Vice President - Technical Product Engineering Lead Agentic AI

Technical Product Engineering

Technical Product Engineering Lead

Key Responsibilities

Technical Leadership & Architecture

• Define and implement the technical vision and architecture for AI-driven financial products, ensuring scalability, security, and regulatory compliance.

• Guide engineering teams in designing agentic automation frameworks, decision engines, and workflow orchestration tailored for the financial industry.

• Evaluate emerging AI technologies, platforms, and patterns to accelerate innovation.

End-to-End Product Development

• Lead the full engineering lifecycle-from prototyping and model integration to production deployment and post-release enhancements.

• Collaborate with product and domain teams to convert financial use cases (e.g., underwriting, claims, fraud detection, onboarding, KYC) into actionable engineering plans.

• Maintain a healthy balance between feature velocity, code maintainability, and operational robustness.

SDLC Ownership & Quality Governance

• Oversee SDLC processes, ensuring engineering rigor across design, development, testing, release, and support.

• Drive defect management, testing automation, observability, and performance validation for secure, enterprise-grade AI products.

• Implement quality benchmarks, coding standards, and engineering best practices.

AI & Model Integration

• Partner with AI/ML teams to integrate large language models, agent frameworks, and predictive models into financial workflows.

• Ensure responsible AI principles-explainability, fairness, compliance, and risk controls-are embedded in the product.

Cross-Functional Collaboration

• Work closely with product management, domain specialists, data engineering, and client teams to align engineering outputs with business outcomes.

• Communicate priorities, risks, and technical trade-offs clearly to stakeholders across global teams.

Client-Centric Delivery

• Engage with financial clients to understand domain challenges and customize solution architectures accordingly.

• Ensure products meet industry-specific regulatory, privacy, and security standards (e.g., PCI, SOX, AML/KYC regulations).

Team Leadership & Capability Building

• Mentor engineering teams, promote a culture of continuous learning, and build deep capabilities in agentic automation and AI-driven development.

• Lead global, distributed teams with a focus on high performance, reliability, and innovation.

Qualifications We Seek

Minimum Qualifications

• Proven experience leading engineering teams delivering AI/ML or automation products in a large-scale enterprise environment.

• Strong understanding of SDLC, defect management, and engineering quality processes.

• Hands-on experience with cloud-native architectures, microservices, APIs, and AI integration patterns.

• Excellent leadership, communication, and technical decision-making skills.

Preferred Skills

• Experience building products for financial services-banking, insurance, capital markets, or risk management.

• Familiarity with regulatory requirements and data governance frameworks in BFSI.

• Strong grasp of Agile delivery models and modern DevSecOps practices.

• Ability to balance technical rigor with business priorities and client impact.

• Experience mentoring teams and fostering engineering excellence.

Education

• Bachelor's degree in Computer Science, Engineering, or related technical discipline.

• Master's degree in Technology Management, AI/ML, Business, or Data Science is a plus.