AI Large Language Model (LLM) Technology Architect (All Genders)

As an hands-on AI/LLM Architect, you will design and build enterprise AI systems spanning classical ML, generative AI, and agentic architectures. You will translate requirements into concrete architecture decisions, build reusable components, and deliver ADRs and diagrams to guide engineering teams. You will ground AI outputs with enterprise data sources, ensure security and reliability, and work with cross-functional delivery teams. This is a hands-on role with impact across architecture, experimentation, and tooling, shaping scalable AI solutions for clients.

• Design, build, and deliver AI software components end-to-end
• Architect AI agent systems including orchestration, prompts, tools, and memory
• Prototype and validate orchestration patterns for task handoffs and state management
• Evaluate design options balancing capability, cost, performance, and reliability
• Develop evaluation strategies for agent/system quality (accuracy, relevance, faithfulness)
• Integrate foundation models with fine-tuning, RAG, and custom integration
• Develop AI context layer with knowledge bases, data ingestion, and grounding
• Implement embedding/vector storage and retrieval in end-to-end RAG pipelines
• Design memory and context management for grounded outputs
• Create reusable components and templated patterns across engagements
• Optimize cost, performance, latency, and throughput of models and pipelines
• Build governance, security, and Responsible AI controls (PII, access, guardrails)
• Establish observability: logging, tracing, monitoring, alerting, cost tracking
• Produce architecture artifacts (ADRs, blueprints, diagrams, integration specs)
• Collaborate with data engineers, ML engineers, and application developers
• Continuously learn and apply new AI design patterns and technologies
• Translate requirements into concrete architecture decisions that meet stakeholders’ needs

• Proven experience designing and deploying enterprise-grade AI solutions using agentic, generative, and classical AI/ML on at least one cloud vendor
• Hands-on experience with agentic, LLM, and Generative AI spaces
• Proficiency in Python
• Strong foundation in architecting and operationalizing LLM-driven application architectures
• Professional experience in coding, ML, DL, and NLP applications
• Several years of hands-on ML architect experience designing large-scale data and analytics systems

• Cross-functional collaboration
• Strong communication of complex architectures
• Analytical mindset with problem-solving
• Python
• LLM architectures
• Agentic AI