AI Professional Services Engineer

Location: New York (US)

Description

This is us 

Kaltura’s (NYSE:KLTR) mission is to power any video experience for any organization – live, on-demand, or real-time. We not only want to make using video simpler, but we also want to better people’s lives through video. Founded in 2006, Kaltura is now a global leader in the video market with millions of people using our products daily to teach, learn, watch, connect, and collaborate. Among our customers, you’ll find more than 1000 global, well-known organizations.

15+ years since starting the company, we continue to foster a diverse and collaborative work environment where everyone gets a say. Our team is currently 700+ people, and we’re still growing. We have offices in New York, London, Singapore, and Tel Aviv, but our technology is all in the cloud. 

Kaltura has a fast-paced environment where initiative is always encouraged. Together with our hybrid work model and flexible state of mind, you get the right conditions for creative juices to flow freely. Thanks to our long line of products, cultivation of rich collaborative culture and care for each Kalturian, you’ll never run out of room to grow and evolve.

If you don't meet 100% of the requirements below - that's okay, nobody's perfect! We believe in hiring people, not just a list of skills. We encourage you to apply if you think this is a role that would make you excited about coming to work every day. 

Requirements

The Role

You are a hands-on engineer in an AI Professional Services (Forward-Deployed) Engineering pod — a small team embedded with priority enterprise customers, owning technical delivery from initial discovery and prototyping through to stable production. You build customer-specific capabilities that deliver immediate operational value and become durable platform primitives when proven broadly useful.

Scope & What You Build

• Production Skills & Agents: understanding of microservices, AI applications and product
• Automated Evaluation Suites: Ground-truth test scenarios, golden datasets, and regression suites measuring semantic correctness, tool-call fidelity, and behavioral stability. 
• Observability & Continuous Tuning: be familiar and up to date on observation and measuring techniques

Requirements

• 2+ years in production software engineering: Deep hands-on experience building backend services, distributed systems, and APIs in Python, TypeScript/Node.js, or Go. You personally write, review, and ship production code.
• Production LLM & Agentic AI systems: Direct experience building and deploying stateful agent workflows, tool/function calling, structured outputs, context window optimization, and production RAG pipelines (hybrid search, semantic chunking, re-ranking).
• Customer-facing technical ownership: Proven experience acting as a technical lead with external engineering teams (Forward-Deployed Engineer, Solutions Engineer with production code ownership, or founding engineer). 
• Design and Understand Architecture: Able to conduct architecture reviews and designing agentic systems
• Discovery under ambiguity: Ability to enter complex, unfamiliar enterprise environments, extract technical requirements from messy business problems, and rapidly design working systems.

Strongly Preferred

• Model Context Protocol (MCP): Hands-on experience authoring or consuming MCP servers and clients to standardize agent tool interoperability.
• Speech pipelines: Background in ASR domain vocabulary biasing and TTS pronunciation tuning.
• Multi-tenant architecture: Experience enforcing strict tenant isolation and preventing cross-tenant context leakage.

The annual base salary range provided for this position is a nationwide market range and represents a broad range of salaries for this role across the country. The actual salary for this position will be determined by a number of factors, including the scope, complexity and location of the role; the skills and experience of the candidate; and other conditions of employment.

Salary Range: $105,000 - $130,000 USD