Software Engineering Advisor – Java Focused, AI Enabled

Introduction

A career in IBM Consulting is built on long‑term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long‑term career development while valuing your unique skills and experiences.

Your Role And Responsibilities

The Software Engineering Advisor is a senior individual contributor responsible for designing, developing, and guiding the delivery of complex, enterprise‑scale software solutions. This role brings deep expertise in Java‑based application development while applying emerging AI capabilities to enhance automation, quality, and delivery efficiency across the software development lifecycle. Operating with a high degree of autonomy, the Advisor influences solution design, technical direction, and engineering best practices. While this role does not carry direct people‑management responsibilities, it plays a critical role in technical leadership, mentoring, and cross‑team collaboration. The ideal candidate is a seasoned Java engineer with applied experience integrating AI‑enabled components into production systems.

Key Responsibilities
Software Engineering Leadership

Serve as a technical advisor on complex initiatives, contributing to system design, solution architecture, and implementation strategy.
Design, develop, and maintain enterprise‑grade Java applications that meet standards for performance, security, scalability, and reliability.
Provide technical guidance and mentorship to engineers across teams, promoting engineering excellence and consistency.

Java Application Development (Primary Focus)

Lead development of backend services and APIs using Core Java, Spring Boot, RESTful services, and SQL.
Translate complex business and technical requirements into well‑designed, maintainable software solutions.
Participate in design reviews, code reviews, and architectural discussions to ensure alignment with enterprise standards.

AI‑Enabled Engineering (Secondary Focus)

Contribute to the design and integration of AI‑enabled capabilities within existing Java applications.
Develop or integrate Python‑based AI services, including:
Retrieval Augmented Generation (RAG) workflows
LLM‑powered APIs and supporting services
Embedding and semantic retrieval patterns
Apply AI responsibly and pragmatically to improve automation, developer productivity, and quality outcomes.

Automation & Quality Engineering

Apply a strong understanding of automation and quality engineering concepts, including API automation and intelligent testing strategies.
Partner with QA, automation engineers, and platform teams to improve reliability and test coverage across systems.

Problem Solving & Technical Analysis

Analyze highly complex problems spanning multiple systems and technologies.
Troubleshoot and resolve issues across Java services, automation frameworks, and AI‑enabled components.
Identify root causes and implement sustainable, production‑ready solutions.

Collaboration & Communication

Collaborate closely with architects, product partners, QA, data engineers, and business stakeholders.
Communicate technical designs, tradeoffs, and risks clearly to both technical and non‑technical audiences.
Operate effectively within a large‑scale, matrixed, and highly regulated enterprise environment.

Experience

Strong years of professional software development experience in enterprise environments.
Strong years of hands‑on Java development experience, including:
Core Java
Spring Boot
RESTful API design
SQL and relational databases
1+ years of applied AI or data‑driven software engineering experience, including:
Python‑based development
Working knowledge of RAG concepts, LLM integration, or AI‑assisted services
Integrating AI components into production applications (beyond proof‑of‑concept work)