Software Engineering Lead

Reed Technology•Raleigh, NC

2d•Remote

About The Position

As a Team Lead you will serve as a hands-on technical leader and people manager for a team of Data Scientists / Applied AI Engineers focused on building, deploying, and scaling customer-facing and internal AI-powered features. In addition to contributing directly to solution design, experimentation, and code delivery, this role provides direction on execution plans, delivery schedules, technical approaches, and operational excellence. The position has direct reports.

Requirements

Strong experience building and shipping AI/ML-powered product features in production environments, with an emphasis on implementation, iteration, and measurable outcomes over research prototypes.
Advanced knowledge of machine learning development lifecycles, including problem framing, data preparation, model development, evaluation, deployment, monitoring, and continuous improvement.
Experience applying techniques such as predictive modeling, classification, ranking, recommendation systems, NLP, LLM-powered workflows, or other statistical/ML methods to real business problems.
Strong proficiency in Python and common data science / machine learning libraries and frameworks.
Experience partnering closely with software engineering teams to productionize models and integrate AI capabilities into scalable applications and services.
Strong knowledge of software development best practices, including version control, testing, code review, CI/CD, and agile delivery methodologies.
Experience designing experiments, defining success metrics, and using offline and online evaluation methods to assess feature performance.
Strong understanding of data modeling, data quality, feature engineering, and working with structured and unstructured data.
Proficiency with SQL and data manipulation techniques, including performance optimization.
Experience with modern data and ML tooling, including cloud platforms, model serving, orchestration, monitoring, and MLOps practices.
Ability to guide build-vs-buy decisions and effectively leverage third-party AI platforms, foundation models, or vendor capabilities where appropriate.
Strong problem-solving skills, including the ability to translate ambiguous business needs into practical technical solutions.
Ability to write and review detailed technical designs, model documentation, and implementation plans for complex systems.
Strong skills in setting, communicating, implementing, and achieving business objectives through direct management of others.

Responsibilities

Lead a team of Data Scientists / Applied AI Engineers responsible for delivering production AI capabilities that improve products, workflows, and customer outcomes.
Serve as the initial point of escalation for technical and delivery issues within the team’s area of responsibility.
Contribute directly to hands-on technical work, including solution design, coding, experimentation, model development, feature implementation, and production troubleshooting.
Partner with product, engineering, design, and business stakeholders to define requirements, prioritize opportunities, and translate business needs into deployable AI solutions.
Drive delivery of AI/ML features from concept through launch, ensuring solutions are robust, scalable, maintainable, and aligned to business goals.
Establish and uphold best practices for experimentation, model evaluation, deployment, monitoring, and ongoing optimization of AI systems in production.
Work closely with engineering teams to operationalize models and AI services, including APIs, batch pipelines, real-time inference, and human-in-the-loop workflows where applicable.
Help the team focus on pragmatic execution by balancing innovation with speed, reliability, cost, explainability, and operational constraints.
Define and monitor success metrics for shipped features, and use feedback, telemetry, and experimentation results to drive continuous improvement.
Write and review technical specifications, implementation plans, and design documents for moderately to highly complex AI-enabled systems.
Resolve complex technical issues involving data, modeling, integration, deployment, and production performance.
Mentor and develop team members in both technical execution and business impact, ensuring they are equipped to build and ship high-value AI features.
Keep abreast of developments in applied AI, machine learning, LLMs, and adjacent technologies, and identify practical opportunities to apply them.
Carry out management responsibilities in accordance with organizational policies and applicable laws, including interviewing, hiring, training, performance management, coaching, recognition, and addressing employee concerns.

Benefits

Shared parental leave
Study assistance
Sabbaticals
Working flexible hours
Comprehensive, multi-carrier program for medical, dental and vision benefits
401(k) with match
Employee Share Purchase Plan
Wellness platform with incentives
Headspace app subscription
Employee Assistance and Time-off Programs
Short-and-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital Indemnity
Family benefits, including bonding and family care leaves, adoption and surrogacy benefits
Health Savings, Health Care, Dependent Care and Commuter Spending Accounts
Up to two days of paid leave each to participate in Employee Resource Groups and to volunteer with your charity of choice