Generative AI Engineer

4 weeks ago

India Bristlecone Full time

Solution Architecture & Design

- Lead the design and development of advanced AI solutions leveraging LLMs, GenAI models, AI agents, and hybrid AI approaches.
- Architect scalable, secure, and efficient AI systems integrating traditional ML with emerging Generative AI capabilities.
- Ensure AI solutions align with enterprise-grade performance, compliance, and ethical AI standards.

Thought Leadership & Innovation

- Act as a subject matter expert (SME) in Generative AI, LLMs, and Agentic AI; contribute to technical strategy and AI roadmaps.
- Represent the organization in conferences, whitepapers, patents, and client discussions as a recognized AI thought leader.
- Explore, evaluate, and integrate cutting-edge research, frameworks, and toolkits in AI and ML.

Engineering & Delivery

- Provide hands-on guidance for model fine-tuning, prompt engineering, multi-agent orchestration, and system optimization.
- Lead proof-of-concept (PoC) development and transition of AI solutions into production.
- Collaborate with product managers, data scientists, engineers, and stakeholders to deliver enterprise-ready AI solutions.

Mentorship & Leadership

- Mentor and guide engineering teams on best practices in AI solutioning, research translation, and applied engineering.
- Foster a culture of innovation, experimentation, and continuous learning within the AI/ML engineering group.

Required Qualifications

- Experience: 7–12 years in Artificial Intelligence and Machine Learning, with 3–4 years dedicated to Generative AI, LLMs, and Agentic AI.

Technical Expertise:

- Strong understanding of LLM architectures (e.g., GPT, LLaMA, Mistral, Claude, Gemini, etc.), fine-tuning, and deployment.
- Experience in AI agent frameworks, multi-agent systems, and orchestration tools.
- Solid background in machine learning algorithms, deep learning, NLP, computer vision, and reinforcement learning.
- Proficiency in Python, PyTorch, TensorFlow, Hugging Face, LangChain, vector databases, and cloud AI platforms (AWS, Azure, GCP).
- Leadership Skills: Proven track record of architecting AI solutions at scale and leading cross-functional teams.
- Research & Innovation: Demonstrated ability to stay ahead of AI trends and convert emerging techniques into practical solutions.

Strong communication skills with the ability to articulate AI concepts to both technical and executive stakeholders

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