Job Description
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 Apply tot his job
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