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Agentic AI Delivery Lead/REMOTE

K-Tek Resourcing LLCUnited States🇺🇸United StatesPosted Sep 23, 2026

Why This Role Stands Out

This remote Agentic AI Delivery Lead role offers a unique opportunity to shape the future of AI within enterprise organizations, driving innovative solutions from concept to production. You'll thrive here if you possess strong leadership skills, a passion for cutting-edge AI and data technologies, and a desire to build scalable, secure platforms in a flexible, remote environment. Join K-Tek Resourcing LLC and make a significant impact on industry-leading AI transformations.

Quick Overview

Seniority
Mid Senior
Work mode
Remote
Location
United States
Posted
Yesterday
SAFeDockerDynamoDBMicroservicesSQLAWSETLMLOpsMachine LearningScrumSnowflakeBudgetingCloudFormationComplianceDatabricksEMRGenerative AIGitGitHub ActionsJenkinsKafkaKubernetesPMPPythonRedshiftRegulatory ComplianceRisk ManagementStakeholder ManagementTerraformUnderwriting

Job Description

Role Overview
We are seeking an experienced Agentic AI Delivery Lead to drive enterprise-scale Agentic AI, Generative AI, Data Management, and Data Modernization programs. The role combines delivery leadership, solution architecture, cloud transformation, and stakeholder management to build secure, scalable, production-grade AI and data platforms on AWS. Property & Casualty (P&C) Insurance experience is preferred.
Key Responsibilities
Agentic AI Strategy and Delivery
  • Lead end-to-end delivery of Agentic AI and Generative AI initiatives from discovery and solutioning through deployment, adoption, and production support.
  • Design and oversee autonomous and multi-agent solutions using large language models, retrieval-augmented generation, reasoning workflows, tool integration, and orchestration frameworks.
  • Define AI transformation roadmaps, delivery plans, success metrics, governance standards, risk controls, and reusable accelerators.
  • Guide the implementation of responsible AI practices covering security, privacy, explainability, human oversight, hallucination controls, and regulatory compliance.
Data Management and Data Modernization
  • Lead legacy-to-cloud data modernization, data migration, platform consolidation, and enterprise data transformation programs.
  • Define and implement data management capabilities across data governance, data quality, metadata management, master data management, data lineage, and lifecycle management.
  • Oversee modernization of data lakes, data warehouses, lakehouse platforms, analytics ecosystems, and real-time data processing solutions.
  • Ensure modern data foundations are scalable, trusted, secure, and ready to support AI, analytics, and reporting use cases.
  • Drive DataOps practices, reusable ingestion and transformation frameworks, and standardized ETL/ELT delivery patterns.
AWS Cloud and Engineering Leadership
  • Provide technical oversight for cloud-native data and AI platforms using AWS services such as S3, Glue, Redshift, EMR, Lambda, Step Functions, Lake Formation, SageMaker, DynamoDB, ECS/EKS, IAM, and CloudWatch.
  • Drive architecture decisions across data engineering, APIs, microservices, event-driven integration, containerization, infrastructure as code, and cloud security.
  • Establish CI/CD, DevOps, MLOps, observability, reliability, performance, and cost-optimization practices for production workloads.
  • Partner with architects and engineering teams to develop scalable reference architectures and engineering standards.
Program and Stakeholder Leadership
  • Manage cross-functional global teams including AI Engineers, Data Engineers, Data Scientists, Architects, Product Owners, Business Analysts, QA, DevOps, and domain SMEs.
  • Own program planning, estimation, budgeting, staffing, delivery governance, dependency management, risk mitigation, and executive reporting.
  • Facilitate business and technology workshops to identify high-value AI and data modernization opportunities.
  • Communicate roadmaps, architecture decisions, delivery status, risks, and business outcomes to senior stakeholders and clients.
  • Mentor teams and promote engineering excellence, delivery discipline, innovation, and reusable solution patterns.
P&C Insurance Transformation
  • Partner with underwriting, claims, policy administration, actuarial, billing, risk, and customer-service teams to identify AI-led transformation opportunities.
  • Lead data modernization and AI initiatives supporting underwriting automation, claims intelligence, fraud detection, pricing analytics, risk insights, and customer servicing.
  • Align delivery with insurance data standards, governance expectations, privacy requirements, and regulatory controls.
Required Qualifications
  • 12+ years of experience across Data and Analytics, AI/ML, Cloud Transformation, Enterprise Architecture, or Digital Transformation.
  • 5+ years of experience leading large-scale data modernization, data management, cloud, AI, or analytics programs.
  • Proven experience delivering enterprise AI, Generative AI, or Agentic AI solutions into production.
  • Strong delivery leadership experience across globally distributed, cross-functional teams.
  • Hands-on understanding of modern data architectures, data engineering, cloud-native design, APIs, security, DevOps, DataOps, and MLOps.
  • Strong executive communication, client management, solutioning, estimation, governance, and risk-management skills.
Technical Skills
  • Agentic AI and GenAI: Agentic workflows, multi-agent systems, LLMs, RAG, embeddings, vector databases, knowledge graphs, prompt engineering, LangGraph, LangChain, CrewAI, AutoGen, and Semantic Kernel.
  • Data Management: Data governance, data quality, metadata management, master data management, data lineage, reference data, privacy, security, and lifecycle management.
  • Data Modernization: Cloud migration, data migration and conversion, legacy modernization, data lakes, data warehouses, lakehouse architecture, ETL/ELT, streaming, and platform consolidation.
  • AWS: S3, Glue, Redshift, EMR, Lambda, Step Functions, Lake Formation, SageMaker, DynamoDB, ECS/EKS, IAM, CloudWatch, and infrastructure as code.
  • Data Platforms: Databricks, Snowflake, Spark/PySpark, Kafka, Delta Lake, Python, and SQL.
  • DevOps and MLOps: CI/CD, Git, Jenkins or GitHub Actions, Docker, Kubernetes, Terraform or CloudFormation, model deployment, monitoring, and observability.
Preferred Qualifications
  • Property & Casualty (P&C) Insurance experience, including exposure to policy, claims, underwriting, actuarial, billing, risk, or insurance data ecosystems.
  • Experience leading data migration, data management, or platform modernization programs within insurance organizations.
  • Familiarity with Guidewire, Duck Creek, or other insurance core platforms.
  • Experience with AI governance, model risk management, responsible AI, and regulated enterprise environments.
  • PMP, SAFe, Scrum, AWS Solutions Architect, AWS Data Engineer, AWS Machine Learning, or relevant AI/data certifications.
  • Business value realization and outcome measurement

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