Senior AI Engineer

As a Senior AI Engineer at Coforge Ltd., you will design and deliver scalable AI and analytics solutions that support predictive, generative, and intelligent automation. The role is based onsite in Oaks, PA and focuses on enterprise architecture, building reliable Python and SQL foundations, and deploying capabilities on Microsoft Azure. Experience in financial services and regulated environments is highly desirable.

What you’ll do

• Design end-to-end AI and analytics solutions for predictive, generative, and intelligent automation use cases.
• Develop scalable architectures for model training, inference, feature generation, and analytical workloads.
• Ensure solutions are resilient, extensible, and aligned with enterprise architecture standards.
• Establish traceability and explainability across AI workflows and outputs.
• Drive architecture decisions that support future AI initiatives and scalability needs.
• Build clean, modular, maintainable Python applications for AI and analytics delivery.
• Create reusable components and frameworks for machine learning and generative AI workloads.
• Implement robust error handling, logging, monitoring, and automated testing practices.
• Integrate AI/ML models into enterprise applications and business workflows.
• Optimize code performance while maintaining strong engineering standards.
• Develop and optimize complex SQL using CTEs, window functions, aggregates, and advanced analytical patterns.
• Support large-scale analytical workloads and participate in performance tuning initiatives.
• Design approaches for entity resolution, relationship discovery, and AI-driven analytics.
• Ensure accuracy and consistency in analytical outputs and reporting.
• Design and implement secure, scalable AI solutions on Microsoft Azure, using Azure-native services for deployment, monitoring, and governance.
• Implement security controls including RBAC and managed identities, aligned with compliance requirements.
• Define environment strategy across Development, Test, and Production environments.
• Optimize cloud resource utilization and cost efficiency.
• Design solutions for entity mapping, relationship modeling, network analysis, and knowledge graph use cases.
• Develop reusable AI features that accelerate future AI initiatives and enable pattern discovery through intelligent contextual modeling and analytical frameworks.
• Support integration of internal and external sources to enrich AI-driven insights.
• Design AI architectures that can be reused across multiple AI and business scenarios.
• Ensure solutions meet regulatory, compliance, and audit requirements, with governance of AI-generated outcomes.
• Collaborate with business stakeholders across risk, operations, compliance, and analytics functions.
• Apply quality controls to ensure accuracy and reliability of AI-driven insights.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Engineering, Data Science, or a related field.
• 8+ years of software engineering experience, including 4+ years focused on AI/ML solutions.
• Expert-level Python programming skills.
• Strong SQL expertise, including query optimization and analytical processing.
• Hands-on experience with Microsoft Azure and Azure AI services.
• Experience designing and deploying enterprise-scale AI solutions.
• Strong understanding of the AI/ML lifecycle, including model deployment, monitoring, and governance.
• Experience implementing secure and compliant cloud architectures.

Technologies

• Python
• SQL
• CTEs
• Window functions
• Aggregates
• Microsoft Azure
• RBAC
• Managed identities

Preferred skills

• Experience with Generative AI, LLMs, RAG, Knowledge Graphs, and Agentic AI frameworks.
• Experience with Azure OpenAI, Azure AI Foundry, Azure Machine Learning, and Cognitive Services.
• Familiarity with graph analytics, relationship modeling, and entity resolution.
• Financial Services domain experience including Risk, Compliance, Asset Management, Banking, or Capital Markets.
• Exposure to MLOps, CI/CD pipelines, and AI governance frameworks.

Key skills

• AI Solution Architecture
• Generative AI (LLMs)
• Azure OpenAI and Azure AI Services
• Python Development
• Advanced SQL
• Azure Cloud Architecture
• AI Governance and Explainability
• Entity Resolution and Relationship Modeling
• Knowledge Graphs
• Machine Learning Integration
• Model Deployment and Monitoring
• Financial Services Domain