Senior Data AI Engineer – GenAI & Agentic AI

Position: Forward Deployed Engineer (Python/PySpark + Claude AI + Data & MLOps)

Job type: Full-time/Permanent hiring

Location: Hybrid/Onsite- Toronto, ON || New Jersey, New York City, Charlotte, Columbus (OH), Pittsburgh, Boston, Malvern (PA), Washington DC

USA Locations (14 openings)

Canada Location (11 openings)

We are seeking an experienced Forward Deployed Engineer (FDE) to design, build, and deploy enterprise-scale AI and data-driven solutions for leading Banking, Financial Services, and Insurance (BFSI) clients. The ideal candidate will possess strong expertise in Data Engineering, Generative AI, Large Language Models (LLMs), Cloud Technologies, APIs, and MLOps/LLMOps.

In this role, you will work directly with business stakeholders, client SMEs, architects, and engineering teams to transform complex business requirements into scalable, production-ready AI solutions. You will be responsible for full lifecycle delivery, from discovery and prototyping through deployment, operationalization, and post-production support.

Key Responsibilities

• Design, develop, and deploy enterprise-grade AI and data applications using Python, PySpark, SQL, Claude AI, APIs, and modern cloud platforms.
• Build AI-powered solutions utilizing Prompt Engineering, Retrieval-Augmented Generation (RAG), Vector Databases, Semantic Search, and Agentic AI frameworks.
• Architect scalable data pipelines, data platforms, and AI solutions with focus on performance, security, reliability, and cost optimization.
• Develop and support batch, streaming, and real-time data processing solutions.
• Implement MLOps and LLMOps frameworks including CI/CD, model lifecycle management, monitoring, deployment automation, and production support.
• Collaborate closely with business stakeholders to understand requirements and translate them into technical designs and implementation roadmaps.
• Conduct data discovery, profiling, quality assessment, and feasibility analysis on large and diverse datasets.
• Build rapid prototypes and proof-of-concepts using real business data and APIs.
• Implement security, governance, privacy, and compliance controls across AI and data solutions.
• Troubleshoot and resolve production issues, performance bottlenecks, and platform incidents.
• Support solutioning activities, technical workshops, client presentations, and RFP responses.
• Mentor engineering teams and contribute to best practices, reusable frameworks, and technical standards.
• Work directly with client teams in a forward-deployed model to accelerate business outcomes and solution adoption.

Required Technical Skills

Programming & Data Engineering

• Python
• PySpark
• SQL
• ETL/ELT Development
• Data Pipelines
• Batch and Streaming Processing
• DataOps

AI / Generative AI

• Claude AI
• Large Language Models (LLMs)
• Prompt Engineering
• Agentic AI
• Retrieval-Augmented Generation (RAG)
• Vector Databases
• Semantic Search
• AI Copilots & AI Workflow Automation

API & Application Development

• REST APIs
• FastAPI
• Enterprise Application Integration
• Microservices

MLOps / LLMOps

• MLflow
• CI/CD Pipelines
• Model Lifecycle Management
• Monitoring & Observability
• Production Deployment
• Rollback & Recovery Strategies

Platform & DevOps

• Docker
• Kubernetes
• Git
• Airflow
• Cloud Platforms
• Infrastructure Automation

Security & Governance

• IAM/RBAC
• Data Security
• Data Privacy
• Encryption
• Secrets Management
• Compliance & Auditability

Domain Experience

Strong experience within one or more of the following:

• Banking
• Financial Services
• Insurance (BFSI)

Experience working in regulated, secure, and highly governed enterprise environments is highly preferred.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, Data Management, or related discipline.
• 10-14+ years of experience in Data Engineering, AI Applications, Cloud Platforms, and Software Engineering.
• Proven experience building and deploying AI/GenAI solutions into production.
• Strong client-facing and consulting experience.
• Ability to lead architecture discussions and provide technical leadership.
• Experience working directly with business stakeholders and cross-functional teams.

Preferred Certifications

• Cloud Platform Certifications (AWS, Azure, GCP)
• Kubernetes Certifications
• AI Engineering Certifications
• Data Engineering Certifications
• Enterprise Architecture Certifications
• Security Certifications