Senior Architecture

Cigna Healthcare•Bloomfield, CT

About The Position

The Senior Architecture (Architecture Senior Advisor) is a senior technical leader. This role helps design, build, and support AI and machine learning (AI/ML) solutions. The person in this role works closely with business and IT teams to create reliable, secure, and compliant technology solutions. They also guide development teams and help set technical standards. Key Responsibilities Lead the full life cycle of AI and machine learning models, from data preparation to deployment and support. Build AI solutions that use large language models (LLMs), tools, and memory components. Research and apply new AI methods, including natural language processing, OCR, recommendations, and predictive models. Set up and support MLOps processes, including model tracking, monitoring, and retraining. Act as a technical lead and provide guidance to delivery and operations teams. Support cloud technologies and drive automation solutions. Define technical standards and help design, build, and support shared AI platforms. Create and maintain product and software roadmaps. Provide technical leadership for Provider Technology solutions. Design end‑to‑end solutions that follow target architecture and reuse existing systems. Work with business partners to support new initiatives and meet compliance needs. Collaborate with multiple IT teams to align technical solutions with business goals. Provide hands-on technical support and share expertise with development teams. Define non‑functional requirements such as security, performance, and reliability. Work with enterprise architecture and cloud teams to plan and deliver enabling solutions. Participate in planning sessions, system demos, and reviews as needed. Maintain architecture documentation and decisions in Confluence. Create and maintain best practices, processes, and deliverables for the architecture team.

Requirements

High School Diploma or equivalent; Bachelor's degree preferred.
9+ years of experience in AI/ML software engineering.
Experience building autonomous or multi‑agent AI systems.
Strong knowledge of generative AI, RAG solutions, vector databases, and embeddings.
Proficiency in Python and working with large language models (LLMs).
Solid understanding of algorithms, statistics, and data structures.
Experience deploying AI solutions to production environments.
Experience working with containers such as Docker, Kubernetes, EKS, or OpenShift.
Experience with CI/CD and infrastructure tools such as GitHub, Jenkins, and Terraform.
Knowledge of security concepts, including encryption and identity management.
Experience with data replication technologies and moving data from on‑premise systems to the cloud.
Knowledge of AWS services and cloud solution patterns.
Experience across the full software development life cycle, including design, testing, implementation, and support.
Strong communication skills and experience working with technical and business teams.
Strong focus on delivering positive customer and business outcomes.
Ability to work well with others and build collaborative relationships.
Strong organization and time management skills.
Ability to learn quickly and manage multiple priorities.
If you will be working at home occasionally or permanently, the internet connection must be obtained through a cable broadband or fiber optic internet service provider with speeds of at least 10Mbps download/5Mbps upload.

Responsibilities

Lead the full life cycle of AI and machine learning models, from data preparation to deployment and support.
Build AI solutions that use large language models (LLMs), tools, and memory components.
Research and apply new AI methods, including natural language processing, OCR, recommendations, and predictive models.
Set up and support MLOps processes, including model tracking, monitoring, and retraining.
Act as a technical lead and provide guidance to delivery and operations teams.
Support cloud technologies and drive automation solutions.
Define technical standards and help design, build, and support shared AI platforms.
Create and maintain product and software roadmaps.
Provide technical leadership for Provider Technology solutions.
Design end‑to‑end solutions that follow target architecture and reuse existing systems.
Work with business partners to support new initiatives and meet compliance needs.
Collaborate with multiple IT teams to align technical solutions with business goals.
Provide hands-on technical support and share expertise with development teams.
Define non‑functional requirements such as security, performance, and reliability.
Work with enterprise architecture and cloud teams to plan and deliver enabling solutions.
Participate in planning sessions, system demos, and reviews as needed.
Maintain architecture documentation and decisions in Confluence.
Create and maintain best practices, processes, and deliverables for the architecture team.