What are the responsibilities and job description for the AI Engineer (LLM/Java) - w2 & locals only position at Redolent, Inc?
Job Title: AI Engineer (Java Background) - w2 & locals only
Location: Sunnyvale, CA (Hybrid)
Employment Type: Full-Time (FTE)
Summary
We are seeking a highly motivated AI Engineer with a strong software engineering foundation in Java and hands-on experience with Generative AI, Large Language Models (LLMs), and AI-powered development tools. This role is ideal for an engineer who enjoys leveraging AI to solve complex business problems, automate engineering workflows, and improve developer productivity. The successful candidate will work across multiple technologies and disciplines, developing AI-driven applications, integrating LLMs into enterprise systems, and building tools that enhance software development efficiency. While Java will be the primary development language, the role requires versatility across modern technologies including Python, JavaScript, and front.
About the Role
This role is ideal for an engineer who enjoys leveraging AI to solve complex business problems, automate engineering workflows, and improve developer productivity.
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.
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.
Required Skills
- Strong proficiency in Java and object-oriented software development.
- Experience leveraging AI coding assistants and AI development platforms.
- Ability to use AI technologies for a wide range of engineering tasks.
- Experience with additional programming languages such as Python, JavaScript, or TypeScript.
- Strong problem-solving skills.
- Experience developing REST APIs, microservices, and cloud-based applications.
Preferred Skills
- 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.