Senior AI Engineer

Job Description

Job Description

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.