Performs independent and complex technical and functional analysis for multiple projects supporting several divisional initiatives. Performs deep data analysis on multiple databaseplatforms,using SQLSupports customer personalization and optimization efforts according to Artificial Intelligence (AI) and Machine Learning (ML) techniques. Designs, implements, and improves technical solutions for AI model deployment, data pipelines, hosting, and Application Programming Interface (API) access.Deployscode and services to Amazon Web Services (AWS) byestablishingContinuous Integration/Continuous Deployment (CI/CD) pipelines. Develops APIs and front-end applications, using Java, Spring Boot, Python, or Angular. Extracts and manipulates data pulled from databases or unstructureddata sources, by building AWS-based AI solutions 

Primary Responsibilities:

• Builds sophisticated analytics and ML platforms and tools to enable innovative AI solutions that enhance data accessibility and intelligent automation.

• Designs, builds, andautomatescomplex and customized data pipelines with multiple ingress sources and consumers.

• Automates manual and error prone processes using AI and ML techniques.

• DeploysML models and operations.

• Deploys solutions using software engineering principles.

• Deployssolutions using Cloud technologies.

• Buildsinnovative and high business value AI powered solutions to improve customer experiences.

• Participatesin architecture design discussions and implements application-level architecture.

• Developscomprehensive documentation for multiple applications or subsystems.

• Establishes full project life cycle plans for complex projects across multiple platforms.

• Advises onrisk assessment and risk management strategies for projects.

• Plans and coordinates project schedules and assignments for multiple projects.

• Provides technology solutions to daily issues and technical evaluation estimates on technology

• initiatives

• Advisessenior management on technical strategy.

• Mentors junior team members.

• Develops original and creative technical solutions toon-goingdevelopment efforts

Education and Experience

Bachelor’s degree in Computer Science, Engineering, Information Technology, Information Systems, Data Science, Analytics, Mathematical Finance, or a closely related field (or foreign education equivalent) and five (5) years of experience as aPrincipal AI/ML Engineer (or closely related occupation) performing requirement analysis, design, and development of Cloud-native AI and ML platforms, using information retrieval systems, vector structured and unstructured databases, and production model serving infrastructure in a financial services environment 

Or, alternatively, Master’s degree in Computer Science, Engineering, Information Technology, Information Systems, Data Science, Analytics, Mathematical Finance, or a closely related field (or foreign education equivalent) and three (3) years of experience as aPrincipal AI/ML Engineer(or closely related occupation) performing requirement analysis, design, and development of Cloud-native AI and ML platforms, using information retrieval systems, vector structured and unstructured databases, and production model serving infrastructure in a financial services environment

Skills and Knowledge

Candidate must alsopossess

• Demonstrated Expertise (“DE”)developing retrieval-augmented generation (RAG) systems using Python,FastAPI, Large Language Models (Claude, Bedrock, or Azure OpenAI), vector databases, and AWS OpenSearch; building asynchronous REST APIs with sub-500msresponse times usingasyncioand Kubernetes; creating interactive user interfaces (UIs) for experimenting with chunking strategies and search algorithms, usingStreamlitand Python; and performing root cause analysis and debugging, and logging frameworks to mitigate memory leaks and production issues, using Python profilers  

• DEarchitecting AI and ML infrastructure using AWS SageMaker, Lambda, Docker, or Kubernetes; developing REST APIs for Vision-Language Models (VLMs) usingFastAPI, andsupportingBase64image-to-tensor transformations; implementing multimodal inference endpoints using SageMaker processing image-text pairs with similarity scoring; and establishing cross-Virtual Private Cloud (VPC) connections usingPrivateLinkfor multi-business unit access 

• DEbuilding feature store architectures for real-time model serving using AWS SageMaker Feature Store,S3, or Athena; implementing parallel processing frameworks to achieve latency reduction, using Python multiprocessing and concurrent futures; developing data Extract-Transform-Load (ETL) pipelines processing millions of records using AWS Glue, Step Functions, orPySpark; and deploying ML models using SageMaker endpoints for real-time inference and SageMaker Processing Jobs for batch inference 

• DEestablishing secure AWS infrastructures using Identity and Access Management (IAM) roles, Lambda functions, or VPC security groups; implementing Natural Language Processing (NLP) model deployment pipelines for text classification and sentiment analysis, using Hugging Face Transformers,PyTorch, or SageMaker; developing automated data validation and anomaly detection scripts, using Python, pandas, or scikit-learn across multi-year datasets; and optimizing SQL queries and model scoring pipelines, using PostgreSQL and AWS Athena

Salary:$149,300.00 - $166,000.00year.

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