AI Architect

AI Architect

Job Location:

Manchester, CT or Bloomfield, CT or Austin, TX or Raleigh, NC or Chattanooga, TN or New Jersey (Onsite)

Job Duration:
Fulltime

Job Description:

AI / GenAI:

• Strong experience with Generative AI and Agentic AI architectures
• Hands on knowledge of LLMs, embeddings, RAG pipelines, prompt engineering, and agent frameworks
• Proficiency in Python for AI/ML development

ML & Data Engineering:

• Experience with ML/DL frameworks such as Tensor Flow, PyTorch, scikit learn
• Knowledge of data engineering, feature engineering, and analytics pipelines
• Familiarity with vector databases, graph databases, and search engines

Cloud & Platform:

• Experience designing AI solutions on cloud platforms (AWS, Azure, or GCP)
• Strong understanding of cloud native, microservices, and API driven architectures
• Exposure to observability, monitoring, and logging for AI systems

Security & Compliance:

• Knowledge of data privacy, security best practices, and enterprise compliance standards
• Experience designing secure and governed AI solutions

Responsibilities:

AI & Solution Architecture:

• Define and own end to end AI architecture for enterprise solutions, from data ingestion to AI driven decisioning and insights.
• Design AI native platforms where GenAI and ML capabilities are embedded as core services, not bolt ons.
• Establish modular, reusable, and composable AI components aligned to enterprise architecture standards.
• Ensure scalability, performance, reliability, and security of AI systems in production.

GenAI & Agentic AI:

• Large Language Models (LLMs)
• Retrieval Augmented Generation (RAG)
• Multi agent and agent orchestration patterns
• Define agent workflows, memory/context handling, tool integration, and decision confidence mechanisms.
• Guide responsible selection and usage of cloud based and open source LLMs.

Data, ML & MLOps:

• Design AI solutions leveraging modern data platforms, feature stores, vector databases, and knowledge graphs.
• Define MLOps / LLMOps pipelines for training, evaluation, deployment, monitoring, and lifecycle management.
• Implement mechanisms for model versioning, drift detection, cost optimization, and continuous improvement.

Governance, Security & Responsible AI:

• Ensure AI solutions adhere to enterprise security, privacy, and compliance requirements.
• Embed Responsible AI principles, including explainability, auditability, bias mitigation, and human in the loop controls.
• Define governance frameworks for model usage, access control, and operational oversight.

Technical Leadership &

Collaboration:

• Act as technical thought leader for AI initiatives across delivery teams.
• Collaborate with product owners, UX designers, data engineers, cloud engineers, and Dev Ops teams.
• Provide architecture guidance, reviews, and mentorship to senior engineers.
• Communicate complex AI concepts clearly to technical and non technical stakeholders.

Diverse Lynx LLC is an Equal Employment Opportunity employer. All qualified applicants will receive due consideration for employment without any discrimination. All applicants will be evaluated solely on the basis of their ability, competence and their proven capability to perform the functions outlined in the corresponding role. We promote and support a diverse workforce across all levels in the company.