AI Solutions Lead

Role & responsibilities

• Lead the design, architecture, and delivery of AI/ML and Generative AI solutions for enterprise business problems.
• Translate business requirements into scalable, secure, and production-ready AI solutions.
• Drive end-to-end GenAI/LLM initiatives, including RAG, AI Agents, prompt engineering, embeddings, vector databases, and LLM evaluation.
• Develop POCs, prototypes, solution blueprints, technical proposals, and architecture documents.
• Work closely with business stakeholders, clients, product teams, data scientists, ML engineers, and software engineers.
• Provide technical leadership for AI solution implementation, deployment, optimization, and troubleshooting.
• Evaluate emerging AI technologies, frameworks, models, and cloud AI services and recommend appropriate solutions.
• Establish best practices around AI architecture, MLOps, security, governance, scalability, cost optimization, and responsible AI.
• Support presales activities, including client discussions, solution presentations, RFP/RFI responses, estimations, and demonstrations.
• Mentor and guide AI/ML engineering teams and ensure delivery quality, timelines, and technical standards.
• Collaborate with cloud and engineering teams to deploy AI solutions using AWS, Azure, or GCP.
• Measure solution effectiveness through accuracy, latency, scalability, cost, adoption, and business ROI

Preferred candidate profile

• 5 to 10 years of experience in AI/ML, Data Science, Software Engineering, AI Consulting, Solution Architecture, or related fields.
• Strong hands-on experience with Generative AI, LLMs, RAG, AI Agents, NLP, Machine Learning, and Deep Learning.
• Strong programming skills in Python and experience building production-grade AI applications and APIs.
• Experience with OpenAI/Azure OpenAI, AWS Bedrock, Google Vertex AI, Hugging Face, LangChain/LlamaIndex, or similar AI platforms.
• Strong understanding of Vector Databases, embeddings, prompt engineering, LLM evaluation, fine-tuning, and AI application architecture.
• Good knowledge of AWS/Azure/GCP, Docker, Kubernetes, REST APIs, microservices, CI/CD, and MLOps.
• Proven ability to convert business requirements into technical AI solutions and architecture.
• Experience in client-facing consulting, presales, POCs, solution demonstrations, and stakeholder management is highly desirable.
• Strong communication, presentation, analytical, problem-solving, and technical leadership skills.
• Bachelor's degree in Computer Science, IT, AI/ML, Data Science, Engineering, or a related discipline; Master's degree is an advantage.
• Experience leading or mentoring cross-functional AI/ML engineering teams will be preferred.
• Candidates with experience delivering enterprise-scale AI/GenAI solutions from POC to production will be strongly preferred.