Senior Manager

Position Summary

We are seeking a skilled and experienced AI Engineer to design, build, and operate production-grade generative AI capabilities. This role focuses on developing advanced Retrieval-Augmented Generation (RAG) pipelines, sophisticated multi-agent systems, and robust automated evaluation frameworks. The ideal candidate will bridge the gap between applied data science and rigorous software engineering, focusing on building scalable, secure, and cost-efficient AI-powered products.

Job Responsibilities

• GenAI Application Architecture: Architect and deploy production-grade LLM applications using microservices (e.g., FastAPI) and robust software engineering practices, including APIs, integration testing, and CI/CD.
• Advanced RAG Engineering: Build and optimize end-to-end RAG pipelines, including document ingestion, semantic chunking strategies, metadata enrichment, vector database indexing (e.g., Azure AI Search), hybrid search (e.g., BM25 + vectors), and reranking to ground model outputs and minimize hallucinations.
• Agentic AI Workflows: Design and implement agentic AI solutions, incorporating tool-calling, state management, memory architectures, planning vs. reacting agent design, reflection loops, and multi-agent coordination using frameworks like LangGraph and AutoGen. Develop human-in-the-loop systems for verification and control.
• LLMOps & Lifecycle Management: Establish and manage operational standards for the AI lifecycle, including model fine-tuning, prompt versioning, semantic caching, rate limiting, and dynamic model routing to optimize for latency, cost (token economy), and performance. Implement CI/CD pipelines for AI/ML workloads.
• Model Evaluation & Observability: Develop and implement automated evaluation loops using LLM-as-a-judge methodologies to assess faithfulness, relevance, and toxicity. Monitor model drift, performance, and reliability using frameworks such as RAGAS, TruLens, and DeepEval.
• AI Safety & Governance: Implement strict guardrails (e.g., NeMo Guardrails, Llama Guard) to protect against prompt injection, data leakage, and other vulnerabilities, ensuring alignment with enterprise Responsible AI standards.
  
  

Education

Bachelor of Engineering

Master of Technology in Information Technology or Computer

Work Experience

10+ years of experience in a pharma analytics company or with a Pharma company in an analytics role

Behavioural Competencies

Teamwork & Leadership

Motivation to Learn and Grow

Ownership

Cultural Fit

Talent Management

Technical Competencies

Problem Solving

Lifescience Knowledge

Communication

Project Management

Attention to P&L Impact

Capability Building / Thought Leadership

Scale of revenues managed / delivered

Scale of resources managed