We are seeking a Senior Vice President (SVP) of Software Engineering who combines strategic leadership with hands-on technical expertise. This role is ideal for a technology leader passionate about building software at scale using cloud-native architectures, data engineering best practices, and modern UI development with Angular, while driving Agentic AI development within a SAFe Agile operating model. You will lead large-scale engineering initiatives, mentor senior engineering talent, and actively contribute to solution design and development. Drive Agentic AI development across product lines, leveraging LLMs for implementing business use cases and AI-driven automation to accelerate SDLC and deliver business value. Architect scalable, high-performing systems using cloud-native architecture and proven design patterns. Build foundational frameworks across middleware and UI to accelerate development and reduce maintenance overhead. Lead data engineering efforts, including data modelling, data pipelines (ETL/ELT), batch and streaming data processing, data governance (catalog/lineage) and quality engines, and big data technologies. Align engineering initiatives with SAFe Agile principles, ensuring predictable delivery and continuous improvement.

Job Duties. Drive Agentic AI development across product lines, leveraging LLMs for implementing business use cases and AI-driven automation to accelerate SDLC and deliver business value. Architect scalable, high-performing systems using cloud-native architecture and proven design patterns. Build foundational frameworks across middleware and UI to accelerate development and reduce maintenance overhead. Lead data engineering efforts, including data modelling, data pipelines (ETL/ELT), batch and streaming data processing, data governance (catalog/lineage) and quality engines, and big data technologies. Align engineering initiatives with SAFe Agile principles, ensuring predictable delivery and continuous improvement. Actively contribute to product requirements analysis and solution architecture. Lead proof-of-concepts, design of critical components, and code reviews. Implement agents using Google’s ADK. Implement foundational components across Java, Python, and React or Angular for enterprise-grade applications. Champion AI-based code generation tools to automate repetitive engineering tasks. Collaborate with DevOps teams to optimize CI/CD pipelines, containerization (Docker/Kubernetes), and observability. Mentor and lead a global team of engineering leads and senior developers. Foster a culture of innovation, technical excellence, and accountability. Ensure compliance with security, regulatory, and performance standards.

CT1

• Only those lawfully authorized to work in the designated country associated with the position will be considered.

• Please note that all Position start dates and duration are estimates and may be reduced or lengthened based upon a client’s business needs and requirements.

Must Have Skills/Attributes: AI, Java, Python, Spring Boot

Nice To Have Skills/Attributes: GenAI tools, LLM (Large Language Model), Machine Learning

Experience Desired: Strong experience in Java, microservices, RESTful APIs, and distributed architectures (10+ yrs); Hands-on experience in leadership roles (8+ yrs); Experience in the Python/LLMs/AI/ML technologies (2+ yrs)

Required Minimum Education: High School Diploma or equivalent

Preferred Education: Master’s Degree

Preferred Certifications/Licenses: Certifications in AI/ML engineering & Cloud Architecture (AWS/Azure/Google Cloud Platform)

C2C is not available, Bachelor’s or master’s (preferable) degree in engineering or sciences

Preferred License/Certification Certifications in AI/ML engineering & Cloud Architecture (AWS/Azure/Google Cloud Platform), 15+ years in software engineering, with 8+ years in hands-on leadership roles. Strong expertise in microservices, RESTful APIs, and distributed architectures. Experience in the following AI/ML technologies:

-Development: Python, FastAPI, Java, Spring AI, Async Programming

-Foundational Models: Gemini, OpenAI, Claude, Llama, Local Models

-Machine Learning: PyTorch, TensorFlow, Fine-tuning

-AI Frameworks: Google’s ADK, LangChain, LlamaIndex, Hugging Face

-Orchestration: LangGraph, Multi-Agent Systems

-Retrieval Augmented Generation: PostgreSQL, Vector DBs, Advanced Retrieval

-Deployment: Docker, Production APIs, Monitoring

-Applied Methodology: Prompt Engineering, Workflow Design, GenAI Optimization Must have some Python/GenAI/LLM experience. Need atleast a year of AI experience., Experience with Financial Risk and Data.