Summary

RevStar is seeking a senior, hands-on Data & AI Engineering Lead to serve as the technical standard expert and force multiplier for our Data, GenAI, and Agentic AI practice.

This is a player-coach role, with strong leadership skills required. The Data & AI Engineering Lead does not directly manage individual contributors day-to-day. Instead, this role focuses on raising the quality, consistency, and scalability of all Data, GenAI, and Agentic AI solutions delivered by RevStar, while mentoring, coaching, and supporting the success of the engineering team.

Our Product Managers own project execution and delivery teams. The Data & AI Engineering Lead is responsible for:

• Establishing and enforcing data, ML, GenAI, and agentic system engineering standards
• Operating a Data, GenAI & Agentic AI Center of Excellence
• Leading standards committees, internal training, and leadership labs
• Creating reusable accelerators, reference architectures, and boilerplate pipelines
• Ensuring all teams are building production-ready, scalable, secure, and observable data and AI systems on AWS
• 100% of active projects utilizing the "Standard Reference Architectures."
• Demonstrable reduction in hours required for "Data QuickStarts" due to accelerators.
• High Net Promoter Score from Tech Leads who rely on this role for escalation and coaching.
• Key "Center of Excellence" assets are updated quarterly to reflect key market shifts.

This role remains deeply hands-on in architecture and system design while enabling dozens of concurrent projects to move faster with confidence.

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

Company Benefits

• Paid Time Off – Take the time you need to recharge and stay productive.
• Remote-First Working Environment – Collaborate from anywhere while staying connected with our global team.
• Comprehensive Health Coverage – Medical, Dental, Vision, FSA, HSA, Short-Term & Long-Term Disability.
• Annual Learning & Development Stipend – Invest in your skills with conferences, certifications, or courses.
• Peer Mentorship & Coaching – Learn from experienced engineers, product managers, and architects to accelerate your growth.
• Professional Growth Opportunities – Exposure to cutting-edge AWS GenAI, data, and cloud technologies across diverse industries.
• Company Outings & Volunteer Opportunities – Build relationships and give back to the community.
• Collaborative, Innovative Culture – Work alongside top talent in a fast-paced, supportive environment that values curiosity and initiative.