Senior AI Engineer

About the role

We are hiring a **Senior AI Engineer** for our partner in **Frisco, TX or Bellevue, WA** for an **onsite role.** **Job Details:**

**Role: Senior AI Consultant**

**Location: Frisco TX or Bellevue WA \- Onsite** **Mandatory Areas:\-**

* AI,ML * NLP * LLM/SLM

RAG *

**About the Role**

We are looking for a Senior AI Consultant to serve as a strategic advisor and technical architect for our AI transformation program. 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, Gamma, 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.