Lead Software Engineer - Python - GenAI

About the job

Responsibilities

• Architect and implement resilient, highly scalable, fault-tolerant, low-latency services and drive target-state architecture.
• Design and deploy services that integrate with enterprise systems, ensuring functional, performance, scalability, security, governance, and auditability requirements are met.
• Lead and mentor the development team in a high-pressure delivery environment, managing multiple deliverables and strengthening stakeholder relationships.
• Collaborate with LOB users, SMEs, architects, DBAs, and system administrators to design solutions, manage enhancements, and resolve issues.
• Build and mature capabilities that execute ML pipelines for fraud detection and risk assessment, supporting modeling teams in implementation and tooling.
• Productionalize models built by data scientists, including validation readiness and quality controls prior to live usage.
• Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes.
• Apply knowledge of the Software Development Life Cycle toolchain, including AI-assisted development and automation capabilities, to improve value realized by automation.
• Design and own reusable ML platform components (e.g., 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 (tool-using agents, orchestration, state management, and audit-ready traceability).
• Define and implement guardrails and evaluation approaches for agentic AI in production (quality, safety, latency, and cost).

Requirements

• Formal training or certification on software engineering concepts and 5+ years of applied experience.
• Hands-on practical experience delivering system design, application development, testing, and operational stability.
• Deep distributed-systems engineering expertise in Python/Java with strong platform, delivery, and production-operability discipline.
• Recent hands-on software development experience in 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.
• Ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations.
• Experience coaching engineers on safe, compliant adoption within delivery practices.
• Experience developing in Linux environments.
• Strong Kubernetes orchestration experience (building, deploying, and operating production services).
• Messaging expertise with Kafka, MQ, or similar platforms.
• Experience with backend infrastructure patterns (e.g., load balancing, autoscaling).
• Experience with NoSQL databases such as Cassandra.
• Experience with log analytics / observability tools (e.g., ELK, Splunk).
• Strong SDLC knowledge and agile ways of working, including CI/CD, application resiliency, security, testing, and operational stability.
• Strong communication skills and proven ability to influence across senior technology and business stakeholders.
• AI/ML platform exposure (MLOps, feature engineering, model hosting/operationalization).
• AWS and/or hybrid on-prem + cloud experience.
• Agentic AI experience: building and operating LLM-driven agents with tool integration, monitoring/telemetry, and governance/audit considerations.