Principal AI Software Engineer

Role description

JD for AI Engineer

Description

We are seeking a highly skilled Generative AI Engineer with 4–5 years of hands-on experience to design, develop, and deploy scalable AI-driven solutions. You will be responsible for building end-to-end pipelines that leverage Large Language Models (LLMs), integrating complex APIs, and optimizing model performance through advanced prompt engineering. The ideal candidate thrives at the intersection of software engineering and cutting-edge artificial intelligence.

Key Responsibilities:

• AI Solution Development: Build and deploy GenAI-powered applications using multiple LLM providers such as Copilot.

• Python Engineering: Develop scalable backend systems, microservices, and APIs to integrate AI models into production workflows.

• Prompt Optimization: Design and implement advanced prompt strategies, including chain-of-thought, few-shot prompting, and multi-step reasoning to ensure accurate AI outputs.

• Data & Workflow Design: Architect RAG (Retrieval-Augmented Generation) pipelines and manage vector databases for efficient context retrieval.

• Performance Monitoring: Evaluate model performance, manage token economics (cost optimization), and implement output validation.

Knowledge & Skills:

• Core Language: Expert-level Python (Pandas, NumPy, and asynchronous programming).

• API Integration: Proven ability to integrate third-party AI APIs

• Prompt Engineering: Mastery of system prompting, context window management, and systematic A/B testing for prompt refinement.

• Infrastructure: Cloud platforms (AWS, Azure, or GCP) for model deployment.

Essential Soft Skills for Success:

• Creative Problem-Solving: The ability to think critically when AI outputs are inconsistent and troubleshoot complex logic errors.

• Cross-Functional Communication: Translating highly technical AI concepts into business value for non-technical stakeholders.

• Adaptability: A mindset for continuous learning to stay current with AI tools that evolve on a regular basis.

Education & Experience:

• Experience: Minimum 4–5 years in software engineering, with at least 2 years focused specifically on AI/ML or GenAI projects.

• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.