AI Professional Services Engineer

Kaltura

. Work as a hands-on engineer in an AI Professional Services (Forward-Deployed) Engineering pod .

Posted 11/9/2026full-timeNew York City • New York • United StatesJuniorMid-Level💰 $105,000 - $130,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying backend services, distributed systems, and APIs, with a strong focus on AI applications and microservices. Proven ability to lead technical delivery and collaborate with external engineering teams while ensuring continuous improvement through observability and tuning.

Highest-signal resume keywords

Production Software EngineeringBackend Services DevelopmentPython ProgrammingTechnical LeadershipMicroservices Architecture

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Backend ServicesDistributed SystemsAPIsPythonTypeScriptNode.jsGoStateful Agent WorkflowsContinuous TuningArchitecture Reviews

Soft Skills

CollaborationProblem-SolvingTechnical Requirement Extraction

Tools & Technologies

MicroservicesAI ApplicationsModel Context Protocol (MCP)Observation TechniquesRegression Suites

Industry Keywords

Agentic SystemsASR Domain Vocabulary BiasingTTS Pronunciation TuningTenant IsolationCross-Tenant Context Leakage

Tech Stack

Tools & technologies

Distributed SystemsJavaScriptMicroservicesNode.jsPythonTypeScriptGo

About the role

Key responsibilities & impact

Work as a hands-on engineer in an AI Professional Services (Forward-Deployed) Engineering pod
Embed with priority enterprise customers and own technical delivery from initial discovery and prototyping through stable production
Build customer-specific capabilities that deliver immediate operational value
Develop production skills and agents using microservices and AI applications
Create automated evaluation suites with ground-truth test scenarios, golden datasets, and regression suites
Measure semantic correctness, tool-call fidelity, and behavioral stability
Implement observability and continuous tuning
Conduct architecture reviews and design agentic systems
Collaborate with external engineering teams as a technical lead

Requirements

What you’ll need

2+ years in production software engineering
Deep hands-on experience building backend services, distributed systems, and APIs
Proficiency in Python, TypeScript/Node.js, or Go
Direct experience building and deploying stateful agent workflows, tool/function calling, structured outputs, context window optimization, and production RAG pipelines
Proven experience acting as a technical lead with external engineering teams
Ability to conduct architecture reviews and design agentic systems
Ability to extract technical requirements from complex enterprise environments and ambiguous business problems
Familiarity with microservices, AI applications, and products
Familiarity with observation and measurement techniques for continuous tuning
Strongly preferred: hands-on experience authoring or consuming Model Context Protocol (MCP) servers and clients
Strongly preferred: background in ASR domain vocabulary biasing and TTS pronunciation tuning
Strongly preferred: experience enforcing strict tenant isolation and preventing cross-tenant context leakage

Benefits

Comp & perks

Hybrid work model
Flexible state of mind
Diverse and collaborative work environment
Opportunities for growth and evolution