and strategic corporate investors including Two Bear Capital, Atlantic Bridge, SineWave Ventures, Ansa Capital, AT&T Ventures, Bell Ventures, Comcast Ventures, and Singtel Innov8”
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What we do
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Software Engineer - Applied AI
On-SiteSanta Clara, CA, US
On-Site • Santa Clara, CA, US
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Software Engineer - Applied AI
Selector AI
Software Engineering, Data Science
Santa Clara, CA, USA
USD 130k-160k / year
Posted on Sep 13, 2025
Apply now
About Us
Selector is building an operational intelligence platform for digital infrastructure. By adopting an AI/ML-based analytics approach, the platform provides actionable multi-dimensional insights to network, cloud, and application operators. It enables operations teams to meet their KPIs through seamless collaboration, search-driven conversational user experience, and automated data engineering pipelines.
Our solutions are used by leading Telecoms, Media Providers, Retail, and Professional Sports organizations across the world. Our novel approach and rapidly expanding footprint put us in the unique position for continued growth to become a category leader. To fuel our growth, we are seeking passionate, high-energy, results-oriented individuals to join our team.
Our mission is to deliver world-class solutions on behalf of the large enterprise. Supported by leading investors, Selector is uniquely positioned to deliver a world-class solution to address large enterprise requirements across the globe.
Selector offers a discretionary PTO policy, health insurance, 401k, the opportunity for a bonus, and more.
Key Responsibilities
Design, build, and optimize agentic AI systems that power Selector’s operational intelligence platform.
Leverage emerging frameworks (e.g., pydantic-ai, LangChain) and evaluate new agentic AI technologies to accelerate development and maintain cutting-edge capabilities.
Requirements
Bachelor’s or Master’s degree in Computer Science, Data Science, or related technical field; or equivalent practical experience.
Compensation
The salary for this role is $130,000 - $160,000. Final offer amounts are determined by multiple factors, including prior experience, and may vary from the amount listed.
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Develop empirical pipelines for measuring and assessing agent performance, ensuring all prompt and model changes are backed by data-driven evidence and quantifiable improvement.
Implement advanced Natural Language Processing (NLP) techniques to translate natural language queries into complex structured queries against operational data sources.
Design human-in-the-loop workflows for error detection, correction, and refinement—enabling agents to prompt for clarifications when necessary.
Build transparent tracking mechanisms for agent thoughts, decisions, and observations throughout iterative task flows to improve interpretability, debugging, and trust.
Evaluate and apply different agent paradigms (ReAct, reflex, goal-based, utility-based, etc.) to align agent behavior with specific task requirements.
Collaborate cross-functionally with data engineers, product managers, and customer success teams to ensure AI-driven features align with customer needs and business outcomes.
Contribute to the evolution of Selector’s conversational UX, making agent interactions more natural, reliable, and contextually aware.
3-5 years of software engineering experience, with at least 1 year of experience building Agentic AI systems
Strong programming skills in Python and familiarity with modern AI/ML ecosystems.
Experience building or integrating agent-based systems using frameworks such as pydantic-ai, LangChain, or similar.
Solid understanding of Natural Language Processing and prompt engineering techniques.
Proven ability to design metrics-driven evaluation pipelines for AI/LLM performance testing.
Knowledge of agent reasoning strategies (e.g., ReAct, reflexive, goal-driven, utility-based) and practical experience choosing among them.
Familiarity with human-in-the-loop systems, error handling, and recovery strategies.
Strong problem-solving, analytical, and debugging skills, with attention to reproducibility and system robustness.
Excellent communication skills, with the ability to collaborate in a fast-paced startup environment.
Bonus: Experience with operational data domains (networking, cloud, application performance) or conversational UX design.
