Roles & Responsibilities :

- Lead the end-to-end design and architecture of AI/ML and GenAI solutions, from ideation through production deployment.

- Translate business requirements into scalable, secure, and commercially viable AI solutions.

- Identify opportunities to apply Generative AI, LLMs, NLP, computer vision, predictive analytics, and intelligent automation to business problems.

- Design solutions using technologies such as LLMs, RAG, vector databases, AI agents, prompt engineering, model evaluation, and fine-tuning where appropriate.

- Evaluate and select appropriate AI models, frameworks, platforms, APIs, and cloud services.

- Work with engineering, data science, data engineering, product, and business teams to ensure successful implementation.

- Define solution architecture, technical specifications, integration patterns, data flows, and deployment strategies.

- Lead POCs, prototypes, and MVPs, and establish a path from experimentation to production.

- Ensure AI solutions meet requirements for security, scalability, performance, reliability, governance, and responsible AI.

- Provide technical leadership and mentoring to AI/ML engineers, data scientists, and solution architects.

- Engage with senior stakeholders and customers to understand requirements, present solution approaches, and communicate technical concepts in business terms.

- Support pre-sales activities, including solution proposals, technical presentations, estimations, RFP/RFI responses, and customer workshops.

- Work with delivery and project teams on effort estimation, timelines, risks, dependencies, and technical delivery plans.

- Establish best practices for MLOps/LLMOps, model monitoring, evaluation, observability, and lifecycle management.

- Stay current with emerging developments in GenAI, LLMs, AI agents, cloud AI platforms, and enterprise AI architecture.

- Contribute to the organization's AI strategy, reusable solution accelerators, reference architectures, and technical thought leadership.

Preferred Candidate Profile :

- 5-10 years of overall experience in software engineering, AI/ML, data science, solution architecture, or related technology roles.

- Demonstrated experience in designing and implementing enterprise AI/ML solutions.

- Strong hands-on understanding of Generative AI and LLM technologies.

- Experience with RAG, embeddings, vector databases, prompt engineering, LLM evaluation, AI agents, and/or fine-tuning.

- Strong programming experience in Python; familiarity with APIs, microservices, and modern software engineering practices.

- Experience with one or more major cloud platforms: AWS, Microsoft Azure, or Google Cloud.

- Good understanding of data engineering, databases, APIs, integration architectures, and distributed systems.

- Experience with AI/ML frameworks and platforms such as PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, or equivalent technologies.

- Exposure to MLOps/LLMOps, CI/CD, Docker, Kubernetes, model deployment, monitoring, and cloud-native architectures.

- Strong understanding of AI security, data privacy, responsible AI, governance, and enterprise architecture principles.

- Experience working directly with business stakeholders, customers, or senior leadership.

- Ability to convert complex business requirements into clear technical architecture and implementation roadmaps.

- Strong communication, presentation, problem-solving, and stakeholder-management skills.

- Experience leading POCs, technical teams, or cross-functional AI initiatives.

- Experience in pre-sales, consulting, RFP/RFI responses, or client solutioning would be an advantage.

- Relevant bachelor's or master's degree in Computer Science, AI/ML, Data Science, Engineering, or a related discipline.