Software Engineering Director

Job Title : Software Engineering Director - AI

Job Description :

The Director of Engineering for Assisted Services will lead the engineering strategy, architecture, and delivery of platforms that power human-assisted customer interactions across the bankincluding contact center tooling, advisor/agent workflows, servicing orchestration, customer communication flows, and intelligent automation.

This leader will unify fragmented servicing platforms, modernize legacy components, and accelerate our transition to an event driven, API first, and increasingly AI assisted servicing ecosystem. The Director will oversee engineering teams building next generation capabilities such as AI guided agent experiences, intelligent case routing, natural language search, automated summarization, and contextual recommendationsall designed to elevate both the colleague and customer experience.

The role requires deep engineering leadership, strong architectural discipline, operational excellence, and hands-on experience designing or integrating AI powered applications into complex servicing environments.

Key Responsibilities :

Leadership & Strategy :

- Lead, inspire, and develop high performing engineering teams, fostering a culture of innovation, ownership, and engineering excellence.

- Define the technical strategy for Assisted Services across servicing platforms, omni channel agent tools, workflow engines, and customer interaction systems.

- Drive the adoption of AI assisted servicing capabilities, including conversational AI, machine learningbased recommendations, agent assist tooling, and automated knowledge retrieval.

- Shape and implement an architectural vision that unifies assisted and self service experiences into a cohesive, modern servicing ecosystem.

- Partner with Product, Operations, Risk, Enterprise Architecture, and Data Science to ensure AI solutions are aligned with customer needs, responsible AI standards, and regulatory requirements.

- Bridges the gap across geographically distributed teams, ensuring synergy and a unified team culture. Right mindset and attitude are equally important as technical skills.

- Experience managing teams across different corporate cultures, prior GCC experience will be an advantage

- Drives the adoption of agentic flows and Gen AI practices to solve business problems and improve delivery quality and cycle time

- Demonstrates programme leadership, cross-functional influence, benefits realisation, and executive reporting across business lines

Delivery & Execution :

- Oversee delivery of core servicing capabilities including call center tooling, unified agent desktops, case management, workflow automation, and system integrations.

- Lead engineering efforts to build and deploy AI-driven enhancements such as :

1. Real time agent assist (summaries, recommendations, prompts)

2. Predictive servicing and intelligent routing

3. Contextual data retrieval and knowledge search

4. NLP powered insights to shorten handle times and improve accuracy

- Ensure teams have clear requirements, technical specifications, and a strong delivery operating model to meet timelines and quality expectations.

- Implement robust engineering processes, tooling, and CI/CD pipelines that support rapid iteration and frequent releases.

Platform Reliability, Compliance & Security :

- Embed secure-by-design, privacy, and responsible AI practices across all servicing applications.

- Ensure AI models and features adhere to ethical, compliance, and regulatory guidelinesincluding transparency, explainability, and model risk controls.

- Strengthen platform reliability and performance through observability tooling, automated quality checks, and proactive monitoring.

Cross-Functional Collaboration :

- Collaborate with Data Science and AI teams to operationalize models into production systems, including inference pipelines, model monitoring, and lifecycle management.

- Partner with Operations to understand agent workflows, reduce friction, and identify where AI can drive meaningful improvements in efficiency and consistency.

- Engage with Fraud, Identity, Security, and Compliance teams to ensure AI assisted solutions uphold trust and customer protection.

Technical Expertise :

- Experience in engineering tools to support SDLC processes, driving engineering deliveries and supporting AI tool adoption across the enterprise

- Ability to build agentic flows and processes using AI and Gen AI to solve business and customer problems at scale. Adopting Exponential Engineering Practices including AI-assisted development to improve cycle time and delivery quality.

- Experience building and supporting platforms that drive revenue, with exposure to consumer journeys or fraud ecosystems is a plus

Core Capabilities :

- Demonstrate day-one readiness to operate in the new model adopting new tools and technologies at the expected velocity

- Learning agility is paramount and candidates who can adapt quickly to new technologies will be given preference.

Required Qualifications :

- 12+ years of hands on software engineering experience building large scale, customer-facing systems.

- 10+ years leading engineering teams in complex, multi platform environments.

- Proven experience delivering or integrating AI powered applications, such as agent assist tools, conversational AI, ML-driven analytics, or intelligent process automation.

- Expertise in modern engineering practices, including Agile/Scrum, DevOps, CI/CD, release management, and API-led development.

- Strong proficiency in multiple languages (e.g., Java, Python, JavaScript/React, Go, C#) and experience with cloud platforms (AWS/Azure/GCP).

- Deep knowledge of distributed systems, event driven design, and high availability architectures.

- Excellent communication skills, capable of influencing senior stakeholders across business and technology.

Desired Qualifications :

- Experience in financial services, especially in servicing platforms, contact centers, CRM, case management, identity, or authentication.

- Background deploying or scaling AI/ML solutions (NLP, classification models, vector search, LLM based applications).

- Familiarity with responsible AI frameworks, model governance, and regulatory considerations in a financial services context.

- Ability to navigate complex organizational structures and drive alignment across multiple senior leaders.

Education

- Required : Bachelors degree in Computer Science, Engineering, or similar technical discipline.

- Preferred : Masters degree in Software Engineering, Computer Science, AI/ML, or related field.