Job Summary
We are seeking a highly skilled and innovative Senior AI/ML Engineer with strong expertise in Python, PySpark, Azure Machine Learning, Generative AI, and Full Stack Development to design and deliver advanced analytics and AI-driven solutions for global investment banking and brokerage operations.
The ideal candidate will combine deep technical expertise in machine learning, distributed computing, cloud-native AI platforms, and modern AI frameworks such as LangChain, LangGraph, RAG, Agentic AI Frameworks, FastAPI, and Azure OpenAI Service. This role requires close collaboration with business stakeholders to transform complex financial data into actionable insights that improve decision-making, reduce operational risk, and enhance operational efficiency.
Key Responsibilities
Machine Learning & Advanced Analytics
- Design, develop, and deploy advanced machine learning models using Python and PySpark to analyze large-scale financial datasets and generate actionable business insights.
- Build predictive, classification, clustering, anomaly detection, forecasting, and risk models supporting investment banking and brokerage functions.
- Perform rigorous model validation, back-testing, and experimentation using historical and simulated market data.
- Evaluate and implement appropriate statistical, machine learning, deep learning, and AI techniques based on business requirements and regulatory considerations.
- Optimize model performance through feature engineering, hyperparameter tuning, algorithm enhancements, and distributed computing techniques.
Generative AI & Agentic Solutions
- Design and implement enterprise-grade Generative AI solutions using Azure OpenAI Service.
- Build and deploy Retrieval-Augmented Generation (RAG) applications leveraging vector databases and knowledge retrieval systems.
- Develop intelligent agent-based systems using LangChain, LangGraph, and Agentic AI frameworks to automate business workflows and enhance decision support.
- Apply Natural Language Processing (NLP), Large Language Models (LLMs), document intelligence, and conversational AI to streamline surveillance, reporting, compliance, and advisory functions.
- Ensure safe, responsible, and governed adoption of Generative AI capabilities across the organization.
Python Full Stack Development
- Design and develop scalable backend services and APIs using FastAPI.
- Build microservices and AI application frameworks that integrate machine learning and GenAI capabilities into enterprise ecosystems.
- Develop reusable and maintainable software components following modern software engineering best practices.
- Implement API integrations, authentication mechanisms, monitoring, logging, and performance optimization strategies.
Data Engineering & MLOps
- Design and implement scalable data pipelines and feature engineering workflows using Azure Machine Learning and cloud-native services.
- Build reusable data products and machine learning components supporting multiple analytics and AI initiatives.
- Partner with Data Engineering teams to operationalize machine learning models and AI applications.
- Establish model monitoring, retraining strategies, experiment tracking, and lifecycle management processes.
- Ensure solutions are secure, reliable, scalable, and production-ready.
Cloud & Azure AI Platform
- Develop end-to-end ML and AI solutions using:
- Azure Machine Learning
- Azure OpenAI Service
- Azure Data Lake
- Azure Databricks
- Azure Storage Services
- Azure DevOps
- Manage model deployment, monitoring, governance, and operationalization on Azure platforms.
- Support enterprise-scale AI and analytics workloads while maintaining compliance and security standards.
Business Collaboration
- Collaborate with product owners, business analysts, operations teams, and technology stakeholders to define high-value data science initiatives.
- Translate complex investment banking and brokerage business challenges into measurable analytical solutions.
- Present recommendations and analytical findings to both technical and non-technical audiences.
- Drive adoption of AI and machine learning solutions through effective communication and stakeholder engagement.
Governance & Responsible AI
- Promote responsible AI practices by evaluating model fairness, explainability, bias, security, and data quality.
- Document assumptions, risks, methodologies, and limitations in a transparent and accessible manner.
- Ensure adherence to regulatory requirements, model governance frameworks, and enterprise AI policies.
Leadership & Mentoring
- Mentor junior data scientists, machine learning engineers, and developers.
- Promote best practices in software development, experimentation, MLOps, AI engineering, and model governance.
- Contribute to a culture of innovation, continuous learning, and technical excellence.
