Key Responsibilities
Strategic Architecture & Client Leadership
Serve as the technical authority and trusted advisor for C-level stakeholders across enterprise engagements in FSI, including capital markets, banking, and insurance.
Develop and maintain executive client relationships while owning the technical delivery of Amdocs services.
Shape architecture vision spanning Azure cloud, Databricks, GenAI, and modern DevOps pipelines.
Translate regulatory, security, and operational business outcomes into AI and cloud architecture solutions with clarity, strategy, and industry alignment.
GenAI & AI Systems Engineering
Design, develop, and deploy GenAI models using frameworks like OpenAI, LangChain, and retrieval-augmented generation (RAG).
Architect AI systems across data pipelines, API layers, and cloud-native components, including integrations with financial data sources and transaction systems.
Enable agentic AI systems with goal planning, agent tuning, and verification loops tailored to high-compliance environments.
Implement validation frameworks and compliance checkpoints aligned to FSI regulatory expectations.
Cloud Engineering & DevOps Delivery
Architect and deliver highly available, secure, and scalable solutions on Azure and Databricks, aligned to financial-grade operational standards.
Lead design of CI/CD pipelines, infrastructure automation, and integration of AI with enterprise systems used in trading, customer servicing, and fraud detection.
Guide implementation teams, ensuring technical delivery aligns with business outcomes and compliance frameworks.
Collaboration & Mentorship
Collaborate across engineering, data, product, and risk/compliance teams to ensure integrated and impactful solutions.
Mentor cloud and AI engineers, elevating team capabilities and technical excellence.
Act as the primary escalation point for critical delivery challenges and guide resolution across cross-functional teams.
Innovation & Thought Leadership
Stay ahead of emerging GenAI trends, including agent-based systems, LLM orchestration, and autonomous pipelines, and their applicability to capital markets
innovation.
Influence internal capability building, tooling adoption, and IP development with an FSI lens.
Contribute to presales activities including SOWs, effort estimation, and solutioning for FSI clients.
Requirements and Skills
Education
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or related field.
Additional credentials in finance, capital markets, or quantitative disciplines are a
plus.
Technical Skills
10+ years of Data & AI experience
8+ Databricks experience and 8+ years on Azure, with hands-on delivery in regulated industries.
Deep expertise in Python, SQL, and data modeling for structured, time-series, and transactional financial data.
Proficient with OpenAI, LangChain, LangGraph, and RAG to architect scalable GenAI pipelines.
Familiar with agentic AI frameworks, autonomous orchestration, and safe AI design.
Skilled in system architecture across APIs, databases, and AI services tailored to FSI needs.
Strong grasp of MLOps practices including model approval workflows, monitoring, and rollback mechanisms.
Industry Experience
Proven track record of building AI solutions in financial services, banking, or capital markets domains.
Experience with regulatory constraints, auditability, and explainability requirements in AI systems.
Use-case knowledge in areas such as AML/KYC, client onboarding, investment research, regulatory compliance, and trade support.
Preferred Experience
Familiarity with LLMs such as GPT, LLama, Claude, or Gemini in financial services scenarios.
Exposure to financial NLP (e.g., earnings calls, 10-Ks), financial graphs, and transaction analysis.
Understanding of cloud security models and data governance in FSI environments.
Soft Skills
Excellent verbal and written communication skills, especially when working with non-technical financial stakeholders.
Collaborative, proactive, and able to navigate cross-functional teams with finance, risk, and tech stakeholders.
Passion for driving innovation in highly regulated, data-sensitive environments.
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