AI Applications & Software Engineering Manager
Job Description:
• Lead cross-functional software engineering teams to build AI-enabled applications using LLMs and other advanced ML models.
• Collaborate with business stakeholders to identify high-impact opportunities to apply AI to core business problems.
• Oversee the end-to-end software lifecycle: architecture, development, testing, deployment, and support.
• Champion AI innovation by integrating generative AI, prompt engineering, RAG (Retrieval-Augmented Generation), fine-tuning, and related techniques into software solutions.
• Guide development teams in adopting best practices for ethical, responsible AI and model explainability.
• Partner with data scientists and MLOps teams to operationalize models into scalable and maintainable systems.
• Lead technology roadmap planning and prioritization to align AI application with business strategies.
• Ensure applications meet performance, security, compliance, and service-level requirements.
• Promote a culture of continuous learning and improvement with a focus on emerging AI/ML technologies.
• Coach, develop, and retain top talent within the engineering organization.
Requirements:
• At least 5 years of experience in software engineering with a strong foundation in AI/ML technologies is required.
• At least 3 years of experience managing a team is required, preferably in software development environment.
• Proven experience deploying LLMs (e.g., OpenAI, Claude, Mistral, Gemini, LLaMA) in production environments.
• Deep understanding of modern AI/ML frameworks, MLOps principles, and generative AI patterns.
• Experience with cloud-based AI platforms (e.g., Vertex AI, SageMaker, Azure OpenAI, or Snowflake Cortex).
• Strong background in software architecture and agile development methodologies.
• Exceptional communication skills with the ability to explain complex AI concepts to business leaders.
• Demonstrated success leading innovation initiatives in high-growth or enterprise environments.
• Experience in integrating AI into enterprise platforms such as ERP, CRM, or custom business systems.
• Familiarity with hybrid AI approaches (symbolic + neural), reinforcement learning, or autonomous agents.
• Strong knowledge of prompt engineering, vector search, fine-tuning, and inference optimization.
• Experience in regulated industries or handling sensitive data (e.g., healthcare, finance).
Benefits:
• Health insurance
• 401(k) matching
• Flexible work hours
• Paid time off
• Remote work options
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