AI Architect

Title: AI Architect

Duration: Contract to Hire

Location: REMOTE

Key Responsibilities
Design scalable enterprise AI architectures aligned to business and technical needs
Lead solutioning and prototyping of AI/GenAI systems (including LLM-based solutions)
Translate requirements into architecture diagrams and solution designs
Partner with data, platform, and application teams to integrate AI capabilities
Support development teams with guidance on implementation and engineering approaches
Drive AI platform development and enterprise integration across systems (SAP, Salesforce, etc.)
Ensure adherence to AI governance, risk, and security standards
Present architecture and solutions for review and enterprise alignment
Scope of Work / Deliverables
Support AI Big Bet initiatives focused on customer experience (e.g., agentic voice solutions)
Develop enterprise AI platform capabilities
Create architecture documentation and solution designs
Establish integration patterns between AI platforms and enterprise systems
Assist in evaluating external AI partners and proof-of-value solutions
Day-to-Day Activities
Participate in daily stand-ups and cross-functional meetings
Collaborate with customer architects, AI team, and enterprise stakeholders
Develop architecture diagrams and documentation
Conduct independent solution design and prototyping work
Engage with external partners and internal teams
Team & Collaboration
Highly collaborative, cross-functional environment working with:
Customer architects (2 3 stakeholders)
AI platform team (Cindy Hoffman team)
Enterprise AI leadership (Pravin Kumarappan)
Data, integration, and solution architects
Required Skills
Experience delivering production AI/ML solutions
Strong AI architecture and platform design expertise
Hands-on experience with GenAI and LLM-based systems
Deep understanding of ML lifecycle (training, inference, evaluation)
Ability to prototype, solution, and guide implementation
Experience integrating AI into enterprise systems
Strong understanding of AI governance, risk, and guardrails
Technical Environment
Cloud platforms: AWS, Google Cloud Platform (Azure exposure beneficial)
Data platforms: Databricks (preferred)
Enterprise systems: SAP, Salesforce, Avaya (nice to have)
AI frameworks: LLMs, GenAI systems
Required Skills
Experience delivering production AI/ML solutions
Strong AI architecture and platform design expertise
Hands-on experience with GenAI and LLM-based systems
Deep understanding of ML lifecycle (training, inference, evaluation)
Ability to prototype, solution, and guide implementation
Experience integrating AI into enterprise systems
Strong understanding of AI governance, risk, and guardrails
Preferred Qualifications
Experience working in large enterprise environments
AI certifications (Databricks, AWS, Google Cloud Platform, etc.)
Utility industry experience (nice to have)
Experience scaling AI solutions in enterprise settings
Soft Skills
Strong communication and stakeholder management skills
Ability to translate complex AI concepts into business language
Self-starter with strong cross-functional collaboration ability
Comfortable presenting solutions to leadership
Red Flags
Experience limited to proof-of-concept AI work only
Lack of enterprise-scale system experience
Limited recent exposure to AI technologies
No integration experience between AI and data platforms

Thnks,

Suman Pachigulla