Senior AI Platform & GenAI Engineer

We are seeking a highly experienced Sr Machine Learning Engineer to design, develop, deploy, and scale enterprise-grade Artificial Intelligence, Machine Learning, Generative AI, and Agentic AI solutions. The ideal candidate will possess deep expertise in AI platform engineering, cloud-native architectures, MLOps, and intelligent automation. This role requires hands-on experience building production-ready AI applications, Retrieval-Augmented Generation (RAG) solutions, AI agents, and large-scale machine learning platforms while driving AI innovation, governance, and business transformation across the organization.

KEY RESPONSIBILITIES

• Design, develop, test, deploy, and maintain Machine Learning, Generative AI, and Agentic AI solutions in production environments.

• Collaborate with Data Scientists, Software Engineers, Architects, and Dev Ops teams to deliver scalable AI products and enterprise platforms.

• Build and operationalize Large Language Model (LLM) applications using foundation models and enterprise AI services.

• Design and implement Retrieval-Augmented Generation (RAG) architectures integrating enterprise knowledge repositories, vector databases, and semantic search capabilities.

• Develop AI-powered applications utilizing advanced prompt engineering, context management, and reasoning techniques.

• Build and orchestrate AI agents and multi-agent systems capable of autonomous reasoning, planning, workflow execution, and decision support.

• Establish prompt engineering frameworks, evaluation methodologies, and optimization processes to improve AI application performance and reliability.

• Translate business requirements into scalable AI-driven solutions that deliver measurable business value.

• Design, build, deploy, and maintain AI/ML and Generative AI platforms on AWS and Databricks.

- Data Ingestion

- Data Preparation

• Implement and maintain MLOps and LLMOps frameworks for enterprise-scale AI lifecycle management.

• Develop CI/CD automation processes supporting AI application delivery and model deployment.

• Build AI observability and monitoring solutions to track:

- Data Drift

- Hallucinations

- Cost Optimization

- Business Outcomes

• Ensure production AI systems meet requirements for reliability, scalability, performance, security, and compliance.

• Evaluate emerging AI technologies, frameworks, platforms, and foundation models for enterprise adoption.

AGENTIC AI & INTELLIGENT AUTOMATION

• Design and implement agentic AI workflows integrated with enterprise systems, APIs, databases, and knowledge repositories.

• Develop intelligent automation solutions that increase operational efficiency and reduce manual effort.

• Build human-in-the-loop review mechanisms and governance workflows for AI-assisted decision making.

• Develop tool-using AI agents capable of securely interacting with enterprise applications, APIs, and external services.

• Implement agent orchestration patterns to support complex business workflows and decision automation.

AI GOVERNANCE & RESPONSIBLE AI

• Develop and maintain documentation, standards, policies, and governance frameworks for AI and Machine Learning solutions.

• Ensure compliance with Responsible AI principles, including:

- Transparency

- Explainability

- Privacy

- Security

- Regulatory Compliance

• Partner with Risk, Security, Legal, and Governance teams to establish enterprise AI controls and monitoring capabilities.

• Support model validation, explainability, auditability, and compliance requirements.

• Implement governance controls for AI lifecycle management and operational oversight.

LEADERSHIP & STRATEGY

• Serve as a technical leader and mentor to AI Engineers, Data Scientists, and Software Engineering teams.

• Contribute to enterprise AI strategy, architecture…