Job ID: H#12999 - Enterprise AI Architect
Must be Hybrid in Hartford, CT or Charlotte, NC
PLEASE NOTE: This is a 6 month contract-to-hire and needs to meet Client full-time conversion policies. Those dependent on a work permit sponsor now or anytime in the future (ie H1B, OPT, CPT, etc) do not meet Client requirements for this opening.
The Hartford is seeking a highly skilled, hands-on AI Architect to support the Enterprise Technology Architecture (ETA) organization. This role will be responsible for leading the design, governance, and implementation of AI-centric technology architectures across a hybrid infrastructure landscape, including AWS, Google Cloud Platform (Google Cloud Platform), and on premises data centers. The AI Architect will play a critical role in enabling the responsible and secure adoption of Generative AI (GenAI) technologies, establishing architectural standards, and driving the implementation of multiple internal-facing GenAI use cases. This role requires a strong blend of strategic architectural background and hands-on technical execution.
Key Responsibilities:
Architecture & Strategy
- Design and develop Agentic AI solutions leveraging Google ADK, LangGraph/Langchain and Agent Engine on Google Cloud Platform (Google Cloud Platform).
- Deliver innovative AI capabilities that enhance business processes and customer experiences through GenAI and Agentic AI frameworks.
- Ensure AI solutions align with enterprise technology strategy and meet scalability, security, and compliance requirements.
- Drive adoption of GenAI and Agentic AI frameworks across business units.
- Conduct proof-of-concepts (POCs) for emerging AI technologies and frameworks.
- Collaborate with enterprise architects to ensure AI solutions align with technology strategy and reference architectures
- Stay current with AI trends, frameworks, and best practices to propose innovative solutions.
Cloud Security (AWS & Google Cloud Platform)
- Architect and implement secure cloud solutions leveraging native services and third-party tools.
- Define and enforce cloud security posture management (CSPM), identity and access management (IAM), and encryption strategies.
- Collaborate with DevOps and cloud engineering teams to embed security into CI/CD pipelines and infrastructure-as-code.
Datacenter & Hybrid Security
- Ensure secure integration between cloud platforms and on-prem datacenters, including network segmentation, VPNs, and secure data flows.
- Oversee security controls for legacy systems and their modernization paths.
GenAI Security Enablement
- Define security and governance frameworks for GenAI platforms and use cases.
- Ensure responsible AI practices including data privacy, model integrity, and ethical AI usage.
- Collaborate with AI/ML teams to secure model training, inference, and deployment pipelines.
Governance & Collaboration
- Serve as a key member of the Enterprise Technology & Solution Governance
- Partner with business, IT, and risk stakeholders to align security architecture with enterprise goals.
- Provide technical guidance and mentorship to junior engineers and architects on AI development practices.
Required Qualifications:
Qualifications:
- Experience: 10-12 years in Software Engineering, with at least 2+ years in GenAI and Agentic AI development
- Project Delivery: Must have delivered at least one GenAI or Agentic AI project end-to-end.
- Strong proficiency in Google ADK, LangGraph/Langchain, Agent Engine, and Vertex AI.
- Hands-on experience with Google Cloud Platform services: Cloud Run, ECS, Vertex AI Search Engine, IAM, and networking.
- Solid understanding of GenAI patterns, LLM fine-tuning, and prompt engineering.
- Programming Skills: Python, Java, or similar languages for AI development.
- Cloud Certifications: Google Cloud Platform Professional Machine Learning Engineer or Google Cloud Platform Professional Cloud Architect preferred.
- Education: Bachelor s or Master s degree in Computer Science, AI/ML, or related field.
- Soft Skills: Strong problem-solving, communication, and collaboration skills.
Key Competencies:
- Strategic and analytical thinking
- Successfully integrated AI agents into business or technical workflows for automation and enhanced decision-making
- Improved operational efficiency and customer experience through AI-driven innovation.
- Established reusable AI patterns and best practices for enterprise adoption.
- Strong communication and stakeholder engagement
- Proactive and solution-oriented mindset
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