Senior AI/ML Engineer - Generative AI & LLM

Role Overview

We are seeking a Senior AI/ML Engineer specializing in Generative AI, Large Language Models (LLM), and agentic systems to lead impactful machine learning projects at scale. The role involves leading design, development, and delivery of scalable AI/ML solutions that drive measurable business value.

Key Responsibilities

• Lead the architecture, creation, deployment, and expansion of machine learning, LLM, and agent-based solutions to generate tangible business outcomes.
• Participate actively in developing robust ML pipelines and workflows with a focus on reproducibility, continuous integration/deployment, data and feature integrity, code quality, testing, and deployment efficiency.
• Facilitate integration of AI/ML functionalities into enterprise software to enable seamless adoption and maximize benefits.
• Make critical system architecture decisions ensuring the AI/ML solutions are scalable, dependable, cost-effective, and maintainable.
• Develop and implement reusable frameworks, engineering patterns, and standards to boost productivity and scalability across engineering teams.

Required Skills and Competencies

• Expertise in designing and deploying scalable AI/ML systems and production-grade engineering.
• Ability to productionize ML, LLM, and Generative AI models and agentic systems into high-performance, reliable services optimized for latency, throughput, and costs.
• Experience building scalable, batch and real-time ML pipelines for both training and inference ensuring reproducibility across multiple environments.
• Skillful in orchestrating automated end-to-end ML workflows incorporating CI/CD pipelines and managing data and feature consistency across platforms.
• Lead full production rollout of AI/ML solutions integrating enterprise applications through microservices, APIs, and Docker containerization.
• Proficiency in advanced MLOps practices encompassing scalable system design, ML governance, production-grade monitoring, and resilient deployment strategies.
• Hands-on with Git, Azure DevOps, and modern build/test/deploy tooling plus familiarity with enterprise ML platforms like Databricks MLflow and AI Foundry.

Eligibility

Open to all graduates who meet the skill and experience requirements.