AI Solutions Engineer 1

Allegis Group Services, Inc.; India; On-site; INR 700,000 - 1,100,000; Full time

Job summary

Allegis Group Services, Inc. is building its AI Engineering team and hiring engineers at the start of their careers who want to build real AI systems, not demos.

As an AI Solutions Engineer I, you'll write production-grade code and contribute to intelligent agents and the Foundation Layer capabilities that power them. This learning-intensive role pairs you with senior engineers and a Lead, with code reviews, and hands-on features from day one.

Qualifications

• 1–3 years of software engineering experience (internships and personal projects count).
• Strong programming skills in Python and/or TypeScript.
• Solid CS fundamentals: data structures, algorithms, and basic systems thinking.
• Experience with Git and version control workflows.
• Ability to write and run tests.
• Clear communication skills—you can explain your code and your reasoning.
• Intellectual curiosity and a bias toward learning by building.
• Experience building web applications or APIs (any framework).
• Familiarity with cloud platforms (Azure, AWS, or GCP).
• Exposure to AI/ML concepts, LLMs, or chatbot development.
• Experience with CI/CD pipelines or containerization (Docker).
• Computer science degree or equivalent practical experience
• Familiarity with agile development practices
• Languages: Python, TypeScript
• Data: REST APIs, Dataverse, SQL, Snowflake

Responsibilities

• Develop features for intelligent agents, conversational interfaces, and agentic workflows.
• Implement components of Foundation Layer services under guidance from senior engineers.
• Write integrations between AI capabilities and enterprise systems (M365, Dataverse, external APIs).
• Write clean, tested code that follows team patterns and standards.
• Fix bugs, investigate issues, and improve existing solutions.
• Pair program with senior engineers and the Lead to learn architecture patterns and best practices.
• Participate actively in code reviews—ask questions, give thoughtful feedback, and apply what you learn.
• Build understanding of our technology stack: Semantic Kernel, Azure, Microsoft 365, LLMs.
• Develop skills in prompt engineering, RAG patterns, and agent design through hands-on work.
• Take on progressively more complex work as your skills develop.
• Write unit and integration tests for your code.
• Follow CI/CD practices and contribute to build and deployment processes.
• Document your work—what you built, why, and how it works.
• Monitor deployed solutions and participate in incident response.

Skills

Python

TypeScript

Git

Testing

CS fundamentals

Communication

Learning

Education

CS degree or equivalent

Tools

Docker

Dataverse

REST APIs

SQL

Snowflake

Job description

Job Description

About the Role

We're building AGS's AI Engineering team from the ground up, and we're hiring engineers at the start of their careers who want to build real AI systems—not tinker with demos. As a AI Solutions Engineer I, you'll write code that ships to production, contributing to intelligent agents, agentic workflows, and the reusable Foundation Layer capabilities that power them.

This is a learning-intensive role with real responsibility. You'll pair with senior engineers and the Lead, participate in code reviews, and build working features from day one. We don't expect you to know LLMs or the Microsoft ecosystem yet—we expect strong software engineering fundamentals and the drive to learn fast. If you can write clean code, reason about problems clearly, and take feedback well, we'll invest in your growth.

We hire engineers, not configuration specialists. If you want to write real software that solves real problems using AI, this is where to start.

Responsibilities

Build & Deliver

• Develop features for intelligent agents, conversational interfaces, and agentic workflows
• Implement components of Foundation Layer services under guidance from senior engineers
• Write integrations between AI capabilities and enterprise systems (M365, Dataverse, external APIs)
• Write clean, tested code that follows team patterns and standards
• Fix bugs, investigate issues, and improve existing solutions

Learn & Grow

• Pair program with senior engineers and the Lead to learn architecture patterns and best practices
• Participate actively in code reviews—ask questions, give thoughtful feedback, and apply what you learn
• Build understanding of our technology stack: Semantic Kernel, Azure, Microsoft 365, LLMs
• Develop skills in prompt engineering, RAG patterns, and agent design through hands‑on work
• Take on progressively more complex work as your skills develop
• Write unit and integration tests for your code
• Follow CI/CD practices and contribute to build and deployment processes
• Document your work—what you built, why, and how it works
• Monitor deployed solutions and participate in incident response
• Work with AI Solutions Analysts to understand requirements and ask clarifying questions
• Communicate progress, blockers, and what you're learning to your team
• Participate in sprint ceremonies and contribute to planning discussions
• Support QA by clarifying implementation details and fixing defects

Qualifications

Required

• 1–3 years of software engineering experience (internships and personal projects count)
• Strong programming skills in Python and/or TypeScript
• Solid CS fundamentals: data structures, algorithms, and basic systems thinking
• Experience with Git and version control workflows
• Ability to write and run tests
• Clear communication skills—you can explain your code and your reasoning
• Intellectual curiosity and a bias toward learning by building

Preferred

• Experience building web applications or APIs (any framework)
• Familiarity with cloud platforms (Azure, AWS, or GCP)
• Exposure to AI/ML concepts, LLMs, or chatbot development
• Experience with CI/CD pipelines or containerization (Docker)
• Computer science degree or equivalent practical experience
• Familiarity with agile development practices
• Languages: Python, TypeScript
• Data: REST APIs, Dataverse, SQL, Snowflake

We don't expect you to know all of this. We expect the fundamentals and the ability to learn the rest quickly.

What We're NOT Looking For

• People who want to configure tools rather than write code
• Engineers who wait to be told exactly what to do and how to do it
• Developers who skip testing, documentation, or code reviewPeople who treat AI as a black box rather than something to understand

What Makes You Stand Out

• You've built something—a side project, an open-source contribution, a school project you're proud of
• You write code that's clean and readable, not just functional
• You ask good questions when you're stuck instead of spinning
• You take feedback as fuel, not criticism
• You're curious about how things work under the hood
• You want to be great at this, not just good enough

This is the entry point for our engineering career track: You'll have a clear path forward with real mentorship. The Lead AI Solutions Engineer and senior engineers will invest in your development through pairing, code review, and progressively larger scope. Engineers who grow quickly here will take on ownership of features, then systems, then architecture.