Senior AI Engineer

Role overview

Key accountabilities

• Lead agentic AI, autonomous workflow, multi-agent, and enterprise orchestration design and implementation; define agent and MCP patterns.
• Architect vector stores, embedding pipelines, retrieval systems, document parsing, processing, and metadata extraction.
• Lead Azure and GCP AI cloud architecture; design Kafka event-driven systems and establish OpenShift/Kubernetes model-serving and MLOps standards.
• Mentor engineers; lead design and code reviews; uphold CI/CD, testing, code management, and documentation practices.
• Partner with business stakeholders and product owners, align with enterprise architecture, support governance, and communicate technical trade-offs.
• Maintain AI solution SLAs, monitoring, and alerting; ensure alignment with data policies, ethical standards, and regulations.

Technical competencies

• Expertise in LLMs, embedding models, generative AI, orchestration frameworks, agent development, vector databases, RAG, and knowledge retrieval.
• Python, AI/ML frameworks such as LangChain, LlamaIndex, or Semantic Kernel; TensorFlow or PyTorch; MLflow or TFX.
• API design, microservices, event-driven architecture, advanced SQL, Git, GitHub/GitLab, and CI/CD.
• Azure and/or GCP; object storage such as S3, GCS, or ABS; Kafka, Spark, Airflow, or Apache NiFi.
• Docker, Kubernetes/OpenShift, MLOps, model monitoring, versioning, and management.
• Technical leadership, mentoring, stakeholder communication, executive reporting, and cross-functional collaboration.

Qualifications and experience

• Bachelor’s or master’s degree in computer science, software engineering, data science, or a related field.
• At least 7 years of software engineering experience, including at least 4 years focused on AI/ML applications.
• Demonstrated leadership delivering AI solutions in production environments.
• Expert experience with Azure or GCP, OpenShift/Kubernetes, and enterprise integration patterns.
• Banking or financial services experience is mandatory.
• Financial-services regulatory compliance, data governance, and security experience is preferred.
• Azure AI Engineer, GCP ML Engineer, or equivalent certifications are strongly preferred.

Employer offering

• The employer describes an innovation-driven digital environment, international exposure, employee well-being, work-life balance, and competitive compensation and benefits.