Senior  ML LLM Engineer

Job Title:- Senior  ML LLM Engineer/Technical Lead

Summary:  This position will own the design, fine-tuning, deployment, and continuous optimization of Large Language Model (LLM)-powered services at scale. You will architect AI solutions that not only work but perform reliably in high-volume, mission-critical environments. This role requires a high-impact leader who can translate business objectives into scalable AI systems, accelerate model deployment cycles, and ensure measurable ROI from every AI initiative.

Key Responsibilities:

• High-Impact Model Development & Optimization
• Rapidly design, fine-tune, and benchmark LLMs (GPT-4o, Claude, open-source models) to meet performance and cost-efficiency targets.
• Architect Retrieval-Augmented Generation (RAG) pipelines with optimized query latency for real-time user experiences.
• Select and implement models for scalability across multiple product lines and operational workflows.
• Production-Grade AI Deployment
• Lead end-to-end deployment of AI services into client-facing products and internal tools, ensuring >99% uptime.
• Build scalable APIs and microservices for AI model integration across multiple environments.
• Partner with DevOps and Security teams to ensure AI deployments meet compliance, privacy, and SOC2/SOC1 standards.
• MLOps & Lifecycle Management at Scale
• Implement automated pipelines for model training, evaluation, deployment, and monitoring.
• Establish and track performance metrics (latency, accuracy, hallucination rate, cost per query).
• Proactively manage model drift and retraining cycles to maintain performance under changing data conditions.
• Strategic Collaboration & Impact
• Work with TSL and AISO (AI Service Organization) teams to align AI capabilities with growth objectives.
• Serve as the technical AI subject matter expert for executive strategy sessions and client discussions.
• Evaluate emerging AI technologies and recommend adoption strategies that deliver competitive advantage.

Knowledge, Skills, and Abilities

• 3-5 years in ML engineering, applied NLP, or AI systems architecture with proven production deployments.
• Expert in Python and AI frameworks (LangChain, HuggingFace, LlamaIndex, FastAPI).
• Strong experience with Azure AI stack, vector databases, and streaming architectures.
• Deep understanding of model evaluation, monitoring, drift detection, and retraining.
• Ability to rapidly prototype and iterate while maintaining enterprise-grade reliability.
• Data-driven decision-making with a focus on measurable business outcomes (ROI, adoption, cost optimization).
• Experience scaling AI solutions for B2B SaaS or high-transaction platforms.
• Familiarity with AI governance, compliance, and ethical frameworks.
• Track record of delivering AI features or tools that directly increased revenue, reduced costs, or accelerated workflows.