Senior AI Engineer

We’re looking for a Senior AI Engineer (Senior/Principal Consultant) to join our Technology Delivery team. In this role, you’ll combine deep expertise in AI/ML engineering and software development to design, build, and deploy advanced generative AI and agentic systems for leading financial services clients. You’ll work hands-on across the full AI engineering lifecycle, from architecting intelligent multi-agent systems to deploying scalable production-grade AI applications within enterprise environments. As a senior consultant, you’ll also collaborate closely with multidisciplinary teams and client stakeholders to drive innovation, accelerate adoption, and deliver measurable business impact.

• →Architect and develop autonomous AI systems leveraging multi-modal large language models across text, image, audio, and video
• →Design and implement agentic workflows using prompt engineering, Retrieval-Augmented Generation (RAG), APIs, and enterprise data integrations
• →Fine-tune, optimize, and deploy large language and multi-modal models with a focus on scalability, reliability, and low-latency performance
• →Build scalable MLOps pipelines and cloud-native AI applications to support secure, production-grade deployments
• →Collaborate with clients and cross-functional teams to shape AI engineering strategy and accelerate GenAI adoption across complex environments

• Bachelor’s degree or higher in Computer Science, Artificial Intelligence, Engineering, or a related STEM discipline
• Proven hands-on experience deploying LLMs and multi-modal AI models within enterprise or large-scale production environments
• Strong software engineering expertise in Python, including backend development, API design, and distributed systems
• Solid understanding of scalable MLOps, observability, CI/CD practices, and cloud-native AI deployment architectures
• Excellent communication, stakeholder management, and problem-solving skills within agile delivery environments

• Experience building AI agent frameworks or autonomous orchestration platforms
• Knowledge of vector databases, semantic search, and advanced RAG architectures
• Experience with cloud platforms such as AWS, Azure, or GCP for AI workloads
• Familiarity with financial services, banking, or regulated enterprise environments
• Exposure to AI governance, model monitoring, and responsible AI practices