Software Engineer - AI

Ingram Micro is seeking a highly motivated Software Engineer to join our growing AI Engineering team. This role focuses on designing, developing, and deploying next-generation AI-powered solutions, including engineering productivity agents, enterprise automation agents, knowledge agents, code generation agents, and intelligent business workflow assistants. You will work at the intersection of Software Engineering, Generative AI, Agentic Systems, Data Engineering, and Cloud Technologies, building scalable solutions that drive productivity across the organization.

We are looking for a hands‑on engineer with strong Python expertise, a solid foundation in software engineering principles, and a passion for experimenting with emerging AI technologies.

• Design and develop AI-powered agents for engineering, operations, support, and enterprise automation use cases.
• Build and maintain agentic workflows using modern AI frameworks and orchestration platforms.
• Develop Retrieval Augmented Generation (RAG) solutions leveraging vector databases and enterprise knowledge stores.
• Implement prompt engineering, context engineering, memory management, and multi‑agent collaboration patterns.
• Integrate Large Language Models (LLMs) into enterprise applications and workflows.

• Design, develop, test, and deploy scalable software solutions using Python and one of Java or .NET.
• Build RESTful APIs, microservices, and event‑driven architectures.
• Participate in architecture discussions and contribute to technical design decisions.
• Write high‑quality, maintainable, secure, and testable code.
• Collaborate with product managers, architects, and engineering teams to deliver innovative solutions.

• Work with structured and unstructured datasets to build AI‑driven applications.
• Apply statistical analysis, data processing, and machine learning techniques to solve business problems.
• Create data pipelines and embeddings for semantic search and knowledge retrieval.
• Evaluate and benchmark AI models for quality, performance, and cost optimization.

• Deploy AI applications on cloud platforms.
• Build CI/CD pipelines for AI and software delivery.
• Monitor AI services and optimize for scalability, reliability, and observability.

• Bachelor’s degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or a related field.
• Minimum 3‑5 years of relevant work experience.
• Strong proficiency in Python (mandatory).
• Strong proficiency in at least one Object‑Oriented language:
  Java or NET (C#).
• Hands‑on experience with:
  Agent Development Kit (ADK), LLM‑based application development, Prompt Engineering, Context Engineering, AI Agent Orchestration, RAG architectures, Vector Databases, Embeddings and Semantic Search.
• Python Ecosystem, strong experience with:
  Num Py, Pandas, Scikit‑learn, NLTK, Spa Cy, Lang Chain or equivalent frameworks, Data processing and analytics libraries.
• Good understanding of data and statistics, including but not limited to statistics and probability, data and analysis, data modeling, data visualization, and AI evaluation methodologies.
• APIs & Backend Development: REST APIs, Microservices, JSON/XML processing, Authentication & Authorization.
• Experience with Databases:
  PostgreSQL, SQL databases, No
  
  SQL databases, Vector Databases (pgvector, Pinecone, Weaviate, ChromaDB, etc.).
• Exposure to one or more Cloud Platforms, such as:
  Google Cloud Platform (GCP), Amazon Web Services (AWS), and/or Microsoft Azure (Azure).

• Experience with ReactJS or modern frontend frameworks.
• Exposure to Machine Learning and NLP solutions.
• Experience with LLM platforms such as:
• OpenAI
• Google Deep Mind
• Anthropic
• Knowledge of MCP (Model Context Protocol).
• Familiarity with Lang Graph, CrewAI, Semantic Kernel, Auto Gen, or similar frameworks.
• Experience working in Agile environments.
• Knowledge of CI/CD, Docker, and Kubernetes.

We are looking for a go‑getter engineer who:

• Has strong curiosity for emerging AI technologies.
• Learns quickly and thrives in ambiguous environments.
• Demonstrates ownership and accountability.
• Is passionate about building products from concept to production.
• Can independently investigate, prototype, and solve complex problems.
• Collaborates effectively across engineering, product, and business teams.
• Continuously experiments and drives innovation.
• Balances speed, quality, and business impact.