Lead Software Development Engineer
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Role details
Tech stack
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Job description
You will join a collaborative engineering team focused on building scalable, data-driven reporting solutions and advancing AI-enabled capabilities for financial services. As a Lead Engineer, you’ll work closely with engineers, product partners, and stakeholders to drive technical decisions, deliver high-impact features, and align solutions to business goals. The team emphasizes modern architectures, AI/ML and LLM-based innovation, and strong engineering practices-leveraging cloud technologies and agentic coding tools to improve reliability, accelerate delivery, and continuously enhance reporting capabilities.
How You’ll Contribute
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
- Candidates should demonstrate the relevant experience, skills, and capabilities needed to successfully perform in the role. Relevant experience may be gained through current responsibilities, prior roles, project work, leadership opportunities, or other comparable experiences.
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field required; master’s degree preferred.
- 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.
Benefits & conditions
This role offers a base salary range of $152,300 to $190,400. The range listed represents a good-faith estimate of base salary compensation for this position and does not include incentive compensation, equity or benefits. Individual pay will be determined based on factors including, but not limited to, relevant experience, skills, education, certifications, and geographic location, in accordance with applicable pay transparency laws. This role is eligible for an additional incentive component as part of the total rewards package.
We provide a comprehensive suite of benefits - subject to Envestnet’s plan eligibility rules - that support your overall well-being including, medical insurance, paid time off (PTO), 401k company match, paid parental leave, education reimbursement, disability coverage and mental health & wellness support. Our investment in you means supporting you professionally, financially, and personally at every stage of your journey with us. Please visit our benefits page on our career site to learn more.
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