Description
We are seeking an Assistant Vice President - Applied AI Engineer to design and build core AI/ML solutions that power our enterprise AI capabilities.
You will take ownership of significant AI subsystems , from agentic workflows and LLM applications to evaluation pipelines and MLOps tooling , delivering production-grade solutions that are secure, scalable, and aligned with our architectural vision.
Your responsibilities will include:
- Development and delivery of high-quality software solutions using industry-aligned programming languages, frameworks, and tools.
- Cross-functional collaboration with product managers, designers, and other engineers to define software requirements and devise solution strategies.
- Collaboration with peers, participation in code reviews, and promotion of a culture of code quality and knowledge sharing.
- Staying informed of industry technology trends and innovations and actively contributing to the organisation’s technology communities.
- Adherence to secure coding practices to mitigate vulnerabilities and ensure secure software solutions.
- Implementation of effective unit testing practices to ensure proper code design, readability, and reliability.
As an Assistant Vice President, you will be expected to:
- Advise and influence decision-making, contribute to policy development, and take responsibility for operational effectiveness.
- Lead a team performing complex tasks, using well-developed professional knowledge and skills to deliver on work that impacts the whole business function.
- Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives, and determination of reward outcomes.
You will need to have:
- A Bachelor's degree (or above) in Computer Science, Engineering, Mathematics, or a related discipline.
- 8+ years of software engineering experience with at least 3 years building AI/ML systems, scalable ML infrastructure, or model serving platforms at enterprise scale.
- Strong proficiency in Python (FastAPI, asyncio) and/or Go/Java, with production experience building APIs and microservices serving high-throughput, low-latency workloads.
- Hands-on experience developing agentic AI systems and LLM applications, including multi-agent orchestration, tool use, planning frameworks, and deployment of multi-step AI workflows.
- Solid technical knowledge of prompt engineering, RAG architectures, and modern agentic frameworks.
- Working experience with GenAI/LLM systems , prompt engineering, retrieval-augmented generation, model serving, and OpenAI-compatible API surfaces.
- Strong understanding of distributed systems architecture , microservices, cloud platforms, API design, and event-driven architectures.
- Experience with AWS services , EC2/EKS, S3, IAM, RDS, and at least one AI service.
- Hands-on experience with Docker and Kubernetes , containerising applications and deploying to orchestrated environments.
- Experience with CI/CD pipelines, Infrastructure-as-Code, and observability tools.
Some other highly valued skills may include:
- Experience building evaluation frameworks for agentic systems.
- Experience in vector databases, knowledge graphs, semantic search, and memory systems for stateful agents.
- Experience implementing AI safety controls.
- Knowledge of AI security frameworks.
- Familiarity with model fine-tuning techniques.
- Knowledge of responsible AI practices, model governance, and security considerations for autonomous systems.
- Understanding of Zero Trust architecture and identity systems.
- Background in financial services , understanding of regulatory requirements, data residency, and compliance obligations.
- Experience with GPU workload management and inference optimisation.