Senior Consultant Specialist

We are currently seeking an experienced professional to join our team in the role of Senior Consultant Specialist.

Principal responsibilities:

• Own end-to-end delivery of AI-enabled applications, from initial discovery and solution scoping through prototype, production implementation, deployment, and adoption support.
• Partner with business stakeholders to understand operational workflows, pain points, acceptance criteria, and measurable success outcomes.
• Translate business requirements into practical AI / automation workflows, including LLM-powered features, RAG-based knowledge solutions, agentic workflows, APIs, and user-facing tools where appropriate.
• Build production-grade software using technologies such as Python, JavaScript / TypeScript, backend services, APIs, databases, and modern web or integration frameworks.
• Integrate AI / ML capabilities into enterprise applications, including prompt orchestration, retrieval pipelines, model APIs, evaluation logic, monitoring, and guardrails.
• Collaborate with product managers, AI researchers, data scientists, platform engineers, cyber security, risk, compliance, and operations teams to ensure solutions are fit for enterprise deployment.
• Design for reliability, maintainability, scalability, security, auditability, and responsible AI use in a regulated banking environment.
• Support deployment activities including CI/CD, environment configuration, observability, performance tuning, incident troubleshooting, and production readiness reviews.
• Gather feedback from real users and production telemetry to iterate on solution quality, model behavior, workflow usability, and business value.
• Act as a technical thought partner to business teams, helping them understand AI capabilities, limitations, trade-offs, and responsible adoption patterns.

Requirements:

• Bachelor’s degree or above in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Mathematics, Software Engineering, or a related technical discipline, or equivalent practical experience.
• Around 5+ years of hands-on experience in AI engineering, LLM application engineering, machine learning engineering, data-intensive software engineering, or full-stack engineering with meaningful AI delivery exposure.
• Strong practical understanding of modern AI / ML and LLM application architectures, including RAG, embeddings, prompt engineering, model APIs, AI workflow orchestration, evaluation, monitoring, and guardrails.
• Hands-on experience building AI-powered applications or platforms, such as enterprise search, document intelligence, chatbot / assistant solutions, Text-to-SQL, agentic workflows, knowledge management, or workflow automation.
• Strong programming capability in Python, with the ability to build reliable AI pipelines, backend services, integrations, evaluation scripts, and automation tools.
• Solid software engineering capability in at least one additional application development language or ecosystem such as JavaScript / TypeScript, Java, or similar, with experience building APIs, services, UI components, or enterprise integrations.
• Proven experience moving AI or data-driven solutions beyond proof of concept into production or production-like environments, including testing, CI/CD, logging, monitoring, deployment, support, and iterative improvement.
• Ability to reason about AI system quality and trade-offs, including accuracy, hallucination risk, latency, cost, retrieval quality, data privacy, security, observability, maintainability, and user experience.
• Strong problem-solving and stakeholder communication skills, with the ability to translate business workflows into AI solution designs and explain technical trade-offs to both engineers and non-technical users.
• Strong ownership mindset, hands-on delivery attitude, and willingness to debug code, inspect data, tune prompts / retrieval logic, integrate systems, and unblock production delivery issues directly.