Hevo Data
About this role
The one role in today's list with no lower experience bound at all. Hevo states up to 5 years, which is a ceiling rather than a floor, so someone early in their career is genuinely eligible. Hevo runs a data pipeline platform processing more than 100 billion records a month, and this role builds internal AI applications that make its go to market teams faster: tools built on LLM APIs, integrations into HubSpot, Salesforce, LinkedIn and Google Sheets, and automations for data enrichment and reporting. The work is prototype heavy, testing new models and APIs and turning the ones that hold up into things people actually use. The stack is Python, REST and GraphQL APIs, and Flask, FastAPI or Streamlit.
Who this is for
What the posting asks for:
- Up to 5 years of experience building end to end applications. Read that carefully: it is an upper bound, not a minimum, which is why this role is open to people early in their careers.
- A strong understanding of AI and machine learning fundamentals: NLP, LLMs, embeddings and prompt engineering.
- Proficiency in Python and working with REST or GraphQL APIs.
- Experience with prototyping frameworks such as Flask, FastAPI or Streamlit.
- Familiarity with go to market systems such as Salesforce, HubSpot or Marketo, or BI tools such as Tableau or Looker.
- Strong problem solving skills and the ability to prototype quickly.
Abilities the posting calls out separately:
- Turning messy go to market data into usable inputs for AI models.
- Mapping AI outputs back into real workflows and processes.
- Explaining technical solutions clearly to non technical people.
- Balancing fast experimentation against reliability and compliance.
The day to day: building internal applications on LLMs and AI APIs such as OpenAI and Anthropic, integrating AI into go to market tools, writing scripts and automations for data enrichment and reporting, rapidly testing new models and APIs and building MVPs, documenting performance and accuracy for each use case, working with Marketing, Sales and BizOps to find their pain points, running demos and training for internal users, and maintaining what you deploy.
How success is measured, which the posting states unusually clearly: two or three working AI prototypes that go to market teams actively use, at least two workflows automated or optimised, documentation good enough to make the work transferable, and measurable gains in productivity.
Experience: up to 5 years, with no minimum stated anywhere in the posting.
Location: Bangalore.
Who should apply: anyone from roughly zero to five years who can actually build with LLM APIs and wants a role where shipping a working prototype counts more than pedigree. The honest caveat is that these are internal tools for sales and marketing teams, not customer facing product engineering, so weigh that against the low bar to entry.
- Up to 5 years of experience building end to end applications. Read that carefully: it is an upper bound, not a minimum, which is why this role is open to people early in their careers.
- A strong understanding of AI and machine learning fundamentals: NLP, LLMs, embeddings and prompt engineering.
- Proficiency in Python and working with REST or GraphQL APIs.
- Experience with prototyping frameworks such as Flask, FastAPI or Streamlit.
- Familiarity with go to market systems such as Salesforce, HubSpot or Marketo, or BI tools such as Tableau or Looker.
- Strong problem solving skills and the ability to prototype quickly.
Abilities the posting calls out separately:
- Turning messy go to market data into usable inputs for AI models.
- Mapping AI outputs back into real workflows and processes.
- Explaining technical solutions clearly to non technical people.
- Balancing fast experimentation against reliability and compliance.
The day to day: building internal applications on LLMs and AI APIs such as OpenAI and Anthropic, integrating AI into go to market tools, writing scripts and automations for data enrichment and reporting, rapidly testing new models and APIs and building MVPs, documenting performance and accuracy for each use case, working with Marketing, Sales and BizOps to find their pain points, running demos and training for internal users, and maintaining what you deploy.
How success is measured, which the posting states unusually clearly: two or three working AI prototypes that go to market teams actively use, at least two workflows automated or optimised, documentation good enough to make the work transferable, and measurable gains in productivity.
Experience: up to 5 years, with no minimum stated anywhere in the posting.
Location: Bangalore.
Who should apply: anyone from roughly zero to five years who can actually build with LLM APIs and wants a role where shipping a working prototype counts more than pedigree. The honest caveat is that these are internal tools for sales and marketing teams, not customer facing product engineering, so weigh that against the low bar to entry.
Apply on company site
Opens jobs.lever.co, the employer's own application page. Applying is always free.