AI Engineer Lead Senior

Anticipated End Date:

2025-12-29

Position Title:

AI Engineer Lead Senior

Job Description:

AI Engineer Lead Senior

Location: This role requires associates to be in-office 1 day per week, fostering collaboration and connectivity, while providing flexibility to support productivity and work-life balance. This approach combines structured office engagement with the autonomy of virtual work, promoting a dynamic and adaptable workplace.  Ideal candidates will be able to report to one of our Pulse Point locations in Atlanta, GA, Hanover, MD, Mason, OH, Indianapolis, IN, Ashburn, VA, Norfolk, VA or New York, NY. Alternate locations may be considered if candidates reside within a commuting distance from an office.

Please note that per our policy on hybrid/virtual work, candidates not within a reasonable commuting distance from the posting location(s) will not be considered for employment, unless an accommodation is granted as required by law.

The AI Engineer Lead Senior is responsible for leading the end-to-end application system development and maintenance on large complex enterprise-wide technology platforms. 

How you will make an impact:

• Leads hands-on development of complex AI prototypes and frameworks, validating new architectures, tooling, and enterprise AI opportunities. 

• Anticipates emerging trends in AI, LLMs, and automation, and ensures the organization remains ahead of technological shifts. 

• Designs and executes enterprise-scale POCs/POTs, assessing scalability, reliability, cost, and long-term feasibility. 

• Partners with other AI Engineers to shape multi-year AI engineering roadmap and define standards, patterns, and accelerators. 

• Evaluates maturity and readiness of AI technologies (LLM platforms, RAG pipelines, orchestration frameworks) for enterprise adoption. 

• Performs advanced design and code reviews, ensuring alignment with architectural direction and engineering excellence. 

• Leads prioritization discussions and influences trade-offs for AI platform evolution, modernization, and experimentation strategy. 

• Guides engineering teams through complex AI technical problems and hands-on solution exploration. 

• Participates in enterprise solution review and decision forums, representing engineering feasibility and innovation opportunities. 

• Owns monitoring and validation approaches for AI prototypes and experimental workloads. 

• Maintains active relationships with customers to determine business requirements, leads requirements gathering meetings and reviews designs with the business.

• Anticipates broad technical change and ensures that company technology stays ahead of the curve.

• Understands the entire architecture for a major part of our business and is able to articulate the scaling and reliability limits.

• Develops and defines application scope and objectives and supervises the preparation of technical and/or functional specifications from with programs will be written.

• Performs technical design reviews and code reviews.

• Delivers application technology solutions and data information planning effort.

• Participates in developing the multi-year technology strategy for critical areas of the business that may encompass multiple systems.

• Partners with technical and non-technical stakeholder to identify the long-term technical trajectory of the technology infrastructure.

• Creates architecture and anticipates future technology needs. 

Minimum Requirements:

Requires an BA/BS degree in Information Technology, Computer Science, or related field of study a minimum of 9 years’ experience;  multi-dimensional platform experience, expert level experience with business and technical applications; or any combination of education and experience, which would provide an equivalent background.

Preferred Skills, Capabilities and Experiences:

• Expert-level AI/ML and LLM experience highly preferred. 

• Deep experience prototyping enterprise-grade AI capabilities—LLM agents, pipelines, vector retrieval, distributed inference highly preferred.  

• Strong hands-on experience with emerging and leading frameworks, not only limited to LangChain, LlamaIndex, HuggingFace Transformers, vector DBs (FAISS, Pinecone, Redis, etc.) highly preferred.  

• Experience implementing scalable RAG architectures, evaluation frameworks, and model experimentation workflows highly preferred.  

• Advanced ML Ops experience—governance,