Software Development Engineer 2 – AI Platform

Company Description

𝐒𝐞𝐞𝐝𝐥𝐢𝐧𝐠𝐋𝐚𝐛𝐬 is an AI native engineering company built to close the gap between AI pilots and production. 𝐒𝐞𝐞𝐝𝐥𝐢𝐧𝐠𝐋𝐚𝐛𝐬 𝐂𝐨𝐫𝐞 combines AI Advisory & Transformation, helping enterprises validate what is actually worth building, with 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐏𝐃𝐚𝐚𝐒, an engineering team that ships domain specific AI capabilities in weeks, not months. Every component runs on 𝐅𝐨𝐫𝐠𝐞𝐛𝐞𝐧𝐜𝐡, 𝐒𝐞𝐞𝐝𝐥𝐢𝐧𝐠𝐋𝐚𝐛𝐬’ production stack for enterprise Gen AI , giving enterprises one governed gateway across every model and provider, deployable in the cloud, private, or fully air gapped. SeedlingLabs is headquartered in Bengaluru, with an engineering hub in Gangavathi . Learn more at www.seedlinglabs.com.

Reports To: Head of Engineering

The Role As a Software Engineer 2, you are the builder. You will work within our “compact, skilled

AI-native teams” to translate architectural designs into working code. You will move beyond writing

standard CRUD APIs and vibe coding to building components of the Agent Brain—writing the code

that lets an AI Agent interact with browsers, databases, and mobile devices. This is your opportunity

to transition from a “Traditional Engineer” to an “AI Engineer.”, learn prompt engineering, context

engineering, harness engineering and multi-agent architectures.

𝐊𝐞𝐲 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬

● 𝐅𝐞𝐚𝐭𝐮𝐫𝐞 𝐈𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 & 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐲:

○ Write clean, robust, and maintainable code (Python/React) for our Startup Engines.

○ Implement specific modules of the Model Context Protocol (MCP), such as

building a connector that allows our Agent to read a specific file format or interact

with a new API.

● 𝐀𝐈 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 & 𝐏𝐫𝐨𝐦𝐩𝐭 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠:

○ Work with Senior Engineers to implement “prompts-as-code.” You will write the

logic that sends context to the LLM and parses the response back into structured

actions.

○ Help build the “Tools” our Agents use—creating the actual functions (e.g.,

click_button, query_db) that the AI calls during runtime execution.

● 𝐑𝐞𝐥𝐢𝐚𝐛𝐢𝐥𝐢𝐭𝐲 & 𝐓𝐞𝐬𝐭𝐢𝐧𝐠:

○ Own the quality of your code. You will write unit tests and integration tests to ensure

that the “non-deterministic” nature of AI doesn’t break our production systems.

○ Own debugging and root cause analysis of production issues. You will use our SOTA

tools to analyze why an Agent failed—was it a bad prompt, a network timeout, or a

hallucination?

● 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧 & 𝐆𝐫𝐨𝐰𝐭𝐡:

○ Participate in (and own) code reviews, learning from peers and architects to improve

your system design skills.

○ Collaborate with the “Spoke” teams, ensuring clear documentation so that engineers

in other locations can use the components you build.

Desired Qualifications

● 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞: 3-5 𝐲𝐞𝐚𝐫𝐬 𝐨𝐟 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞 𝐢𝐧 𝐬𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠.

● 𝐂𝐨𝐫𝐞 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐒𝐤𝐢𝐥𝐥𝐬:  Strong proficiency in React, TypeScript, or Python. You

understand asynchronous programming, API design, and database basics (SQL/NoSQL).

● 𝐂𝐥𝐨𝐮𝐝 𝐁𝐚𝐬𝐢𝐜𝐬: Familiarity with AWS services (Lambda, S3, , Terraform). You know how to

deploy code and check logs.

● 𝐀𝐈 𝐂𝐮𝐫𝐢𝐨𝐬𝐢𝐭𝐲: You may not be an expert, but you have played with ChatGPT APIs,

LangChain, or built small AI demos. You are eager to learn how Agentic Workflows work.

● 𝐏𝐫𝐨𝐛𝐥𝐞𝐦 𝐒𝐨𝐥𝐯𝐢𝐧𝐠: Strong analytical skills. You can look at a bug and trace it back to the root cause, even in a complex distributed system.