Hybrid opportunity at
FreshworksPrincipal Engineer - Machine Learning
Freshworks' AI/ML Engineering team is hiring a Principal Engineer for Machine Learning to set the architecture and technical direction for backend services behind its Agentic AI…
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About This Role
Freshworks' AI/ML Engineering team is hiring a Principal Engineer for Machine Learning to set the architecture and technical direction for backend services behind its Agentic AI Platform. The full-time role is hybrid. It supports the platform that delivers autonomous AI features across the company's enterprise product suite, and it includes setting engineering standards and mentoring senior engineers. The engineer would lead design of runtime services for agents, which handle reasoning,…
Job Description
Freshworks' AI/ML Engineering team is hiring a Principal Engineer for Machine Learning to set the architecture and technical direction for backend services behind its Agentic AI Platform. The full-time role is hybrid. It supports the platform that delivers autonomous AI features across the company's enterprise product suite, and it includes setting engineering standards and mentoring senior engineers.
The engineer would lead design of runtime services for agents, which handle reasoning, planning, tool calls and fast execution. Other areas include stateful dialogue management, shared context and memory, and messaging protocols that let agents coordinate. The role also drives a move toward cloud-native, event-driven microservices, lowers LLM cost and latency through caching, batching, token tracking and model routing, and oversees retrieval pipelines backed by vector stores with end-to-end tracing.
The person defines APIs and SDKs for internal teams and outside partners, and sets expectations for automated testing and tenant isolation. Hybrid attendance is three office days per week, Tuesday through Thursday. Twelve to eighteen years of combined software and ML experience is expected.
Responsibilities
- Lead design and delivery of agent runtime orchestration covering reasoning, planning, tool use and low-latency execution.
- Define developer-friendly APIs and SDKs for internal teams and ecosystem partners.
- Create dialogue state handling plus shared memory services for agents that run many turns.
- Set agent-to-agent communication patterns and shared memory for multi-agent work.
- Direct the transition to cloud-native, event-driven services with service mesh and streaming.
- Bring in caching strategies, request batching, token tracking and smart model selection.
- Oversee enterprise retrieval pipelines, vector database integration and tracing.
- Set standards for test automation and multi-tenant access control, and mentor senior engineers.
Requirements
- Twelve to eighteen years of progressive experience building ML and software systems.
- Track record designing scalable enterprise backend platforms.
- Deep Java and Python skills.
- Hands-on production use of agent frameworks such as LangChain, LangGraph and LangSmith, and workflow engines such as Temporal or Airflow.
- Strong grasp of event-driven design, microservices, Kubernetes, Kafka, AWS and mixed database types including PostgreSQL and vector stores.
- Skill at turning business and AI goals into multi-year platform plans.
Qualifications
- Exposure to AI planning engines, dialogue state tracking, or RL-based feedback loops in production.
- Practical use of enterprise identity and access standards, including single sign-on, OAuth2, RBAC and tenant separation.
- Taking part in open-source AI or ML work, or contributing code to widely used LLM or orchestration libraries.
Core Skills
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Where is this job located?
The posting does not specify a city or office location. The role is hybrid, with in-office presence three days a week, Tuesday through Thursday.
How much experience is required?
The posting asks for twelve to eighteen years in software engineering and ML system development, with growing responsibility.
Which technologies are required?
Deep Java and Python skills are required, along with experience with agent frameworks such as LangChain, LangGraph and LangSmith, and with Kubernetes, Kafka and AWS.
Is a salary listed?
The posting does not state a salary or pay range.
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