AI Software Engineer (Azure AI, Java/Angular Full-Stack)

Avnet•Phoenix, AZ

1d•Onsite

About The Position

Develops, maintains, and enhances business applications with a specialized focus on building, validating, and optimizing intelligent cloud services. Collaborates with stakeholders to validate user requirements, assess available technologies, and recommend technical strategies to deliver production-grade Generative AI features. Assesses objectives for assigned project phases and recommends technical tactics to achieve business needs through modern full-stack development, Agentic AI, and AI solutions.

Requirements

Extensive knowledge and application of full-stack engineering principles, theories, and concepts.
Complete knowledge of all job functions and broad industry best practices, techniques, and standards regarding cloud-native development and enterprise AI deployment.
Develops solutions to complex problems where analysis of situations and/or data requires in-depth evaluation of variables (such as query rewriting, vector database tuning, and prompt flows).
Determines the best approach to achieve results and provides suggestions to improve policies, procedures, and system performance.
Work is performed independently and requires the exercise of judgment and discretion.
Exercises considerable latitude in determining objectives and approaches to assignments.
Work may be reviewed at a high-level.
May represent the organization as a primary contact on assignments and/or projects.
Interacts with senior professionals and management and frequently coordinates work between departments or organizations.
Bachelor's degree or equivalent experience from which comparable knowledge and job skills can be obtained.
Azure AI Ecosystem: Hands-on experience navigating Azure AI Foundry / Azure AI Studio to configure hubs, deploy foundation models (e.g., GPT series, Llama), build prompt flows, and integrate vector search.
Full-Stack Project Delivery: Proven project experience in full-stack application development utilizing Angular(or similar technologies) and Java.
Core Languages & Frameworks: Building and coding applications using languages/technologies such as Java, Python, Spring / Spring Boot, Web Services, and SQL.
Frontend Technologies: Production-level experience using Angular, TypeScript, HTML, CSS/Sass, and Bootstrap.
RAG & Agentic Patterns: Understanding of strategic document chunking, embedding selection, vector stores (e.g., Azure AI Search, pgvector), and exposure to multi-turn agent frameworks or semantic orchestration patterns.
Database & Data Management: Practical knowledge of SQL database design, optimization, and complex dataset retrieval.
Testing & Evaluation: Experience utilizing testing tools like JUnit for Java, coupled with an awareness of LLM evaluation practices (assessing grounding, relevance, and latency metrics).
CI/CD & DevOps: Experience participating in automated deployment and integration pipelines using GitHub Actions, Jenkins, Maven, or Gradle.
Methodologies: Strong alignment with SDLC practices including Agile/Scrum and structured configuration environments.

Nice To Haves

Familiarity with the Model Context Protocol (MCP) for building secure, standardized connections between LLM applications, enterprise data sources, and business tools/APIs.
Familiarity with cloud data tools like Databricks is a plus.

Responsibilities

Develop and implement AI models and algorithms using Microsoft Azure technologies to optimize business processes and improve efficiency.
Uses process design technology methodologies, programming languages and tools, and solutions design techniques to develop full-stack applications to meet business specifications.
Performs analysis, design, development, and testing of applications to solve business requirements, actively leveraging Azure AI to provision resources, manage foundation model endpoints, and orchestrate LLM workflows.
Builds and tunes production-grade RAG pipelines (including document ingestion, semantic chunking, embedding generation, vector indexing, and hybrid retrieval optimization).
Collaborates on the development of semi-autonomous workflows or Agentic AI systems, focusing on tool integration, robust error handling for non-deterministic LLM outputs, and latency management.
Integrates advanced Azure AI services and LLM workflows with existing enterprise Angular front-ends and Java/Spring Boot back-ends, ensuring secure data transit, state management, and seamless UI/UX for AI-driven features.
Supports change readiness initiatives as needed.
Other duties as assigned.