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Sycamore

India, Forward Deployed & Product Engineer

BengaluruIndia
FullTime · Engineering - India
POSTED 22 OCTVERIFIED 33M AGO
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Pay · market
₹22.3L–₹31.2L
p25–p75 · n=4
Open for
13d
since 22 Oct
Hiring · 30d
17
+14 net · open roles
TypeScriptReactCSSPythonFastAPIPostgreSQLKubernetes

About Sycamore

Sycamore is building the trusted agent operating system for the enterprise. Our platform helps companies build, deploy, and orchestrate agentic apps that take on real operational work, with the security and control large organizations need.

We are a small, engineering-led team working directly with Fortune 500 enterprises. We have raised $65M from Coatue and Lightspeed, along with other investors and industry leaders.

The role

The simplest way to describe this role: you are the engineer in the customer room and the product engineer who ships what the room needs.

You will map how an important workflow works today, identify where an agent can create a measurable outcome, and build the application end to end. That can include the user experience, APIs and data model, agent instructions and tools, enterprise integrations, permissions, approval points, durable workflows, and the operational controls needed to run safely.

You own the full loop: discovery, implementation, realistic testing, preview and deployment, production debugging, adoption, and iteration. Your work does not end with a prototype, a requirements document, or a handoff.

Customer-specific product work belongs with you. When the same runtime, connector, memory, approval, or deployment need appears repeatedly, you work with Core AI or Infrastructure to turn it into a reusable capability instead of maintaining parallel custom implementations.

What the work looks like

In one week, you might:

Sit with a customer's operators and engineering team to map a manual process, its domain entities, edge cases, permissions, approval points, and success criteria.

Trace how the workflow connects to existing systems and determine which reads and writes an agent can perform safely.

Build a production application across the user interface, backend APIs, data model, agent behavior, tools, integrations, and human-review surfaces.

Exercise the real workflow in a browser, run backend and end-to-end tests, inspect traces and structured events, and fix failures before users encounter them.

Deploy a preview or development version, work through customer security and networking constraints, and stay close to usage after launch.

Separate the customer's specific business behavior from a reusable platform pattern, then contribute the shared primitive with the relevant Core AI or Infrastructure engineer.

What you will do

Turn ambiguous enterprise problems into clear technical designs, working software, and measurable outcomes.

Build product surfaces for agent conversations, tasks, progress, approvals, artifacts, and operational workflows.

Design APIs and relational data models that accurately represent the customer's domain and remain understandable as the product evolves.

Build agent instructions, tool interfaces, connector interactions, and durable workflow steps with explicit permission and failure behavior.

Navigate enterprise requirements around authentication, authorization, tenant isolation, data handling, deployment, observability, and change management.

Test realistic user journeys rather than stopping at isolated units or happy-path demos.

Debug across product code, agent behavior, integrations, infrastructure, and customer systems until the underlying failure is understood.

Stay accountable for reliability, adoption, and customer outcomes after launch.

Travel within India when working alongside users will accelerate discovery, delivery, or adoption.

The environment you will work in

Our current product environment includes TypeScript, React, TanStack, Tailwind, Python, FastAPI, typed data models, PostgreSQL, durable workflows, MCP-based tools and connectors, browser automation, and cloud-native deployment on Kubernetes.

We use automated tests, coding agents, traces, evaluations, and production feedback as part of everyday engineering.

This is context, not a checklist. We do not require previous experience with every language, framework, or vendor in our stack. Strong engineers who understand systems, learn quickly, and have shipped production software can become effective here without matching our tools one for one.

Source · SycamoreFirst seen 4 NovOriginal ↗