Summary:

The AI Technical Lead is responsible for leading the design, architecture, development, and deployment of enterprise-scale Generative AI and Agentic AI solutions that drive business transformation and innovation. This role combines deep technical expertise in Large Language Models (LLMs), Agentic AI systems, cloud-native AI platforms, and AI engineering best practices with strong customer engagement and technical leadership capabilities. The position serves as the primary technical authority for AI solution delivery, guiding architecture decisions, establishing engineering standards, and leading cross-functional teams in building scalable, secure, and production-ready AI applications. The AI Technical Lead partners closely with customers, business stakeholders, product teams, and engineering organizations to translate business objectives into practical AI solutions that deliver measurable value.

Essential Job Duties and Responsibilities:

AI Strategy & Solution Architecture

• Lead the end-to-end design and delivery of Generative AI and Agentic AI solutions.

• Define reference architectures, implementation patterns, and engineering standards for enterprise AI applications.

• Evaluate emerging AI technologies and frameworks and recommend adoption strategies.

• Ensure AI solutions align with enterprise architecture, security, governance, and scalability requirements.

Agentic AI & Intelligent Systems

• Architect and implement Agentic AI systems, including:

  • Multi-agent workflows

  • Agent orchestration patterns

  • Memory architectures

  • Tool integration frameworks

  • Retrieval-Augmented Generation (RAG) solutions

• Design AI agents capable of interacting with enterprise systems, APIs, business processes, and knowledge repositories.

• Establish reusable frameworks for autonomous and semi-autonomous agent execution.

AI Application Development

• Lead development of AI-powered applications utilizing LLMs, foundation models, and enterprise knowledge sources.

• Design and implement solutions leveraging:

  • Model Context Protocol (MCP)

  • External APIs

  • Enterprise data platforms

  • Knowledge management systems

  • Business applications

• Guide engineering teams in implementing production-grade AI architectures and services.

AI Evaluation, Observability & Governance

• Define and implement AI evaluation frameworks covering:

  • Response quality

  • Groundedness

  • Hallucination detection

  • Agent performance

  • Safety and reliability

• Establish AI monitoring, observability, and operational performance standards.

• Support responsible AI, governance, compliance, and model risk management practices.

• Develop metrics and measurement frameworks to assess business and technical outcomes.

Cloud & Platform Engineering

• Design, deploy, and optimize AI solutions across Azure, AWS, and Google Cloud environments.

• Collaborate with platform teams to establish scalable and secure AI infrastructure.

• Drive adoption of cloud-native architectures, LLMOps, MLOps, and automation practices.

• Ensure solutions meet enterprise requirements for availability, security, performance, and cost efficiency.

AI-Assisted Engineering & Productivity

• Champion adoption of AI-assisted development platforms including:

  • Claude Code

  • GitHub Copilot

  • Cursor

  • Equivalent AI engineering tools

• Establish best practices for AI-enabled software development and engineering productivity.

• Identify opportunities to accelerate delivery through AI-assisted workflows and automation.

Customer Engagement & Technical Consulting

• Work directly with customers to understand business challenges and identify AI-driven opportunities.

• Translate business requirements into scalable technical architectures and implementation plans.

• Lead technical workshops, architecture reviews, proofs of concept, and solution demonstrations.

• Serve as a trusted advisor on AI strategy, implementation, and operationalization

Other Job Duties and Responsibilities:

• Performs other related duties as assigned.

• Comply with all company policies and procedures.

• Maintain regular and punctual attendance.

Supervisory Responsibilities:

• This position is an individual contributor with no direct reports but may provide guidance, leadership, or training to others.

Qualifications:

To perform this job successfully, an individual must be able to perform eachessential functionsatisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required.

Required Technical Skills

• Advanced Python development

• Large Language Models (LLMs)

• Generative AI application development

• Retrieval-Augmented Generation (RAG)

• Agentic AI architectures

• Multi-agent systems

• Model Context Protocol (MCP)

• Tool-calling and agent orchestration frameworks

• AI evaluation and observability platforms

• Cloud platforms (Azure, AWS, Google Cloud)

• API design and integration

• Enterprise application architecture

Preferred Qualifications

• Experience with LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar agent orchestration frameworks.

• Experience implementing AI governance, responsible AI, and model risk management frameworks.

• Familiarity with MLOps, LLMOps, CI/CD pipelines, and cloud-native deployment models.

• Experience leading enterprise-scale AI transformation initiatives.

• Banking & Financial Services industry experience, including exposure to customer servicing, operations, risk, underwriting, fraud, claims, or compliance use cases.

Education and/or Experience:

• Bachelor's degree in Computer Science, Engineering, Information Technology, Data Science, or a related field.

• 10+ years of experience in Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or related technical disciplines.

• Demonstrated experience leading complex AI solution delivery programs from concept through production deployment.

• Proven experience working directly with business stakeholders and customers in consulting or solution delivery environments.

Certificates, Licenses, Registrations:

• None Required

Work Complexity:

Problems and issues faced are numerous, typically undefined where information is difficult to obtain. Conducts extensive investigation to understand root cause of problems and how to make sense of them in the larger financial/mortgage (or job-specific) industry. Problems span a wide range of difficult and unique issues across functions and/or businesses.

Work Environment:

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job.Work is normally performed in a typical interior office work environment which does not subject the employee to any hazardous or unpleasant elements. The noise level in the work environment is usually moderate.

Physical Demands:

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. While performing the duties of this job, the employee is frequently required to sit and talk or hear. The employee is occasionally required to stand; walk; use hands to finger, handle, or feel; and reach with hands and arms. The employee must occasionally lift and/or move up to 25 pounds.

Job Responsibilities:

The statements reflect the general duties and responsibilities considered necessary to perform the essential functions of the job and should not be considered as an all-inclusive list of all the work requirements of the position. The company may change the specific job duties with or without prior notice based on the needs of the organization.

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