A
Forward Deployed Engineer
Accepting applicationsAurora · India
Full-Time Entry AIPythonaiateetch
Posted
3d ago
Category
Test
Experience
Entry
Country
India
Forward Deployed Engineer — Agentic Search Infrastructure
Fully remote
Full-time
€30k–€85k, depending on location and experience
The company
This is an early-stage infrastructure company building the web access layer for AI agents.
AI systems increasingly need to search, extract, and structure information from the open web. Most of that workflow is still brittle: dynamic websites, inconsistent HTML, rate limits, noisy pages, incomplete context, and extraction pipelines that break when pages change.
The company is building an API that lets agents interact with web data reliably: search, retrieve, parse, structure, and use information from the web without every team rebuilding the same infrastructure from scratch.
The bet is simple: over the next few years, AI agents will become one of the main users of the web. They will need infrastructure built for machines, not humans.
The role
You will be the technical bridge between the product and its most important users.
This is not a traditional sales engineering role. You will write code, run technical discovery, build proof-of-concepts, debug customer workflows, and translate real usage into product and engineering feedback.
You will work with developers, founders, and engineering leaders who are trying to use web data inside AI systems. Your job is to understand what they are building, show how the API fits into their architecture, and help turn vague use cases into working technical implementations.
The right person is a strong software engineer who enjoys customer-facing work and wants to be close to where product, infrastructure, and market demand meet.
The technical problem
The web was designed for humans clicking through pages, not for thousands of agents making structured decisions from messy information.
A good API abstraction has to handle much more than fetching pages. It needs to support:
Search and retrieval across noisy, fast-changing web sources.
Reliable extraction from dynamic websites and inconsistent page structures.
Structured outputs that can be used directly inside agent workflows.
Prompting and context configuration that make the system useful across different customer use cases.
Latency, reliability, and error handling good enough for production workflows.
Developer experience that makes the API obvious to adopt, test, and scale.
The hard part is not building one impressive demo. The hard part is helping customers move from demo to repeatable workflow, then feeding those patterns back into the product.
What you’ll own
Technical discovery: understand what customers are trying to build, where web data fits, and what constraints matter in their workflow.
Proofs of concept: build tailored examples, scripts, and API integrations that show the product working on real customer problems.
Demos for technical users: explain the system clearly to developers, engineering leaders, and technical founders.
Solution design: turn customer requirements into practical rollout plans across search, extraction, prompting, context design, and structured outputs.
Customer technical advisory: become the person customers trust when they are evaluating how to use the platform in production.
Product feedback: identify repeated failure modes, missing features, unclear APIs, and edge cases from real usage.
Hands-on product contribution: work directly with Product and Engineering on improvements when customer problems expose product gaps.
Developer education: create clear examples, guides, and internal patterns that reduce friction for future customers.
Who this is for
You are likely a strong fit if you have:
Strong software engineering fundamentals. You can reason through APIs, systems, data flow, failure modes, and tradeoffs.
Hands-on coding ability. You are comfortable building working examples, debugging integrations, and reading technical docs quickly.
High verbal clarity in English. You can explain technical ideas simply without losing precision.
Customer-facing judgment. You listen carefully, ask sharp questions, and understand what the customer is actually trying to achieve.
Autonomy. You can operate without a detailed task list and still converge on useful outcomes.
Interest in search, retrieval, agents, or AI-native infrastructure. Direct search infrastructure experience is helpful, but not required.
Taste for product. You care about whether developers understand, adopt, and continue using what you help build.
Low ego, high standards. You can switch between writing code, running a demo, debugging a workflow, and giving product feedback.
Top candidates will be able to explain a customer problem, reduce it to the right technical abstraction, build the first working version, and identify what should become productized.
Nice to have
Experience with APIs, SDKs, scraping, browser automation, search, retrieval, RAG, LLM agents, or data extraction.
Experience working with technical founders, engineering teams, or developer-facing products.
Startup experience, especially in small teams with high ambiguity.
Familiarity with Python, TypeScript, web infrastructure, or modern AI tooling.
This role is not for you if
You want a pure backend role with no customer interaction.
You want a pure sales role without technical ownership.
You are uncomfortable speaking with developers and engineering leaders.
You need highly defined tasks before making progress.
You do not enjoy debugging messy, real-world workflows.
You prefer large-company structure over small-team autonomy.
Culture
The team is young, technical, and results-oriented.
The operating style is closer to a sports team than a corporate department:
Results matter more than hours tracked.
Autonomy is the default.
Clear objectives matter more than process.
Learning speed matters.
People are expected to take ownership without waiting for permission.
This is a good environment for someone who wants responsibility early and does not need layers of management to move.
Why now
The product sits at the intersection of three fast-moving shifts:
AI agents need reliable access to web data.
Developers need infrastructure that abstracts away brittle scraping and extraction work.
Companies are starting to build workflows where agents search, retrieve, and structure information continuously.
The company is still early enough that a FD Engineer can influence more than individual deals. The patterns you discover with customers can shape product direction, API design, onboarding, examples, and the company’s understanding of the market.
For someone who wants to work close to frontier AI adoption without being isolated from users, this is the highest-leverage part of the company.
Compensation and logistics
Compensation: €30k–€85k, depending on location and experience.
Location: fully remote - Company is based in San Francisco and Italy.
Language: fluent English required.
Role type: full-time - B2B contract preferred.
Function: customer-facing engineering, between software engineering, product, and technical sales.
About Aurora
Aurora helps exceptional engineers find roles at some of the most ambitious startups worldwide.
