Note: The job is a remote job and is open to candidates in USA. 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
Skills
- 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
Benefits
- Remote work model.
- An additional incentive component as part of the total rewards package.
- Subject to Envestnet’s plan eligibility rules: medical insurance, paid time off (PTO), 401k company match, paid parental leave, education reimbursement, disability coverage, and mental health & wellness support.
Company Overview
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