AI LLM Architect

YOU ARE

As an experienced and Senior AI/LLM Architect you will play a pivotal role in designing and delivering end-to-end AI platform architectures that power the modern reinvented enterprise. Operating at the intersection of business and engineering you will own the technical design of advanced AI systems spanning classical machine learning generative AI and agentic systems ensuring they are purposefully architected to meet client businessobjectivesand enterprise-grade standards. Within this scope you will take deep ownership of one or more critical architecture domains such as agentic application design AI security and trust AI operations and observability data and knowledge engineering or model platforms and inference serving as the lead authority in your domain across client engagements.

THE WORK

• Translate business strategy into a technical vision by defining the non-functional requirements (NFRs) necessary to meet operational goals for performance reliability and cost.

• Lead stakeholder workshops toalign ontechnical feasibility define project scope and manage expectations with clients and leadership.

• Drive the technology selection process evaluating build-vs-buy decisions for AI platforms (e.g.ArizeLangSmith) and foundational models.

• Architect model- and tool-agnostic multi-agent systems governed by an MCP Control Plane.

• Design and implement the Agent Registry as the mandatory system of record and the AI Gateway for runtime policy enforcement.

• Design and implement a certification gate to ensure no uncertified agents enter productionvalidatingidentity policies andevaluationmetrics.

• Design implement and abstract core agent services including a first-class abstracted memory service with semantic episodic and procedural endpoints.

• Architect the end-to-end data pipeline for AI systems including data ingestion preprocessing and synchronization for fine-tuning and RAG.

• Design and implement the context layerspanning knowledge graphs vector search and semantic retrievalto create reliable grounded RAG pipelines.

• Architect foundation model adaptation strategies including dynamic cost-and-performance-aware model routing and selection.

• Design implement and prototype high-throughput low-latency inferencing solutions using techniques like response caching and request batching.

• Define security governance and observability ascentrally-enforced by-design controls for all AI systems.

• Architecta robust defense-in-depth security framework including per-agent identity with IAM/IAP binding and layered guardrails.

• Design and implement FinOps controls enforced at the AI Gateway including token budgets cost-center labeling and threshold alerts.

• Establish the framework for comprehensive system evaluation adopting productized tools and instrumenting observability withOTel

• Define andmaintainthe enterprise-wide AI reference architecture reusable design patterns and a library of approved software components.

• Independently design implement build and deliver proof-of-concept prototypes and foundational software components tovalidatearchitectural decisions.

• Produce and own authoritative architecture artifacts including blueprints sequence diagrams design specifications and Architectural Decision Records (ADRs).

• Mentor and guide cross-functional engineering teams (data ML application) on architectural best practices and design patterns.

• Continuously research and integrate emerging AI patterns frameworks and technologies tomaintaina forward-looking architecture.

EDUCATION

• Bachelors Degree or equivalent

BASIC (REQUIRED) QUALIFICATION

• Minimum of 2 years of experience in designing & deploying enterprise grade advanced ai solutions using agenticgenerativeand classical AI/ML using at least one cloud vendor.

• Minimum of 2 years of experience in the AgenticLLMand Generative AI space.

• Minimum of 4 years of coding experience using python

• Minimum of 2 years of experience architecting and operationalizing LLM driven application architecture patterns.

• Minimum of 4 years in coding engineering machine learning deep learning and NLP solutions and applications.

• Minimum of 4 years of experience as a machine learning architect in the industry designing bigdatamachine learning. large scale analytical engineering solutions.