Job Description Summary
We are seeking a Senior AI Architect to lead the design and delivery of enterprise grade AI platforms and solutions across business units. You will define reference architectures, steer build vs buy decisions, and guide multi disciplinary teams from discovery through production and ongoing operations. The ideal candidate combines deep hands on engineering with architectural judgment across data, ML/GenAI, applications, security, and governance—translating business strategy into secure, scalable, cost efficient AI systems.
Job Description
Key Responsibilities
- Translate business strategies into AI roadmaps and target architectures that guide enterprise-wide adoption.
- Lead architecture governance, establishing reference patterns for RAG, fine‑tuning, classical ML, and hybrid search/graph solutions.
- Define and enforce NFRs, SLOs, and FinOps guardrails to ensure scalable, reliable, and cost‑efficient AI systems.
- Design and deliver end‑to‑end AI solutions, from data acquisition and feature engineering to model/prompt development and production deployment.
- Embed security, privacy, and compliance controls across AI workflows, including PII protection and audit readiness.
- Establish evaluation frameworks (offline metrics, HITL, A/B testing, safety filters) to ensure quality, safety, and robustness of GenAI and ML solutions.
- Integrate AI systems with enterprise data platforms, vector databases, graph stores, and ontology‑driven data contracts for interoperability.
- Implement and mature ML/LLMOps practices, including CI/CD pipelines, registries, observability, drift monitoring, and automated rollback processes.
- Drive Responsible AI and governance, partnering with legal, risk, and compliance teams to meet regulatory and ethical standards.
- Lead cross‑functional teams, mentor engineers, promote agile ways of working, and communicate complex topics to technical and non‑technical stakeholders
Essential Requirements
- Bachelor’s or Master’s degree in computer science, IT, or other quantitative disciplines.
- 10+ years overall experience, including 5+ years in AI/ML or data‑intensive solution architecture at enterprise scale.
- Demonstrated success delivering production AI systems that meet enterprise NFRs (security, latency, cost, compliance).
- Strong engineering background in at least two programming languages (e.g., Python, Java, Scala).
- Deep expertise in cloud‑native architectures (Kubernetes, microservices, event streaming) and at least one major cloud platform.
- Practical proficiency with MLOps/LLMOps tools: model/prompt registries, evaluators, feature stores, pipelines.
- Strong understanding of NLP, semantic search, and text mining techniques.
- Ability to manage multiple priorities, work under tight deadlines, and operate within a global team environment.
Desired Requirements
- Experience in the pharmaceutical industry with understanding of industry‑specific data standards.
- Domain expertise in at least one area Pharma R&D,Manufacturing, Procurement & Supply Chain, Marketing & Sales
- Strong background in semantic technologies and knowledge representation (OWL, RDF, SPARQL, SWRL, JSON‑LD, Turtle).
Skills Desired
A/B Testing, AI Platforms, Data Drift, Data Strategies, Generative AI, Google Cloud Platform (GCP) for Machine Learning, Machine Learning (ML), Model Deployment
