Lead Software Engineer - Python - GenAI

Lead Software Engineer role in Corporate Technology focused on secure, scalable production services and ML/AI enablement.

Responsibilities

• Architect and implement resilient, highly scalable, fault-tolerant, low-latency services; drive target-state architecture.
• Design and deploy services integrating with enterprise systems, ensuring functional, performance, scalability, security, governance, and auditability requirements are met.
• Lead and mentor engineering delivery in a high-pressure environment; manage multiple deliverables across business groups and strengthen stakeholder relationships.
• Partner with LOB users, SMEs, architects, DBAs, and system administrators to design solutions, manage enhancements, and resolve issues.
• Build and mature capabilities to execute ML pipelines for fraud detection and risk assessment; support modeling teams with implementation and tooling.
• Productionalize data scientist models, including validation readiness and quality controls before live usage.
• Drive adoption of enterprise-authorized AI-assisted engineering practices, including AI-assisted code review/refactoring, accelerated test strategy, and incident/root-cause analysis support, with consistent validation standards (secure coding, peer review, automated testing) and reusable patterns.
• Apply Software Development Life Cycle toolchain capabilities, including enterprise-authorized AI-assisted development and automation, to improve value realized by automation.
• Design and own reusable ML platform components (for example: feature-store patterns, delivery pipelines) and establish monitoring/alerting for performance, scalability, availability, and reliability.
• Build agentic AI services to automate and enhance engineering and model-ops workflows, including tool-using agents, orchestration, state management, and audit-ready traceability.
• Define and implement guardrails and evaluation approaches for agentic AI in production, covering quality, safety, latency, and cost.

Requirements

• 5+ years applied experience with formal training or certification on software engineering concepts; hands-on delivery across system design, application development, testing, and operational stability.
• Deep distributed-systems engineering expertise in Python/Java plus strong platform, delivery, and production-operability discipline; recent hands-on experience with large-scale distributed systems, primarily Python and modern microservices.
• Strong Python experience for AI/ML engineering, automation, model operationalization, and agentic AI services, including tool integration, monitoring, telemetry, and governance.
• Strong experience with REST APIs and service-oriented / microservices architecture.
• Demonstrated experience leading effective use of approved AI-assisted software development tools (coding, code review, test acceleration, troubleshooting), including setting team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI in engineering workflows, including data sensitivity, secure handling of inputs/outputs, and adherence to resiliency and security expectations; coaching engineers on safe, compliant adoption.
• Experience developing in Linux environments.
• Strong Kubernetes orchestration experience, including building, deploying, and operating production services.
• Messaging expertise with Kafka, MQ, or similar platforms.
• Backend infrastructure pattern experience (load balancing, autoscaling); NoSQL experience with Cassandra; log analytics/observability tools such as ELK or Splunk.
• Strong SDLC knowledge and agile ways of working, including CI/CD, application resiliency, security, testing, and operational stability; strong communication skills and ability to influence senior technology and business stakeholders.
• AI/ML platform exposure including MLOps, feature engineering, and model hosting/operationalization with AWS and/or hybrid on-prem plus cloud.
• Agentic AI experience building and operating LLM-driven agents with tool integration, monitoring/telemetry, and governance/audit considerations.

Technologies

• Python, Java
• AI-assisted software development tools
• REST APIs, microservices
• Linux, Kubernetes
• Kafka, MQ
• Cassandra
• ELK, Splunk
• CI/CD
• MLOps, feature engineering
• AWS
• LLM-driven agents

Benefits

• Competitive total rewards package including base salary
• Commission-based pay and/or discretionary incentive compensation (for eligible roles)
• Paid in the form of cash and/or forfeitable equity
• Comprehensive health care coverage
• On-site health and wellness centers
• Retirement savings plan
• Backup childcare
• Tuition reimbursement
• Mental health support
• Financial coaching

Preferred Qualifications, Capabilities, and Skills

• AWS Certification(s) and/or working knowledge
• AI Certification(s) and/or working knowledge

About the Team

• Corporate Functions professionals cover areas including finance and risk, human resources, and marketing.
• Corporate teams help set businesses, clients, customers, and employees up for success.