Required Qualifications
Technical Skills
- 8+ years of experience in Data Science, Machine Learning, AI Engineering, or related fields.
- Expert-level proficiency in Python and PySpark for large-scale data processing and model development.
- Strong experience with:
- FastAPI
- REST APIs
- Microservices Architecture
- Object-Oriented Programming
- Software Engineering Best Practices
- Hands-on experience with:
- LangChain
- LangGraph
- RAG Architectures
- Agentic AI Frameworks
- LLM Application Development
- Strong expertise in:
- Azure Machine Learning
- Azure OpenAI Service
- Azure Databricks
- Azure Data Lake
- MLOps and CI/CD Practices
- Experience developing and deploying enterprise-grade AI/ML solutions in cloud environments.
Machine Learning & AI
- Deep understanding of:
- Supervised Learning
- Unsupervised Learning
- Deep Learning
- Ensemble Methods
- NLP
- Time-Series Forecasting
- Anomaly Detection
- Risk Modeling
- Strong understanding of model evaluation, feature engineering, experimentation, validation, and explainability.
Domain Experience
- Prior experience supporting:
- Investment Banking
- Capital Markets
- Brokerage Operations
- Trade Surveillance
- Risk Management
- Front Office or Middle Office Functions
- Understanding of financial products, market data, and regulatory expectations is highly desirable.
Soft Skills
- Excellent communication and stakeholder management skills.
- Ability to explain complex technical topics to non-technical audiences.
- Strong analytical and problem-solving capabilities.
- Experience working effectively within distributed and hybrid teams.
Preferred Qualifications
- Experience with vector databases such as Pinecone, Azure AI Search, Weaviate, or ChromaDB.
- Knowledge of containerization technologies including Docker and Kubernetes.
- Experience with CI/CD pipelines and DevOps practices.
- Exposure to Responsible AI, Model Risk Management, and AI governance frameworks.
- Azure certifications in AI, Data Science, or Machine Learning.
*Please note this role is not able to offer visa transfer or sponsorship now or in the future*
We're excited to meet people who share our mission and who can make an impact in a variety of ways. Don't hesitate to apply—even if you only meet the minimum requirements. Think about your transferable experiences and unique skills that make you stand out.
Salary and Other Compensation:
Applications will be accepted until Sept 07, 2026,
The annual salary for this position is between $ 90,000 - $ 150,000 depending on experience and other qualifications of the successful candidate.
This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
- Medical/Dental/Vision/Life Insurance
- Paid holidays plus Paid Time Off
- 401(k) plan and contributions
- Long-term/Short-term Disability
- Paid Parental Leave
- Employee Stock Purchase Plan
Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
コグニザントについて
コグニザント（NASDAQ: CTSH）は、AI Builderおよびテクノロジーサービスプロバイダーとして、お客様にフルスタックのAIソリューションを構築することで、AI投資と企業価値を結ぶ架け橋となっています。業界、ビジネスプロセス、エンジニアリングに関する当社の深い専門知識を活かし、組織固有のビジネス環境をテクノロジー・システムに組み込みます。これにより、人間の可能性を最大限に引き出し、確かな成果を実現するとともに、急速に変化する世界においてグローバル企業が常に一歩先を行くための支援を行っています。 詳細については、cognizant.ai をご覧ください。
雇用に関する追加情報
本募集に記載されている報酬情報は、掲載日時点で正確なものです。Cognizantは、適用される法令に従い、いつでも本情報を変更する権利を留保します。
応募者は、対面またはビデオ会議による面接への参加を求められる場合があります。また、各面接の際に、現在有効な州政府または政府発行の身分証明書の提示を求められる場合があります。
Cognizantは機会均等雇用主です。応募および選考において、人種、肌の色、性別、宗教、信条、性的指向、性自認、国籍、障がい、遺伝情報、妊娠、退役軍人の地位、その他連邦法・州法・地方自治体の法律により保護されるいかなる特性に基づく差別も行いません。
