Selector AI
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. 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. Requirements Bachelor’s or Master’s degree in Computer Science, Data Science, or related technical field; or equivalent practical experience. 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 . 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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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. 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. Requirements Bachelor’s or Master’s degree in Computer Science, Data Science, or related technical field; or equivalent practical experience. 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 . 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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