We are looking for a Senior AI/GenAI Engineer to design, develop, and deploy advanced AI solutions, with a focus on large language models (LLMs), AI workflows, and generative AI applications. The ideal candidate will have hands-on experience with AI/ML frameworks, model deployment, and integrating AI capabilities into real-world products.
Job Responsibilities:
AI Development & Model Implementation
- Design, train, fine-tune, and deploy AI models, including LLMs and generative AI models.
- Implement AI-powered features, such as chatbots, content generation, and predictive analytics.
- Evaluate model performance and optimize for accuracy, efficiency, and scalability.
- Research and integrate emerging AI technologies into existing workflows.
System Design & Integration
- Build AI pipelines and APIs for seamless integration with web and mobile applications.
- Collaborate with backend and frontend teams to implement AI solutions in production.
- Ensure robust and secure handling of data for AI applications.
Collaboration & Mentorship
- Work closely with product managers, data engineers, and developers to deliver AI-driven solutions.
- Provide guidance and best practices for AI/ML development across the team.
- Document AI workflows, model decisions, and performance benchmarks.
Innovation & Research
- Stay updated on AI/GenAI advancements and emerging trends.
- Evaluate new tools, frameworks, and architectures to accelerate AI adoption.
Job Requirements:
- 3–5+ years of experience in AI/ML development, with recent experience in generative AI/LLMs.
- Strong programming skills in Python, PyTorch, TensorFlow, or similar frameworks.
- Experience deploying AI models via cloud platforms (AWS, GCP, Azure).
- Strong understanding of NLP, LLMs, and generative AI workflows.
- Experience with APIs and integrating AI models into web or mobile applications.
- Excellent problem-solving, collaboration, and communication skills.
- Hands-on experience with OpenAI APIs, Hugging Face models, LangChain, or similar frameworks.
- Experience with AI pipelines, prompt engineering, or AI workflow automation.
- Background in data engineering, MLOps, or scalable AI system design.
- Experience in building AI-driven SaaS products or enterprise solutions.
- Exposure to global clients and real-world AI applications