AVP Engineering AI & Platforms

• Engineering Strategy & Technology Leadership:

  Define and execute engineering strategy, technology roadmap, architecture governance, and technology investment priorities across products, platforms, and customer solutions.

• Architecture & Technical Excellence:

  Review, challenge, and guide critical architecture decisions, platform designs, AI strategies, scalability approaches, security models, and implementation plans to ensure long-term technical sustainability.

• Data, AI & Platform Engineering:

  Drive the architecture and evolution of Data Platforms, AI Platforms, GenAI solutions, intelligent applications, reusable accelerators, and enterprise-scale platform capabilities.

• Engineering Delivery & Operational Excellence:

  Own engineering execution, delivery predictability, reliability, technical quality, release governance, observability, and operational readiness across all engineering initiatives.

• Quality Engineering & DevOps:

  Establish modern QA, automation, DevOps, CI/CD, platform engineering, SRE, and engineering productivity practices that improve quality, speed, and reliability.

• Innovation & AI-Native Engineering:

  Drive adoption of AI coding assistants, engineering automation, AI agents, modern development workflows, and innovation programs that improve efficiency and technical outcomes.

• Leadership & Talent Development:

  Build high-performing engineering teams, mentor engineering leaders and architects, strengthen technical culture, and create clear growth paths for future technical leaders.

• Customer & Executive Engagement:

  Partner with customers, executive stakeholders, technology leaders, and business teams to align technical strategy with business goals and customer outcomes.
• Experience: 15+ years (with 5+ years in engineering senior leadership roles)

Skills and Competencies:

Must have

Deep, proven expertise; these are non-negotiable.

• Engineering leadership:

  15+ years of software engineering experience with at least 8+ years leading engineering organizations, engineering managers, architects, and technical leaders.

• Architecture & technical depth:

  Strong expertise in enterprise software architecture, cloud-native platforms, distributed systems, platform engineering, API-first architectures, and large-scale application development.

• Data, AI & platform engineering:

  Experience building and scaling Data Platforms, Analytics Platforms, AI Platforms, Enterprise SaaS applications, and AI-enabled products.

• AI & GenAI:

  Strong understanding of modern AI/GenAI architectures, including LLMs, RAG, AI agents, copilots, intelligent automation, vector databases, and enterprise AI adoption.

• Engineering excellence:

  Deep understanding of DevOps, CI/CD, Quality Engineering, Test Automation, Security, Reliability Engineering, Observability, Platform Engineering, and production operations.

• AI-native engineering leadership:

  Demonstrated ability to leverage AI tools, coding assistants, automation platforms, and agent-based workflows to transform software development, testing, documentation, architecture, and engineering operations.

• Technical governance & delivery:

  Proven ability to improve engineering productivity, software quality, architecture governance, delivery predictability, and operational excellence.

• Stakeholder management:

  Excellent communication, executive stakeholder management, customer engagement, and leadership skills.