Software Engineering Lead HYBRID in Raleigh, NC

Position: Software Engineering Lead ***HYBRID in Raleigh, NC
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** About our Team
** Lexis Nexis Legal & Professional, which serves customers in more than 150 countries with 11,800 employees worldwide, is part of , a global provider of information-based analytics and decision tools for professional and business customers. Our company has been a long-time leader in deploying AI and advanced technologies to the legal market to improve productivity and transform the overall business and practice of law, deploying ethical and powerful generative AI solutions with a flexible, multi-model approach that prioritizes using the best model from today’s top model creators for each individual legal use case.
** About the Role
**** The Lead for our Software Engineering
** team serves as a subject matter expert for a specific team of Software Engineers working toward our new Lexis + AI initiative. You will be instrumental in driving the design, development, and operationalization of scalable, robust solutions working closely with data scientists and engineers to deliver high-impact features for our customers. This is a hands-on leadership role that also requires technical mentoring, architectural thinking, and team guidance across the full application lifecycle.

The position has direct reports.
** Position is required to work in Raleigh, NC with a Hybrid schedule
**** Requirements:
*** 7+ years of professional experience in software development.
* Strong proficiency in
** Python programming language.
*** Strong understanding of software development best practices and methodologies.
* Experience with version control systems (e.g., Git).
* Excellent problem-solving skills and attention to detail.
* Experience with
** web frameworks (Django, Flask, FastAPI).**
* ** Experience with customer facing API design and tradeoffs.
*** Experience with containerization technologies (e.g., Docker, Kubernetes).
* ** Experience with system architecture and API design.**
* ** Led a team or mentored Jr engineer
** s* Hands on experience working with AWS and/or Azure services, such as:  + Compute: EC2, Lambda, Azure Functions  + Storage: S3, Azure Blob  + Databases: RDS, Dynamo

DB, Cosmos DB, Document

DB  + Messaging Services: AWS SNS  + Networking, IAM, and monitoring tools
* Experience working with
** cache databases
** and in-memory data stores such as
** Redis or Memcached
** to optimize read-heavy workloads, inference serving, and low-latency systems.
* Experience designing or working with
** data storage and retrieval systems**, both structured and unstructured
* Experience with
** vector databases** (e.g., Pinecone, FAISS, Weaviate) and
** search technologies** (e.g., Solr, Elasticsearch, Open Search).
* Familiarity with
** observability stacks**: logging (EFK, ELK), monitoring (Prometheus, Datadog, Grafana), and distributed tracing (Open Telemetry).
* Experience integrating and managing
** messaging systems** (e.g. AWS SNS, Kafka)
* Solid understanding of
** access control**,
** IAM**,
** RBAC**, and
** secrets management
** tools (e.g., AWS Secrets Manager, Azure Key Vault).
** Preferred Skills
*** Knowledge of LLM, machine learning pipeline and deployment strategies.
* Knowledge of other programming languages (e.g., Go, Java).
** Responsibilities*
* • Work closely with data scientists and engineers to understand product requirements and translate them into scalable software designs.
• Successfully implement and advocate for development processes, coding best practices, and code reviews
• Operate within various development environments (Agile, Scrum, Kanban, Waterfall) while collaborating with key cross-functional stakeholders
• Architect and optimize
** data storage and retrieval systems
** using structured and unstructured formats (e.g., S3)
• Build and integrate
** vector databases** (e.g., Pinecone, Weaviate, FAISS) and traditional
** search technologies** (e.g., Solr, Elasticsearch, Open Search) to power information retrieval and AI applications.
• Design and deploy
** messaging systems** (e.g., AWS SNS) to support asynchronous and streaming workloads.
• Monitor system and application health in real-time to ensure performance and uptime
• Work with data scientists and engineers to define and track
** model…