Senior AI Engineer

Role summary

AI architecture and platforms

• Lead agentic AI, autonomous workflow, multi-agent, and enterprise orchestration design and implementation.
• Define AI agent and MCP architecture patterns, evaluate emerging technologies, and recommend adoption strategies.
• Architect vector stores, embedding pipelines, retrieval systems, and document parsing, processing, and metadata extraction frameworks.
• Define API standards and integration patterns for bank-wide AI services.

Cloud and technical leadership

• Lead Azure and GCP AI cloud architecture for scalability, security, and cost optimization; design Kafka event-driven applications.
• Set standards for OpenShift/Kubernetes model serving, monitoring, and MLOps.
• Mentor AI engineers; lead design and code reviews; uphold CI/CD, testing, code management, knowledge management, and documentation practices.

Collaboration and governance

• Work with product owners, business stakeholders, enterprise architecture, and IT to align AI solutions with bank technology strategy and target data architecture.
• Explain technical concepts and trade-offs to senior management and steering committees; contribute to governance, data-policy, ethical, and regulatory compliance.
• Define solution SLAs and implement monitoring and alerting.

Technical competencies

• Deep expertise in LLMs, embedding models, generative AI, AI orchestration, complex agents, multi-agent systems, vector databases, RAG, and knowledge retrieval.
• Strong background in TensorFlow or PyTorch, model deployment tools such as MLflow or TFX, and end-to-end ML lifecycle management.
• Advanced Python; AI/ML frameworks such as LangChain, LlamaIndex, or Semantic Kernel; API design, microservices, and event-driven architecture.
• Advanced SQL, including stored procedures, window functions, temporary tables, and recursive queries.
• Expert-level Azure and/or GCP and object storage; advanced Kafka, Spark, and Airflow or Apache NiFi; Docker and Kubernetes/OpenShift.
• MLOps knowledge covering model monitoring, versioning, and management; financial-services industry experience.