About client:

Global AI & Innovation team to build next-generation AI platforms, autonomous agents, and real-time intelligence solutions that transform how a global enterprise operates and serves its customers.

Position Summary:

Seeking a highly skilled Senior AI/ML Engineer to lead the design, development, deployment, and governance of enterprise-scale AI solutions.

Key Responsibilities:

AI Solution Engineering & Architecture:

- Design, develop, and deploy end-to-end AI/ML solutions, including microservices, RAG architecture, and agentic AI workflows.

- Build scalable and reusable AI services that support enterprise-wide business use cases.

- Evaluate and integrate emerging AI technologies, frameworks, and foundation models.

MLOps, Data Science & Advanced Analytics:

- Implement and maintain MLOps pipelines for model training, deployment, monitoring, versioning, and lifecycle management.

- Automate model deployment, performance monitoring, and drift detection processes.

- Optimize AI workloads for cost, scalability, and performance across Azure and AWS cloud platforms.

- Design, develop and deploy scalable, secured, predictive statistical ML models to continuously empower business functions.

Real-Time Data Engineering:

- Build low-latency data ingestion, processing, and orchestration pipelines supporting AI applications.

- Design and maintain vector databases, knowledge repositories, and semantic search capabilities.

- Enable real-time analytics and AI-driven decision-making using large-scale operational and transactional data.

AI Governance, Security & Responsible AI:

- Implement security-by-design principles across AI solutions and data platforms.

- Protect sensitive financial and operational data through robust access controls and governance frameworks.

- Mitigate risks related to prompt injection, hallucinations, data leakage, bias, and regulatory compliance.

- Ensure adherence to Responsible AI, privacy, and enterprise security policies.

Business Partnership & Value Realization:

- Collaborate with business leaders, product teams, and solution architects to identify high-value AI opportunities.

- Translate business problems into scalable AI solutions that drive operational efficiency, growth, and innovation.

- Measure and communicate business outcomes, model performance, and ROI from AI initiatives.

Required Qualifications:

- Bachelor's or master's degree in computer science, Data Science, Engineering, Artificial Intelligence, or related field.

- 7+ years of experience in AI/ML engineering, software engineering, data engineering, or cloud-based solution development.

- Hands-on experience with Generative AI, LLMs, RAG frameworks, AI agents, and vector databases.

- Strong foundation in statistics, predictive modeling, and machine learning.

- Strong proficiency in Python and modern AI/ML frameworks (PyTorch, TensorFlow, LangChain, Semantic Kernel, etc.).

- Experience with Azure AI Services, AWS AI/ML services, and cloud-native architectures.

- Knowledge of MLOps, CI/CD, containerization (Docker/Kubernetes), and modern software engineering practices.

Preferred Qualifications:

- Experience in financial services, logistics, operations, or other highly regulated industries.

- Azure AI Engineer, AWS Machine Learning, Snowflake, or related certifications.

Success Measures:

- Accelerated delivery of AI-powered business solutions

- Improved AI platform scalability, reliability, and security

- Reduced infrastructure and model operating costs

- Increased adoption of AI capabilities across business functions

- Demonstrated business value and measurable ROI from AI investments