Software Engineer 2 , Applied AI

Who We Are

Interviews can be challenging, especially at top tech companies like Google, Facebook, and Netflix. Many candidates fall short simply because they are not adequately prepared. That’s where we come in

At Interview Kickstart, our acclaimed courses specialize in interview preparation and helping professionals transition into high-demand tech fields such as AI, ML, and Data Science. Our programs are designed and taught by current and former hiring managers from leading tech companies.

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How Do We Do That?

We take a structured and holistic approach to interview success through:

• Career Accelerator Programs designed for top tech roles

• A Comprehensive end-to-end learning platform

• A network of 750+ instructors from leading Silicon Valley companies such as Google, Facebook, Amazon, and Netflix

• Live classes, mock interviews, personalized coaching, resume refinement, career strategy sessions, and referrals

Role Overview

In this role, you will work closely with the BU heads to design and build AI-native systems powered by LLMs, AI agents, and intelligent workflows. You will rapidly prototype and deploy AI tools and products that automate workflows, enhance internal systems, and unlock new AI-driven capabilities across the organization.

You will play a key role in building AI agents, autonomous workflows, and LLM-powered platforms that power learning, productivity, and knowledge systems.

This role is ideal for someone who enjoys building quickly, experimenting with emerging AI technologies, and turning ideas into production-ready systems.

What Will Excite Us?

• At least 2 - 4 years of experience software development experience/CS degree building production-grade software systems

• You are working on building Agentic AI projects or building them recently.

• Strong programming experience in Python

• Hands-on experience building LLM-powered applications, AI assistants, or agent-based systems

• Experience working with LLM orchestration frameworks such as LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI, or similar tools

• Familiarity with vector databases, embeddings, and Retrieval Augmented Generation (RAG) architectures

• Experience integrating LLMs with external tools, APIs, and structured data sources

• Understanding of prompt engineering, tool calling, and agent orchestration

• Experience building and deploying AI systems from prototype to production, including considerations for reliability, latency, and cost

• Strong understanding of backend systems, APIs, and scalable system design

• A strong builder mindset with the ability to rapidly prototype and iterate on AI-driven systems

• Interest in applying AI to learning systems, knowledge discovery, and productivity tools

What Will You Be Doing?

• Design and build AI agents and autonomous workflows powered by large language models

• Develop systems that combine LLMs, APIs, and external tools to automate complex workflows

• Build Retrieval Augmented Generation (RAG) pipelines and knowledge retrieval systems

• Experiment with modern AI orchestration frameworks such as LangChain, LlamaIndex, LangGraph, CrewAI, or similar tools

• Build AI-powered tools that improve learning workflows, content generation, and internal productivity

• Prototype and launch AI-first product ideas in collaboration with the founders

• Evaluate and improve AI systems to ensure reliability, response quality, and performance

• Optimize AI workflows for latency, cost efficiency, and scalability

• Stay current with the rapidly evolving ecosystem of LLMs, AI agents, and applied AI tooling

Why Will You Enjoy Working with Us?

• Permanent remote / work-from-home culture

• Opportunity to work on a cutting-edge AI technology stack

• An AI-first approach to solving real-world problems

• Complete ownership and trust from leadership

• Your ideas and concerns are actively heard by the leadership team

• Freedom to experiment, fail, and learn

• Rapid career progression for high performers

• Work with a high-caliber team of engineers and industry experts

• Learn how a fast-growing startup builds and scales.

Department: Engineering
Team: Applied AI