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AI voice and chat agents for customer service contact centers.

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About Observe.AI

The company, in brief.

What they do

Observe.AI sells AI agents for customer service. Voice and chat agents resolve conversations alone, and a companion agent helps live contact center staff. Other agents do analysis and coaching. More than 350 enterprises in banking, health care, insurance, and travel use it. The company started in 2017.

What they value

  • AI helps people and does not replace them.
  • Authenticity and curiosity.
  • Good work with others in a fast, customer-first setting.

Where they hire

Roles are in Bengaluru, the United States, and Canada. Redwood City roles are hybrid, and some sales and agent engineering roles are remote in the US. Bengaluru postings do not state an arrangement. India has technical roles in machine learning, security, and support, plus design, customer success, and sales roles.

Teams and roles

The engineering board is small. The one software engineering role is entry level in Redwood City, and there are no product management roles.

  • Machine learning (Bengaluru): senior engineer for LLM features and multi-agent systems on pipelines with millions of interactions a day. Three or more years of large-scale NLP, and Python with PyTorch or Hugging Face.
  • Software engineering: Python, TypeScript, and Go on agent pipelines, RAG, evaluations, and voice systems.
  • Security (Bengaluru): staff engineer to redesign AWS security and support SOC and HITRUST audits, with out-of-hours incident work.
  • Support: troubleshoot with SQL, MongoDB, and logs.
  • Deployment: pods build agents for each customer. Agent engineers write prompts and integrate APIs and telephony.

A Bengaluru engagement manager leads a deployment pod. A Bengaluru interaction designer configures speech analytics.

What they look for

A strong candidate shows AI or contact center work that reached production and explains it clearly to customers. The ML role values papers at venues such as EMNLP and ACL. Interviews are a two-way conversation about real scenarios and past projects. Candidates meet peers, leaders, or partner teams, depending on the role.

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