AI Delivery Lead

Job description

Job Description: 1. AI Delivery Leadership - Own end-to-end delivery of AI/ML and GenAI programs across multiple client engagements - Drive execution across solution design, development, deployment, and productionization - Ensure alignment with business objectives, SLAs, and delivery KPIs 2. Forward Deployed Engineering (Client Engagement) - Work directly with enterprise clients to understand business problems and translate into AI solutions - Act as a trusted advisor, influencing client strategy and AI transformation initiatives - Operate in on-site / embedded engagement models, ensuring adoption and impact 3. Solution Architecture & Implementation - Lead design and deployment of: - AI/ML models, LLM-based solutions, and agentic workflows - Scalable data pipelines and cloud-native architectures - End-to-end AI platforms including APIs, orchestration layers, and UI integrations - Build and mentor high-performing AI delivery teams - Drive: - Capability development in GenAI, MLOps, and scalable AI systems - Knowledge sharing and best practices standardization - Lead by example with hands-on problem-solving and technical guidance - Identify opportunities for: - AI-driven transformation use cases - Platform acceleration and reusable assets 4. Team Leadership & Capability Building 5. Innovation & Thought Leadership **Required Qualifications** **Education** - Bachelor’s/Master’s degree in Computer Science, AI/ML, Data Science, or related field **Experience** - 6+ years of experience in **AI/ML delivery, data engineering, or software engineering** - 3+ years in **leadership or delivery ownership roles** - Proven experience in **client-facing delivery or consulting roles (FDE preferred)** **Technical Skills** - Strong programming expertise (Python preferred) - Experience with: - GenAI/LLMs (OpenAI, Llama, etc.), RAG pipelines, embeddings - Cloud platforms (AWS/Azure/GCP) - Containerization (Docker, Kubernetes) - Data platforms (Spark, Databricks, APIs, streaming) - Familiarity with: - MLOps / ModelOps / CI-CD for AI systems - Observability and monitoring tools Responsibilities: 1. AI Delivery Leadership - Own end-to-end delivery of AI/ML and GenAI programs across multiple client engagements - Drive execution across solution design, development, deployment, and productionization - Ensure alignment with business objectives, SLAs, and delivery KPIs 2. Forward Deployed Engineering (Client Engagement) - Work directly with enterprise clients to understand business problems and translate into AI solutions - Act as a trusted advisor, influencing client strategy and AI transformation initiatives - Operate in on-site / embedded engagement models, ensuring adoption and impact 3. Solution Architecture & Implementation - Lead design and deployment of: - AI/ML models, LLM-based solutions, and agentic workflows - Scalable data pipelines and cloud-native architectures - End-to-end AI platforms including APIs, orchestration layers, and UI integrations - Build and mentor high-performing AI delivery teams - Drive: - Capability development in GenAI, MLOps, and scalable AI systems - Knowledge sharing and best practices standardization - Lead by example with hands-on problem-solving and technical guidance - Identify opportunities for: - AI-driven transformation use cases - Platform acceleration and reusable assets 4. Team Leadership & Capability Building 5. Innovation & Thought Leadership Qualifications: Bachelor’s/Master’s degree in Computer Science, AI/ML, Data Science, or related field