Software Engineer 1 , Applied AI

Interview Kickstart

United States

Remote

USD 120,000 - 180,000

Full time

7 days ago
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Job summary

Interview Kickstart is hiring an Applied AI Engineer to develop and deploy AI/ML solutions that enhance our learning platform. You will collaborate with data scientists, engineers, and product managers to build robust, scalable models and agent systems.

You should have hands-on experience with LangChain, various AI APIs, and Python web frameworks, and you will work in a fully remote environment with a fast-growing startup culture.

Qualifications

  • Hands-on experience building and deploying AI agents with LangChain or similar.
  • Experience with multi-step agent workflows and orchestration.
  • Proficiency in Python and modern Python web frameworks (Django/DRF, FastAPI).
  • Familiarity with vector databases (Pinecone/Weaviate) and semantic search.
  • Strong debugging and problem-solving skills.

Responsibilities

  • Work closely with senior AI/ML engineers to build LLM-powered agent systems for real product use cases.
  • Design, develop, and optimize agent pipelines/APIs, and contribute to evaluation frameworks.
  • Bug-fix and improve agent performance before adding new features.
  • Optionally contribute to MLOps deployment pipelines.

Skills

AI agent development
LangChain
LangGraph
OpenAI API
Gemini API
Anthropic API
Python
Django
FastAPI
Vector databases
Pinecone
Weaviate
Debugging
Communication
Algorithms

Tools

Django REST framework (DRF)
Python

Job description

Who We Are:

Interviews can be hard, especially at top tech companies like Google, Facebook, and Netflix. Many candidates fall short simply because they aren't adequately prepared. That's where we come in. Our acclaimed courses specialize in interview preparation and transitioning into high-demand tech fields such as AI, ML, and Data Science. At Interview Kickstart, current and former hiring managers have guided over 17,000 tech professionals through transformative career journeys, ensuring their success in landing coveted positions. Think of us as "the everything store" for career transitions and interview skill development.

How Do We Do That, You Ask?

We have a structured approach to interview success, which includes:

  • Career Accelerator Course

  • Comprehensive end-to-end courses and platform

  • A roster of over 600+ instructors from leading Silicon Valley companies like Google, Facebook, Amazon, and Netflix

  • A holistic approach that includes live classes, mock interviews, personalized coaching, resume refinement, career strategies, and invaluable referrals

What's more exciting is that we are completely remote and hiring the best people we can find regardless of geography.

Role Overview:

As an Applied AI Engineer at Interview Kickstart, you will play a crucial role in developing and deploying cutting-edge AI/ML solutions that enhance our platform and improve the learning experience for our students. You will work closely with data scientists, engineers, and product managers to build and scale robust and impactful machine learning models.

What will excite us:

  • An AI-first approach for solving the problems.

  • Solid prompt engineering skills.

  • 1+ years full-time experience building and deploying AI Agents using LangChain, LangGraph, OpenAI API, Gemini API, Anthropic API, etc.

  • Hands-on experience with multi-step agent workflows, orchestration, and evaluating agent reliability.

  • 1.5+ years of full-time experience in Python and Django/Django REST framework (DRF)/FastAPI.

  • Familiarity with vector databases (Pinecone, Weaviate) and semantic search.

  • Good debugging and online searching skills.

  • Good communication skills.

  • Good problem-solving skills (ability to solve hard-level data structures and algorithms problems).

What will you be doing? :

  • You will work closely with senior Applied AI/ML engineers building LLM-powered agentic systems for real product use cases.

  • You will design, develop, and optimize agent pipelines/APIs, build tests for agent behaviors, and contribute to evaluation frameworks.

  • Bug-fixing and improving agent performance will be prioritized before starting new feature work.

  • Optionally, if interested/experienced, you will contribute to MLOps deployment pipelines.

What would excite you?

  • Permanent remote/WFH and flexible work culture.

  • Cutting-edge technology stack.

  • An AI-first approach for solving the problems.

  • Complete ownership and trust from the top management.

  • Ideas and concerns are carefully listened to by the top management.

  • Experiment, fail, and learn.

  • Rapid career progression for high performers.

  • High-pedigree, high-caliber team.

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

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