Observe.AI
About this role
Observe.AI builds AI agents for customer service, used by DoorDash, Affordable Care, Signify Health and Verida. This is a client facing delivery role and the posting is explicit that you would not be building foundation models: you would deploy voice and chat agents inside customer environments. That means prompt design, workflow configuration, API integrations into CRMs and knowledge bases, telephony setup across SIP, CCaaS and PSTN, and the evaluation frameworks that prove an agent hits its containment targets. You would own the lifecycle from design through demos to production and iteration, and be the customer's main technical contact. It asks 3+ years and names LLM tooling directly, including GPT, Claude and Gemini, vector databases, LangChain and LlamaIndex, and RAG patterns.
Who this is for
What the posting asks for:
- A bachelor's degree in computer science, engineering or a related technical field.
- 3+ years in conversational AI, solution engineering, system integration, or delivering AI and LLM based applications in customer environments.
- Strong ability to lead customer facing discussions, from deep technical troubleshooting to weekly project demos, and to explain complex concepts to non technical audiences.
- Strong hands on skills in prompt design, workflow building and API integration (SIP, Twilio, Amazon Connect and similar).
- Familiarity with LLMs (GPT, Claude, Gemini), vector databases, and orchestration frameworks such as LangChain and LlamaIndex.
- Working knowledge of retrieval augmented generation: concepts, implementation patterns and performance optimisation.
- Programming experience in Python, JavaScript or similar for scripting and integrations.
- A strong problem solving mindset, finding workarounds and adapting to each customer's ecosystem.
Counts as a bonus:
- Integration platforms such as n8n or Zapier, and proficiency in API integration and data flow management.
- Familiarity with telephony or voice systems (SIP, CCaaS, PSTN).
The day to day: owning AI agent implementation including prompt design, workflow configuration, integrations, telephony setup and evaluation frameworks; acting as the primary technical partner for customers through demos and feedback; configuring API integrations with authentication, data mapping and error handling; setting up SIP, CCaaS and PSTN routing and troubleshooting call quality; refining prompts and monitoring performance against automation and containment targets; and escalating platform gaps to product and engineering.
Experience: the posting states 3+ years, and accepts several entry paths into that (conversational AI, solution engineering, system integration or software engineering with AI delivery).
Location: Bengaluru.
Benefits listed: medical insurance for self and family with free online doctor consultations, accident and group term life insurance, privilege and sick leave, parental leave, an annual learning and development allowance, and flexible tax benefits including meal cards.
Who should apply: someone three or more years in who wants applied LLM work with a real deployment target and does not mind that the customer is in the room. If you want to train models, this is the wrong role and Sarvam's postings in today's list are the right ones.
- A bachelor's degree in computer science, engineering or a related technical field.
- 3+ years in conversational AI, solution engineering, system integration, or delivering AI and LLM based applications in customer environments.
- Strong ability to lead customer facing discussions, from deep technical troubleshooting to weekly project demos, and to explain complex concepts to non technical audiences.
- Strong hands on skills in prompt design, workflow building and API integration (SIP, Twilio, Amazon Connect and similar).
- Familiarity with LLMs (GPT, Claude, Gemini), vector databases, and orchestration frameworks such as LangChain and LlamaIndex.
- Working knowledge of retrieval augmented generation: concepts, implementation patterns and performance optimisation.
- Programming experience in Python, JavaScript or similar for scripting and integrations.
- A strong problem solving mindset, finding workarounds and adapting to each customer's ecosystem.
Counts as a bonus:
- Integration platforms such as n8n or Zapier, and proficiency in API integration and data flow management.
- Familiarity with telephony or voice systems (SIP, CCaaS, PSTN).
The day to day: owning AI agent implementation including prompt design, workflow configuration, integrations, telephony setup and evaluation frameworks; acting as the primary technical partner for customers through demos and feedback; configuring API integrations with authentication, data mapping and error handling; setting up SIP, CCaaS and PSTN routing and troubleshooting call quality; refining prompts and monitoring performance against automation and containment targets; and escalating platform gaps to product and engineering.
Experience: the posting states 3+ years, and accepts several entry paths into that (conversational AI, solution engineering, system integration or software engineering with AI delivery).
Location: Bengaluru.
Benefits listed: medical insurance for self and family with free online doctor consultations, accident and group term life insurance, privilege and sick leave, parental leave, an annual learning and development allowance, and flexible tax benefits including meal cards.
Who should apply: someone three or more years in who wants applied LLM work with a real deployment target and does not mind that the customer is in the room. If you want to train models, this is the wrong role and Sarvam's postings in today's list are the right ones.
Apply on company site
Opens job-boards.greenhouse.io, the employer's own application page. Applying is always free.