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

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

Bachelor’s/Master’s degree in Computer Science, AI/ML, Data Science, or related field