Envestnet
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Thiruvananthapuram · Hybrid · 3-5 Yrs · Oct 14
Investment & Asset Management · 1001 to 5000 Employees · Chicago, US
Envestnet is a leading independent provider of technology‐enabled investment and practice management solutions to financial advisors who are independent, as well as those who are associated with small or mid‐sized financial advisory firms and larger financial institutions. Envestnet's technology is focused on addressing financial advisors' front, middle, and back‐office needs while leveraging our platform to grow their businesses and expand client relationships. We offer a highly competitive compensation and benefits package as well as the excitement, challenges, and rewards of a fast-growing, entrepreneurial company.
Hiring: Engineering
What employees say
+ Work life balance Friendly atmosphere
− Low pay Changing culture after bain acquisition
More reviews on the company profile.
Interview experience · Product Developer
The Envestnet interview was moderate and technical in nature, with a strong emphasis on problem-solving skills and core programming fundamentals. Candidates were expected to build logic without relying on inbuilt functio
Very_difficult difficulty · India · 126 reports
More interview insightsJob description
Overview
The primary work location for this role is with a hybrid work model.
Responsibilities
- Lead the design, development, and deployment of scalable AI-enabled applications and services that improve business outcomes, engineering efficiency, and product innovation.
- Architect and implement production-grade AI systems utilizing LLMs, Generative AI technologies, Retrieval Augmented Generation (RAG), intelligent agents, and AI-assisted workflows.
- Design and develop reusable AI frameworks, APIs, and platform capabilities that accelerate AI adoption across teams.
- Establish best practices for AI development, deployment, observability, testing, monitoring, and operational excellence.
- Drive adoption of MLOps/LLMOps practices to support scalable model lifecycle management and production deployment.
- Provide architectural guidance on AI integrations with enterprise platforms including Wealth Management systems, identity platforms, data ecosystems, and internal applications.
- Demonstrated experience in engineering across software, data, and machine learning domains, including building and deploying production-grade AI/ML systems.
- Strong hands-on proficiency in Python, with a solid foundation in software engineering best practices (e.g., code quality, testing, version control, and design patterns).
- Hands-on experience with vector databases and semantic search technologies (e.g., pgvector, Pinecone, Weaviate, Redis, OpenSearch).
- Experience designing and operationalizing ML/LLM Ops pipelines using platforms such as ML flow, Azure ML, SageMaker, or Kubeflow.
- Proven experience developing and deploying AI solutions leveraging Large Language Models (LLMs) and Generative AI workloads, Retrieval-Augmented Generation (RAG) architectures, agentic frameworks such as LangChain, Strands, or similar
Nice to have
- Experience integrating AI/ML solutions with enterprise platforms such as wealth management systems, data lake houses, and identity/access management systems.
- Expertise in system design and architecture, including APIs, microservices, serverless computing, and event-driven architectures.
- Solid understanding of security best practices, including identity and access management (IAM), secrets management, data loss prevention (DLP), private networking, and encryption.
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Job application FAQ
Last updated 27 October 2026
- How do I apply for Senior AI Engineer at Envestnet?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. Envestnet may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this Senior AI Engineer role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is Senior AI Engineer remote or on-site in Thiruvananthapuram, Keralam?
- This listing is marked hybrid with location Thiruvananthapuram, Keralam. Confirm details on the job description before applying.
- What skills matter for this Senior AI Engineer role at Envestnet?
- This is a senior Senior AI Engineer role. Key skills include Hybrid. Feedback AI highlights matched vs missing skills on your profile after signup.