We work with teams that value high ownership, strong technical standards, and direct impact.
Show more Show less
Fully remote
Full-time
€30k–€85k, depending on location and experience
The company
This is an early-stage infrastructure company building the web access layer for AI agents.
AI systems increasingly need to search, extract, and structure information from the open web. Most of that workflow is still brittle: dynamic websites, inconsistent HTML, rate limits, noisy pages, incomplete context, and extraction pipelines that break when pages change.
The company is building an API that lets agents interact with web data reliably: search, retrieve, parse, structure, and use information from the web without every team rebuilding the same infrastructure from scratch.
The bet is simple: over the next few years, AI agents will become one of the main users of the web. They will need infrastructure built for machines, not humans.
The role
You will be the technical bridge between the product and its most important users.
This is not a traditional sales engineering role. You will write code, run technical discovery, build proof-of-concepts, debug customer workflows, and translate real usage into product and engineering feedback.
You will work with developers, founders, and engineering leaders who are trying to use web data inside AI systems. Your job is to understand what they are building, show how the API fits into their architecture, and help turn vague use cases into working technical implementations.
The right person is a strong software engineer who enjoys customer-facing work and wants to be close to where product, infrastructure, and market demand meet.
The technical problem
The web was designed for humans clicking through pages, not for thousands of agents making structured decisions from messy information.
A good API abstraction has to handle much more than fetching pages. It needs to support:
Search and retrieval across noisy, fast-changing web sources.
Reliable extraction from dynamic websites and inconsistent page structures.
Structured outputs that can be used directly inside agent workflows.
Prompting and context configuration that make the system useful across different customer use cases.
Latency, reliability, and error handling good enough for production workflows.
Developer experience that makes the API obvious to adopt, test, and scale.
The hard part is not building one impressive demo. The hard part is helping customers move from demo to repeatable workflow, then feeding those patterns back into the product.
What you’ll own
Technical discovery: understand what customers are trying to build, where web data fits, and what constraints matter in their workflow.
Proofs of concept: build tailored examples, scripts, and API integrations that show the product working on real customer problems.
Demos for technical users: explain the system clearly to developers, engineering leaders, and technical founders.
Solution design: turn customer requirements into practical rollout plans across search, extraction, prompting, context design, and structured outputs.
Customer technical advisory: become the person customers trust when they are evaluating how to use the platform in production.
Product feedback: identify repeated failure modes, missing features, unclear APIs, and edge cases from real usage.
Hands-on product contribution: work directly with Product and Engineering on improvements when customer problems expose product gaps.
Developer education: create clear examples, guides, and internal patterns that reduce friction for future customers.
Who this is for
You are likely a strong fit if you have:
Strong software engineering fundamentals. You can reason through APIs, systems, data flow, failure modes, and tradeoffs.
Hands-on coding ability. You are comfortable building working examples, debugging integrations, and reading technical docs quickly.
High verbal clarity in English. You can explain technical ideas simply without losing precision.
Customer-facing judgment. You listen carefully, ask sharp questions, and understand what the customer is actually trying to achieve.
Autonomy. You can operate without a detailed task list and still converge on useful outcomes.
Interest in search, retrieval, agents, or AI-native infrastructure. Direct search infrastructure experience is helpful, but not required.
Taste for product. You care about whether developers understand, adopt, and continue using what you help build.
Low ego, high standards. You can switch between writing code, running a demo, debugging a workflow, and giving product feedback.
Top candidates will be able to explain a customer problem, reduce it to the right technical abstraction, build the first working version, and identify what should become productized.
Nice to have
Experience with APIs, SDKs, scraping, browser automation, search, retrieval, RAG, LLM agents, or data extraction.
Experience working with technical founders, engineering teams, or developer-facing products.
Startup experience, especially in small teams with high ambiguity.
Familiarity with Python, TypeScript, web infrastructure, or modern AI tooling.
This role is not for you if
You want a pure backend role with no customer interaction.
You want a pure sales role without technical ownership.
You are uncomfortable speaking with developers and engineering leaders.
You need highly defined tasks before making progress.
You do not enjoy debugging messy, real-world workflows.
You prefer large-company structure over small-team autonomy.
Culture
The team is young, technical, and results-oriented.
The operating style is closer to a sports team than a corporate department:
Results matter more than hours tracked.
Autonomy is the default.
Clear objectives matter more than process.
Learning speed matters.
People are expected to take ownership without waiting for permission.
This is a good environment for someone who wants responsibility early and does not need layers of management to move.
Why now
The product sits at the intersection of three fast-moving shifts:
AI agents need reliable access to web data.
Developers need infrastructure that abstracts away brittle scraping and extraction work.
Companies are starting to build workflows where agents search, retrieve, and structure information continuously.
The company is still early enough that a FD Engineer can influence more than individual deals. The patterns you discover with customers can shape product direction, API design, onboarding, examples, and the company’s understanding of the market.
For someone who wants to work close to frontier AI adoption without being isolated from users, this is the highest-leverage part of the company.
Compensation and logistics
Compensation: €30k–€85k, depending on location and experience.
Location: fully remote - Company is based in San Francisco and Italy.
Language: fluent English required.
Role type: full-time - B2B contract preferred.
Function: customer-facing engineering, between software engineering, product, and technical sales.
About Aurora
Aurora helps exceptional engineers find roles at some of the most ambitious startups worldwide.
We work with teams that value high ownership, strong technical standards, and direct impact.
Show more Show less