Large Language Model Architect

Project Role : Large Language Model Architect Project Role Description : Architect large language models (LLM) that can process and generate natural language. Design neural network parameters, trained on large quantities of unlabeled text data. Must have skills : Large Language Models (LLMs) Good to have skills : NA Minimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education

Summary: We are building out a world-class AI Delivery and Architecture team and are looking for exceptional engineers who want to shape how enterprise AI systems are designed, built, and operated at scale. This is a senior hands-on technical role that sits at the intersection of cloud engineering, LLM/GenAI application development, and AI infrastructure platform design.

You will drive architecture decisions, lead delivery across complex multi-cloud AI programs, and act as a force multiplier for the engineers around you. You will be equally at home writing production Python, reviewing infrastructure-as-code, and presenting architecture trade-offs to senior stakeholders.

Roles & Responsibilities:

• Architect and deliver end-to-end GenAI solutions

Define the AI roadmap for our key customers Design RAG pipelines, agentic workflows, and multi-model orchestration patterns that go beyond prototypes into production-grade systems. Lead technical design and governance Own Architecture Decision Records , run design reviews, establish engineering standards, and ensure solutions are reusable and maintainable across teams. Drive AI infrastructure platform engineering Build and scale model-serving infrastructure (Bedrock, Vertex AI, Azure OpenAI), and AI gateway/routing layers. Strong system integration Skills Own multi-cloud delivery Architect and deliver across AWS, Azure, and GCP using IaC (Terraform/Pulumi), Kubernetes (EKS/AKS/GKE), and GitOps workflows. Embed observability and LLMOps from day one Instrument AI systems with OpenTelemetry, LLM-specific tooling , token/cost dashboards, and drift detection. Champion responsible AI and security Implement guardrails, output filtering, prompt injection defenses, data residency controls, and OWASP LLM Top 10 mitigations. Mentor and grow the team Guide engineers through complex technical challenges, lead code and architecture reviews, and help set the bar for engineering quality. Translate strategy into delivery Work closely with product, data science, and business stakeholders to turn AI objectives into executable technical roadmaps.