Lead Software Development Engineer

Envestnet is hiring a Lead Software Development Engineer to build scalable, secure platforms and reporting solutions for financial services. The role leads architecture and technical decisions, integrates AI/ML capabilities, and partners across engineering, product, and business teams to deliver reliable systems that meet business and regulatory needs.

Responsibilities:

• Responsible for building scalable, secure platforms in support of Envestnet business operations, including wealth management, financial data aggregation and advisor-driven technology solutions. Works across cloud-based architectures, integrating complex data sources and APIs to deliver reliable, high-performance systems. Collaborates with product managers, data scientists and compliance stakeholders to meet both business and regulatory requirements
• Architects and designs systems, services, or platforms with broad impact
• Leads technical decision-making for major features or initiatives
• Breaks down complex problems into scalable and maintainable solutions
• Drives cross-team collaboration and align technical solutions with business goals
• Establishes and enforces best practices in architecture, coding, and deployment
• Mentors engineers across multiple levels and contribute to talent development
• Anticipates technical risks and proactively implement mitigation strategies
• Leads incident response and root cause analysis for critical issues
• Influences roadmap planning through technical insight and feasibility analysis
• Partners with DevOps/SRE to improve system reliability, deployment automation, and observability
• Designs and maintains CI/CD pipelines for owned services, improving deployment speed and safety
• Implements infrastructure-aware design decisions (scalability, failover, resiliency, cost)
• Leads the design and delivery of scalable reporting solutions, leveraging Java and/or Python, cloud infrastructure, RESTful APIs, event-driven architectures, and SQL/NoSQL technologies
• Specializes in AI/ML integration, LLM-based capabilities, and AI platform engineering, including the support and enhancement of production AI/ML applications
• Utilizes agentic coding tools and AI-enabled development practices to accelerate feature delivery, improve code quality, and enhance software development lifecycle efficiency
• Partners with business, product, and quality engineering stakeholders to translate complex requirements into robust, maintainable solutions and ensure successful end-to-end delivery

Requirements:

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field required
• Strong technical background with .NET, xUnit, Reqnroll, RESTful APIs, and API management solutions such as Apigee
• Experience with PostgreSQL, SQL Server, Redis, and ElastiCache
• Experience with AWS services including EC2, S3, ELB, ASG, API Gateway, Lambda, RDS, EKS, CloudWatch, SQS
• Experience with Kubernetes, Docker, Kafka, CloudFormation, CDK, Terraform, DevOps practices, automation, agile delivery, Scrum, and test-driven development
• 2+ years designing, delivering, or integrating production-grade AI/ML systems, LLM-based applications, AI platform capabilities, and agentic workflows
• Experience with Python-based AI/ML application support, enhancement, maintenance, reliability, scalability, and production readiness
• Strong knowledge of AI cost control, evaluation, governance, LLM integration patterns, stateful agents, memory patterns, and practical AI use case delivery
• Experience with event-driven architectures, Kafka or asynchronous messaging, cloud infrastructure such as AWS, GCP, or Azure, and observability practices
• Demonstrated ability to lead architectural decisions, define technical standards, conduct code reviews, and communicate trade-offs to technical and non-technical stakeholders
• Experience in fintech, reporting, real-time financial platforms, regulated production environments, or other domains requiring strong data consistency, idempotency, fault tolerance, and scalability
• Hands-on experience using agentic coding tools such as Claude Code or GitHub Copilot to accelerate feature delivery, code review, testing, and SDLC execution
• master's degree