Job Description
Role: Senior AI Delivery Lead / LLM Solutions Architect
Experience: 15–25 years
Location: Remote
Employment Type: Full-time
Overview
We are seeking a highly seasoned Senior AI Delivery Lead with deep expertise in Large Language Model (LLM) solution design and enterprise AI delivery governance. This role requires a dual focus: serving as the primary Delivery Lead for multiple concurrent AI programs (2× large engagements) while also acting as the senior architect responsible for prompting frameworks, retrieval strategies, and model selection to ensure scalable, high-quality solution outcomes.
The ideal candidate brings a unique combination of AI/LLM technical depth, multi-team governance experience, and strong delivery leadership capabilities across complex, cross-functional environments.
Key Responsibilities
Delivery Leadership and Governance
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Drive all delivery ceremonies including sprint planning, backlog refinement, stand-ups, retrospectives, and release readiness.
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Own risk, dependency, and issue tracking across multiple teams and technology streams.
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Maintain delivery health dashboards and proactively implement corrective actions.
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Coordinate inter-team and cross-vendor activities to ensure alignment of workstreams, milestones, and quality outcomes.
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Manage communications with customer stakeholders, executives, and internal leadership across two simultaneous AI program deliveries.
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Ensure compliance with delivery governance frameworks, SLAs, and change-control processes.
AI/LLM Technical Architecture
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Define and standardize prompt patterns, prompting frameworks, safety layers, and guardrails.
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Design retrieval architectures including chunking strategies, vectorization schemas, embedding model selection, retrieval pipelines, and relevance optimization.
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Evaluate and recommend LLM model choices (OSS, proprietary, fine-tuned models) based on use case, performance, cost, security, and latency constraints.
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Guide teams on RAG system architecture, observability, evaluation pipelines, and hallucination-reduction strategies.
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Drive architectural reviews and provide governance for model lifecycle management, experimentation, A/B testing, and performance optimization.
Program & Technical Oversight
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Lead solution design sessions, technical deep dives, and architectural decision-making across AI/LLM components.
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Provide mentorship and technical leadership to cross-functional teams (data engineers, ML engineers, prompt engineers, QA, DevOps, product owners).
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Serve as a thought partner to clients on AI roadmaps, scaling strategies, and enterprise-grade deployment patterns.
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Ensure end-to-end solution reliability, including retrieval pipelines, orchestration, monitoring, and fallback strategies.
Experience and Qualifications
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15–25 years of experience in AI/ML, with at least 5–8 years in LLM, transformer-based architectures, and enterprise AI implementations.
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Proven track record leading large AI programs as a Delivery Lead, Program Manager, or Engagement Lead while doubling as a senior AI architect.
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Hands-on experience with:
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Prompt engineering and prompt architecture patterns
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RAG design, embedding strategies, retrieval optimization
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Model selection (LLMs, OSS models, fine-tuned models)
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AI evaluation frameworks, metrics, and observability pipelines
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Strong understanding of enterprise delivery management (Agile/Scrum, scaled agile, governance cadences).
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Ability to manage and govern 2× parallel projects of significant scale.
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Excellent communication, stakeholder management, and cross-team coordination skills.
Preferred Skills
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Experience with vector databases, feature stores, or knowledge graphs.
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Familiarity with MLOps tooling, LLMOps, evaluation pipelines, and productionizing AI workloads.
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Background in cloud platforms (Azure, AWS, GCP) and associated AI services.
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Exposure to regulatory compliance, ethics, and AI safety principles.
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Demonstrated ability to mentor teams and drive best practices across engineering and delivery functions.
What This Role Enables
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High-quality, scalable AI/LLM architectures across enterprise environments.
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Predictable delivery with reduced risk, improved alignment, and high stakeholder satisfaction.
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Ability to run dual projects efficiently while maintaining deep technical influence.
