AI Architect

AI Architect

Location:

Bloomfield, CT / Austin, TX

Duration:
Fulltime

Job Description:

Skills Desired:

• 12–16 years of overall IT experience

• 8+ years of experience in AI/ML solution or enterprise architecture

• Proven experience delivering production grade AI platforms at scale

• Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related field

Behavioral & Professional

Skills:

• Strong analytical and problem solving skills

• Excellent communication and stakeholder management abilities

• Ability to balance strategic vision with hands on architectural depth

• Experience working in agile and fast paced delivery environments

• Mentoring mindset with the ability to uplift technical teams

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:

• Architect Generative AI solutions, including:

o Large Language Models (LLMs)

o Retrieval Augmented Generation (RAG)

o 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.

Required Technical

Skills:

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