Senior AI Engineer

Appex Innovation • Frisco, TX

6d • Onsite

About The Position

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.

Requirements

• 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.

Nice To Haves

• 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.

Responsibilities

• 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 This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed