AI Solutions Manager

Role Summary

Lead enterprise AI solution initiatives combining product vision, technical excellence, and delivery governance. Drive architecture, roadmap, and execution for AI-powered products, ensuring measurable business impact, compliance, and scalability. Build and mentor high-performing teams while fostering innovation and operational rigor.

Key Outcomes

• Define and implement AI product strategy aligned to business objectives.
• Deliver enterprise-grade AI applications with clear ROI, reliability (SLOs), and security.
• Establish best practices for IT delivery, observability, and compliance.
• Build and lead cross-functional teams; enable collaboration between engineering, product, and operations.

Responsibilities

• Product Management: Own AI product lifecycle from ideation to deployment; define roadmaps, prioritize features, and ensure user-centric design.
• Gen-AI Solutions: Architect and deliver Generative AI applications leveraging LLMs, multi-agent systems, and orchestration frameworks.
• Team Management: Build, mentor, and scale high-performing teams across engineering and product functions.
• IT Delivery: Ensure robust delivery governance, cost optimization, and adherence to SLAs/SLOs for enterprise AI systems.
• Translate business challenges into scalable AI architectures and actionable roadmaps.
• Collaborate with Product, Security, Compliance, and Ops teams to ensure safe-by-default systems.
• Manage vendor relationships and evaluate emerging AI technologies for strategic fit.

Technical & Leadership Skills

• AI/ML Expertise: Agentic AI, Generative AI, Conversational AI, orchestration frameworks (LangChain, CrewAI, LangGraph).
• Product Management: Roadmap planning, stakeholder engagement, feature prioritization, and go-to-market strategies.
• Cloud & DevOps: AWS/Azure/GCP, container orchestration (Kubernetes), CI/CD pipelines.
• Azure/GCP Architecture: Design secure, scalable AI solutions leveraging Azure AI Services, Azure OpenAI, Cognitive Services, Event Grid, AKS; Architect GCP-based AI platforms using Vertex AI, Pub/Sub, GKE, Cloud Functions, and implement cost governance.
• MLOps: Model lifecycle management, observability, governance, and cost optimization.
• IT Delivery: Agile/DevOps practices, risk management, and compliance frameworks.
• Leadership: Team building, stakeholder management, strategic planning, and delivery governance.

Qualifications

• Bachelor’s/Master’s in Computer Science, Data Science, or related field.
• 8-12 years of experience in AI/ML solution delivery, product management, and IT governance.
• Proven track record of deploying and operating AI systems at scale.
• Strong programming background (Python preferred) and familiarity with modern AI ecosystems.