Generative AI Engineer

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.

articulate AI concepts to both technical and executive stakeholders