Key Responsibilities

Design, develop, and deploy AI-powered applications and solutions using modern LLMs and Generative AI technologies.
Build, customize, and enhance AI tools, agents, and workflows to improve engineering productivity and operational efficiency.
Integrate AI capabilities into enterprise applications and software development processes.
Develop and maintain scalable backend services primarily using Java.
Utilize AI-assisted development tools (such as GitHub Copilot, Cursor, Claude, ChatGPT, or similar platforms) to accelerate software development and innovation.
Evaluate emerging AI technologies, frameworks, and models and recommend their adoption where appropriate.
Collaborate with product managers, architects, and engineering teams to identify opportunities for AI-driven automation and optimization.
Create proof-of-concepts, prototypes, and production-ready AI solutions.
Participate in architecture discussions, code reviews, testing, deployment, and ongoing support activities.
Develop solutions across multiple technology stacks, including backend, frontend, APIs, automation, and AI frameworks.

Required Qualifications

Bachelor's degree in Computer Science, Software Engineering, or a related technical field.
5+ years of professional software development experience.
2+ years of hands-on experience working with Generative AI, Large Language Models (LLMs), AI agents, or AI-powered applications.
Strong proficiency in Java and object-oriented software development.
Experience leveraging AI coding assistants and AI development platforms to design, develop, test, and deploy software solutions.
Ability to use AI technologies to perform a wide range of engineering tasks, including coding, testing, debugging, documentation, automation, and system design.
Experience with one or more additional programming languages such as Python, JavaScript, TypeScript, or similar.
Strong problem-solving skills and ability to rapidly learn and adapt to emerging AI technologies.
Experience developing REST APIs, microservices, and cloud-based applications.

Experience with OpenAI, Anthropic, Gemini, Llama, or other foundation models.
Experience with AI frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or similar.
Experience building AI agents, Retrieval-Augmented Generation (RAG) solutions, vector databases, and prompt engineering workflows.
Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
Familiarity with containerization and orchestration technologies such as Docker and Kubernetes.
Experience with modern frontend frameworks such as React, Angular, or Vue.js.
Knowledge of MLOps, model deployment, and AI governance best practices

Bachelor's degree

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