Job Title: Data AI Engineering Lead

Company Name: RevStar

Job Url: https://revstarcareers.com/data-ai-engineering-lead-revstar-careers?jr_id=69a89d5d79f3f4037f42b483

Job Description: Role and Responsibilities
Technical Leadership (Player-Coach)
Act as a hands-on technical leader across:
Data platforms and analytics
Machine learning systems
GenAI and Agentic AI solutions
Provide architectural guidance for:
Data lakes, lakehouses, and analytics platforms
ML pipelines, evaluation, and lifecycle management
Agentic AI systems (multi-agent workflows, orchestration, tool use, memory, and state)
Serve as an escalation point for complex data, AI, and agentic system challenges
Partner with Product Managers and Tech Leads to validate feasibility, scalability, and long-term maintainability
Lead by example through production-grade architectures and technical decision-making
Standards, Governance & Center of Excellence
Lead the Data, GenAI & Agentic AI Standards Committee
Define, document, and enforce standards for:
Data ingestion, modeling, transformation, and governance
ML system design, evaluation, and deployment
GenAI patterns (RAG, embeddings, prompt orchestration)
Agentic AI patterns (planning, tool calling, decision loops, memory, guardrails)
Security, compliance, and data privacy
Observability, cost controls, and performance management
Operate a Data & AI Center of Excellence supporting all delivery teams
Review projects for standards compliance and coach teams on remediation
Ensure consistency across high-volume QuickStarts and long-running production engagements
Enablement, Training & Leadership Development
Design and deliver internal training on:
AWS-native data platforms and analytics
ML and GenAI system design
Agentic AI architecture and implementation
Data quality, lineage, and governance
LLM evaluation, safety, and monitoring
Lead Data & AI Leadership Labs focused on:
Scaling from POC to production
Responsible AI and agent governance
Human-in-the-loop and fail-safe design for agents
Mentor senior engineers and technical leads as they grow into advanced roles
Improve onboarding and time-to-productivity through shared patterns, templates, and accelerators
Accelerators, Reference Architectures & Reusability
Build and maintain reusable assets including:
Data ingestion and transformation pipelines
RAG and hybrid search reference architectures
Agentic AI reference architectures (single-agent and multi-agent systems)
ML training, evaluation, and deployment templates
Cost-optimized analytics and reporting patterns
Ensure accelerators are:
Secure and compliant
Observable and cost-aware
Production-ready by default
Continuously evolve assets based on delivery learnings and AWS roadmap updates
Cross-Functional Collaboration
Partner closely with:
Product Management Leads
Data Product Managers
DevOps and Security leadership
Ensure alignment between:
Business outcomes
Data, AI, and agentic architectures
Delivery execution
Support discovery, estimation, and technical validation during pre-sales and planning
Enable consistent execution across distributed teams
Continuous Improvement & Innovation
Identify systemic issues across Data, GenAI, and Agentic AI projects and drive practice-wide improvements
Stay current on:
AWS Data & AI services
Obtaining and maintaining AWS certifications
Agentic AI frameworks and orchestration patterns
Governance, evaluation, and safety techniques for autonomous systems
Evaluate emerging tools and patterns and translate them into RevStar standards
Balance innovation with operational excellence and repeatability
Qualifications
Required
7+ years of experience in data engineering, analytics, ML, or AI systems
Deep hands-on experience designing and delivering cloud-native Data, GenAI, and Agentic AI systems on AWS
Strong programming skills in Python (data manipulation, APIs, automation)
Proven experience with:
Data lakes, warehouses, and analytics platforms
ML lifecycle management and evaluation
GenAI systems (RAG, embeddings)
Agentic AI systems (tool calling, orchestration, memory, planning)
Demonstrated ability to lead standards and influence technical direction across multiple teams
Excellent written and verbal communication skills
Ability to lead through expertise rather than authority
AWS certifications (GenAI, Solutions Architect, or equivalent)
Preferred
Experience in consulting or agency environments
Familiarity with:
CI/CD and Infrastructure-as-Code (CDK, Terraform)
MLOps and LLMOps / AgentOps tooling
Regulated environments (HIPAA, financial data, privacy controls)
Experience building internal frameworks, accelerators, or Centers of Excellence
What This Role Is — and Is Not
This role is:

A hands-on technical leader
The owner of Data, GenAI, and Agentic AI engineering standards
A coach and multiplier for delivery teams
A builder of systems, patterns, and enablement
This role is not:

A people manager with direct reports
A project manager or delivery coordinator
A purely strategic or non-technical role
While this role mentors engineers on technical growth, all administrative, performance-rating, and career-pathing conversations remain with the Product Manager.

Location
Remote, United States