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Job Title: Senior AI Consultant/ Advisor 

Location:  Bellevue WA- Onsite

On Contract

About the Role
We are looking for a Senior AI Consultant to serve as a strategic advisor and technical architect for our AI transformation programme. The engagement spans multiple high-impact use cases in Telco Ops, along with a broader model selection and cost-governance framework. You will play a thought leadership role, guiding senior stakeholders on AI strategy, architecture decisions, and execution models—bringing both hands-on expertise in GenAI and traditional AI/ML as well as experience advising VP/Sr. Director-level leadership in large enterprises. You will help us make the right decisions on model architecture, tooling, implementation sequencing, and team structure, with a specific focus on when to use SLMs vs LLMs and how to build cost-efficient, production-grade AI pipelines.
What You Will Do
· Advise on architecture decisions for AI use cases involving SLM, LLM, hybrid AI pipelines across multiple AI tasks like classification, information extraction, document processing, correlation, and reasoning workloads.
· Review and challenge model selection choices, benchmarking methodology, and fine-tuning strategies for different AI tasks tasks
· Guide the cost-versus-accuracy trade-off analysis across model types (frontier LLM, LLM with fine-tuning, SLM instruct, SLM fine-tuned) and workload profiles.
· Provide practical input on implementation approach, team structure, sprint sequencing, and make-vs-buy decisions.
· Review data strategy, labelling effort sizing, evaluation harness design, and MLOps requirements for each workload.
· Advise on how to structure the business case and design the appropriate AI architecture including executive-level cost, latency, and accuracy comparisons.
· Flag risks including vendor lock-in, model drift, data governance gaps, and compliance requirements for use cases in regulated industries/domains
· Act as a trusted advisor to senior leadership (VP/Sr. Director level), shaping AI strategy and influencing key decision-making forums.
What You Must Have
· 8+ years of experience in applied ML and AI, with at least 3–4 years in enterprise NLP or LLM/SLM system design and deployment.
· Demonstrable hands-on experience with SLMs including fine-tuning and deployment using models such as Phi, Gemma, Llama, Mistral, or Qwen families.
· Strong understanding of frontier LLM APIs (OpenAI, Azure OpenAI, Anthropic) and when they add genuine value over smaller models.
· Experience designing multi-task NLP pipelines covering classification, named entity recognition, document extraction, RAG, and reasoning.
· Ability to translate model architecture decisions into cost models and business cases (implementation cost, run cost, savings, ROI).
· Experience with at least one of the following verticals: telecom, healthcare, or industrial/manufacturing B2B operations.
What is highly desirable
· Experience with automation or workflow orchestration in high-volume operational environments.
· Knowledge of LLMOps practices for SLM deployment including quantization, batching, model versioning, and latency benchmarking.
What success looks like in this role
· Clear, defensible architecture recommendation for each use case with rationale for model tier selection, estimated implementation cost, and projected run cost savings.
· A practical evaluation framework and scoring rubric that the internal team can use to benchmark models independently.
· A sequenced implementation roadmap that the delivery team can execute in 4-6 month phases.
· Executive-ready cost comparison across LLM-only, SLM-only, and hybrid approaches for each use case.