Team Lead, Engineering, Data & AI

This is a fully remote position, open to applicants in Tennessee.

📋 Description

• Take ownership of the complete delivery process for a portfolio of fixed-price client projects.

• Ensure thorough visibility into project health across the team.

• Manage scope diligently and effectively.

• Verify that project financials are precise and up-to-date.

• Conduct organized post-engagement evaluations.

• Collaborate with sales and business development to define new client opportunities.

• Lead or supervise effort estimation for engineering outputs.

• Review and approve SOW language related to engineering outputs.

• Act as the primary engineering contact for clients.

• Communicate project status, risks, and decisions proactively.

• Navigate challenging conversations when projects are not on track.

• Mentor, coach, and develop a team of solution engineers.

• Thoughtfully assign engineers to various engagements.

• Create and continuously enhance delivery playbooks, estimation templates, and reusable tools.

⛳️ Requirements

• Over 7 years of experience in data engineering, ML/AI engineering, or a closely related technical field.

• More than 3 years in an engineering leadership or delivery management position within a professional services, consulting, or systems integration organization.

• Proven experience managing fixed-price or outcome-based client engagements.

• History of building and nurturing high-performing engineering teams in a client delivery setting.

• Experience in supporting pre-sales activities, including scoping, estimation, and proposal preparation.

• Strong knowledge of modern cloud data platforms (e.g., Databricks, Microsoft Fabric, BigQuery, etc.).

• Familiarity with AI and ML engineering, encompassing model deployment, MLOps, and the practical application of LLMs (RAG pipelines, prompt engineering, API integration).

• Proficient in Python and SQL; hands-on experience with dbt, Airflow, Spark, or similar transformation and orchestration tools.

• Ability to read, review, and provide constructive technical feedback on engineering outputs.

• Understanding of DataOps principles: CI/CD for data, data quality frameworks, testing, and production observability.

🏝️ Benefits

• Flexible work arrangements.

• Opportunities for professional development.