Ai Architect

Job Title: Ai Architect

Job Description

We are seeking a Senior data science AI Architect with deep experience in Data Science and Generative AI solutions — to design, build, and deploy AI-powered applications that automate business processes and improve decision-making. This is a hands-on technical leadership role focused on developing production-ready AI solutions using large language models (LLMs), agentic AI frameworks, retrieval-augmented generation (RAG), and modern cloud data platforms — including Microsoft Azure AI Foundry.
This individual will work closely with business stakeholders and product teams to translate business needs into scalable technical solutions and architecture designs, driving innovation across AI-enabled products and platforms. The role is highly hands-on: partnering directly with the business, evaluating emerging AI technologies and vendor offerings, and building rapid proofs of concept to validate ideas and reduce delivery risk.
The ideal candidate combines deep AI application development and data architecture skills with proven leadership ability: mentoring engineers, setting technical direction, and driving enterprise AI adoption across the full product lifecycle. Experience in utility, energy, or other regulated infrastructure environments is a strong plus given our client base. 

Key Responsibilities 

Business Partnership & Solution Leadership
•    Partner directly with business teams to shape and design new AI-enabled capabilities.
•    Lead solution architecture and technical design for Data Science and GenAI initiatives.
•    Evaluate emerging AI technologies, vendor offerings, and new platform capabilities.
•    Build rapid proofs of concept (POCs) to validate ideas and reduce implementation risk.
•    Provide technical leadership and architectural guidance across the full product lifecycle.
•    Work across engineering, product, data, and business teams to drive delivery.
AI Solution Design & Development
•    Design and build agentic AI applications that automate business workflows and improve operational efficiency.
•    Develop AI solutions using LLMs, multi-agent architectures, and retrieval-augmented generation (RAG).
•    Create and optimize prompt engineering strategies, reasoning workflows, and AI integrations.
•    Build and maintain APIs, backend services, and AI application components.
•    Evaluate new AI technologies and recommend solutions that drive business value.
Data Architecture & Integration
•    Design data retrieval and grounding strategies that connect AI applications to enterprise data sources.
•    Develop vector search, embedding, and knowledge retrieval solutions.
•    Design and deploy AI solutions using Microsoft Azure AI Foundry (model catalog, Agent Service, prompt flow / evaluation, and grounding to enterprise data).
•    Partner with data engineering teams to ensure AI systems leverage reliable and secure data pipelines.
•    Establish standards for AI performance, accuracy, and reliability.
•    Experience with data science models, data bricks, data pipelines, governance
Technical Leadership
•    Serve as a technical lead for AI architecture and development initiatives.
•    Provide guidance and mentorship to developers, engineers, and technical teams.
•    Review solution designs and help establish AI development standards and best practices.
•    Translate complex AI concepts into practical solutions for technical and business stakeholders.
•    Lead and grow a team of AI engineers: set goals, coach performance, and build succession depth on the AI practice.
•    Influence and align cross-functional stakeholders (engineering, data, product, and business leaders) around AI architecture decisions and roadmap trade-offs.

Platform & Automation
•    Support and enhance enterprise AI platforms and integrations.
•    Implement automation, CI/CD, and Infrastructure-as-Code (IaC) practices for AI deployments.
•    Maintain technical documentation, architecture diagrams, and implementation standards. Required Qualifications
•    8+ years of experience in software engineering, data engineering, AI/ML, data science, or related technical fields.
•    2+ years of hands-on experience building and deploying AI or LLM-based applications.
•    Strong experience with OpenAI, Claude, or similar LLM platforms and APIs.
•    Experience building agentic AI solutions and multi-agent workflows.
•    Strong understanding of prompt engineering, tool usage, and AI application design.
•    Experience designing and implementing RAG solutions and vector search technologies.
•    Proficiency in Python and API development.
•    Experience working with cloud platforms and modern data architectures.
•    Strong communication, leadership, and problem-solving skills.
•    Demonstrated leadership experience: mentoring engineers, leading technical initiatives, or managing/influencing cross-functional teams (formal management experience not required, but strong informal/technical leadership is).
•    Proven experience partnering directly with business and product stakeholders to translate ambiguous business needs into technical architecture and solution designs.
•    Experience building rapid proofs of concept (POCs) to validate ideas and reduce implementation risk. Preferred Qualifications
•    Experience with MCP (Model Context Protocol) and agent orchestration frameworks such as LangGraph, LangChain, CrewAI, or AutoGen.
•    Hands-on experience with Microsoft Azure AI Foundry (formerly Azure AI Studio), including model catalog, Agent Service, Foundry IQ / grounding, and evaluation tooling.
•    Experience with Databricks, Snowflake, Azure AI services, or similar platforms.
•    Background in workflow automation, analytics, pricing, sales, or customer-facing business applications.
•    Experience working in regulated enterprise environments.
•    Prior experience with utility, energy, or critical-infrastructure clients (electric, gas, water) — including familiarity with regulatory, reliability, and safety constraints common to that sector.
•    Experience evaluating and piloting emerging AI vendor platforms and tools, using a structured framework for technology selection.
•    Advanced degree in Computer Science, Data Science, AI, or a related field. 

Technical Environment Experience with the following technologies is highly desirable:
•    OpenAI, Azure OpenAI, Claude
•    Azure AI Foundry (Microsoft Foundry) — Agent Service, model catalog, Foundry IQ
•    MCP (Model Context Protocol)
•    Python, FastAPI
•    LangChain, LangGraph, CrewAI
•    Databricks, Delta Lake
•    Vector databases and semantic search platforms
•    Azure, AWS, or other cloud environments
•    CI/CD pipelines and Infrastructure as Code (Terraform, GitHub Actions, Azure DevOps) 

Success in This Role Success will be measured by:
•    Delivery of scalable, production-ready AI applications.
•    Ability to move AI use cases from concept to deployment, including rapid POCs that validate ideas before full build-out.
•    Technical leadership and mentorship of engineering teams.
•    Quality, reliability, and business impact of AI solutions.
•    Effective partnership with business and product stakeholders to shape and deliver new AI-enabled capabilities.
•    Effective collaboration with engineering, data, and business teams to drive delivery.