AI Software Engineer

Role Overview

As an AI Software Engineer, you will design, develop, deploy, and support AI-powered applications that solve real business challenges. This role blends software engineering, AI/ML implementation, systems integration, and production support to ensure solutions are reliable, secure, scalable, and aligned with business objectives.

Key Responsibilities

• Design and develop AI-enabled applications, services, APIs, and workflows.
• Translate business requirements into technical AI solutions and system designs.
• Build and maintain integrations between AI services and enterprise systems.
• Prepare, manage, and validate data for AI models and inference workflows.
• Optimize prompt engineering, retrieval logic, orchestration flows, and agent behavior.
• Deploy AI solutions using best practices in software engineering and DevOps.
• Maintain accurate documentation and change tracking.
• Monitor performance, reliability, output quality, latency, and cost in production environments.
• Troubleshoot and resolve system defects, performance issues, and integration challenges.
• Ensure AI systems meet security, governance, privacy, and compliance standards.
• Document architectures, workflows, technical decisions, and support procedures.
• Collaborate cross-functionally to deliver measurable business value.
• Continuously improve solutions based on performance data and user feedback.

Day-to-Day Activities

• Monitor the health and performance of AI applications in production.
• Resolve bugs, failures, and quality issues across AI workflows and integrations.
• Develop and enhance AI features within enterprise systems.
• Validate outputs for quality, accuracy, and business relevance.
• Tune prompts, pipelines, and orchestration logic.
• Participate in design reviews, code reviews, and release activities.
• Partner with stakeholders to refine requirements and priorities.

Monthly Focus Areas

• Evaluate solution performance against business and technical KPIs.
• Analyze trends such as model drift, reliability, and output consistency.
• Recommend and implement improvements to models, prompts, and architecture.
• Optimize cost, scalability, and system resilience.
• Participate in governance, risk, and compliance reviews.
• Update documentation and operational procedures.
• Identify opportunities for new AI use cases and enhancements.

Required Qualifications

• Bachelor’s degree in computer science, Information Technology, or a related field.
• 1–3+ years of experience working with AI platforms such as Oracle AI, AWS AI, Anthropic, or OpenAI.
• Proficiency in Python.
• Strong understanding of (LLMs).

Preferred Qualifications

• Experience with LangChain, vector databases, RAG, or MCP frameworks.
• Familiarity with OCI and Docker.