Practice Lead - AI

About Impower.ai

Impower.ai helps Fortune 1000 enterprise organizations solve complex business challenges through modern Data, AI, and engineering solutions. Impower designs and delivers scalable platforms that enable intelligent decision-making, automation, and AI-driven outcomes.

Role Summary

The Practice Lead – AI is a technical and architectural leader of the AI Practice, serving as a peer thought leader who supports the Practice Director in building the practice. This role owns solution strategy, delivery execution, and senior client advisory for AI engagements, while contributing to the growth and market positioning of the practice.

This is a dual mandate. The role owns the design and execution of modern AI solutions for Fortune 1000 clients, and it supports the Practice Director in building the practice itself: its offerings, its point of view, and its reputation in the market.

What You Will Do

Lead Client Solutions

• Act as a trusted advisor to senior technology leaders
• Lead architecture and solution design for AI-based initiatives
• Translate business needs and outcomes into scalable, production-ready solutions

Advance AI Capabilities

• Architect and deliver AI/LLM solutions across cloud platforms, including generative AI, RAG-based architectures, and agentic systems
• Select the right model, framework, and cloud provider for each client's environment and constraints, rather than defaulting to a single stack
• Help clients move AI from experimentation to production
• Evaluate and recommend emerging AI tooling and frameworks for client and internal use

Shape AI Strategy

• Support the Practice Director in defining the practice's point of view on AI strategy for enterprise clients
• Contribute to proposals, capability narratives, and go-to-market materials that position Impower's AI offerings
• Represent the practice in client-facing strategy discussions, not only technical delivery

Own Delivery Quality and AI Governance

• Establish best practices for performance, scalability, and cost across AI engagements
• Implement AI governance and quality frameworks, covering model risk, data handling, and responsible AI use
• Ensure consistent, high-quality delivery across engagements

Lead and Grow the Team

• Lead, manage, and develop engineers assigned to AI engagements
• Build a culture of technical excellence and accountability
• Operate as a peer thought leader who supports the Practice Director, contributing to practice growth, reusable assets, and go-to-market strategy

Core Technical Expertise / Exposure

• LLM and generative AI architecture, including RAG, agentic systems, and multi-model orchestration
• LLM frameworks such as LangChain, Semantic Kernel, or equivalent
• Cloud AI platforms across at least one hyperscaler (Azure, AWS, or GCP), with the ability to design solutions that are not locked to a single provider
• MLOps and LLMOps practices, including model evaluation, monitoring, and lifecycle management (MLflow or equivalent)
• Python and the ability to prototype, validate, and productionize AI solutions hands-on
• AI governance frameworks, covering model risk, data handling, and responsible AI use
• Working fluency with the surrounding data ecosystem (cloud data platforms, orchestration, data modeling) sufficient to architect AI solutions that depend on it

Qualifications

• 10+ years in Data, Analytics, or AI engineering
• Proven experience designing enterprise-scale AI solutions
• Strong architectural mindset with hands-on technical depth
• Experience leading high-performing technical teams
• Demonstrated ability to operate as a strategic partner, not only a delivery lead, in client and internal settings
• Strong consultative skills, including structuring ambiguous business problems, running discovery with client stakeholders, and advising through competing priorities in enterprise environments
• Excellent client-facing communication skills

What Success Looks Like

• Scalable AI platforms and solutions delivering measurable business value, from initial use case through production
• High-performing engineering teams operating with consistency and quality across engagements
• Trusted advisor relationships with senior client stakeholders, built on consultative credibility as well as technical depth
• A visible contribution to the AI Practice's capability narrative, assets, and market position, in support of the Practice Director