{"id":2148810,"url":"https://alion.io/job/cognizant-senior-aiml-lead-developer-remote","title":"Senior AI/ML Lead/ Developer (Remote)","company":{"id":85,"name":"Cognizant","domain":"cognizant.com","url":"https://alion.io/company/cognizant","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Cognizant Careers","truth_index":{"grade":"B","score":84,"open_postings":101,"ghost_share":0,"stale_share":0.832,"repost_share":0,"time_to_fill_p50_days":17,"computed_at":"2026-10-15T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Washington, United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":90000,"max":150000,"currency":"USD","period":"year","gross":null,"usd_annual":150000},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":true,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"FastAPI","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"OpenAI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Time Series Forecasting","optional":false},{"name":"Docker","optional":true},{"name":"Kubernetes","optional":true},{"name":"Pinecone","optional":true},{"name":"Spark","optional":true},{"name":"Weaviate","optional":true}],"status":"live","first_seen_at":"2026-09-24T14:33:15Z","employer_posted_date":"2026-10-09","last_verified_at":"2026-10-15T19:08:40Z","board_verified":true,"closed_at":null,"days_open":21,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":21},"description":"Job Summary\nWe 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.\nThe 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.\nKey Responsibilities\nMachine Learning & Advanced Analytics\nDesign, develop, and deploy advanced machine learning models using Python and PySpark to analyze large-scale financial datasets and generate actionable business insights.\nBuild predictive, classification, clustering, anomaly detection, forecasting, and risk models supporting investment banking and brokerage functions.\nPerform rigorous model validation, back-testing, and experimentation using historical and simulated market data.\nEvaluate and implement appropriate statistical, machine learning, deep learning, and AI techniques based on business requirements and regulatory considerations.\nOptimize model performance through feature engineering, hyperparameter tuning, algorithm enhancements, and distributed computing techniques.\nGenerative AI & Agentic Solutions\nDesign and implement enterprise-grade Generative AI solutions using Azure OpenAI Service.\nBuild and deploy Retrieval-Augmented Generation (RAG) applications leveraging vector databases and knowledge retrieval systems.\nDevelop intelligent agent-based systems using LangChain, LangGraph, and Agentic AI frameworks to automate business workflows and enhance decision support.\nApply Natural Language Processing (NLP), Large Language Models (LLMs), document intelligence, and conversational AI to streamline surveillance, reporting, compliance, and advisory functions.\nEnsure safe, responsible, and governed adoption of Generative AI capabilities across the organization.\nPython Full Stack Development\nDesign and develop scalable backend services and APIs using FastAPI.\nBuild microservices and AI application frameworks that integrate machine learning and GenAI capabilities into enterprise ecosystems.\nDevelop reusable and maintainable software components following modern software engineering best practices.\nImplement API integrations, authentication mechanisms, monitoring, logging, and performance optimization strategies.\nData Engineering & MLOps\nDesign and implement scalable data pipelines and feature engineering workflows using Azure Machine Learning and cloud-native services.\nBuild reusable data products and machine learning components supporting multiple analytics and AI initiatives.\nPartner with Data Engineering teams to operationalize machine learning models and AI applications.\nEstablish model monitoring, retraining strategies, experiment tracking, and lifecycle management processes.\nEnsure solutions are secure, reliable, scalable, and production-ready.\nCloud & Azure AI Platform\nDevelop end-to-end ML and AI solutions using:Azure Machine Learning\nAzure OpenAI Service\nAzure Data Lake\nAzure Databricks\nAzure Storage Services\nAzure DevOps\n\nManage model deployment, monitoring, governance, and operationalization on Azure platforms.\nSupport enterprise-scale AI and analytics workloads while maintaining compliance and security standards.\nBusiness Collaboration\nCollaborate with product owners, business analysts, operations teams, and technology stakeholders to define high-value data science initiatives.\nTranslate complex investment banking and brokerage business challenges into measurable analytical solutions.\nPresent recommendations and analytical findings to both technical and non-technical audiences.\nDrive adoption of AI and machine learning solutions through effective communication and stakeholder engagement.\nGovernance & Responsible AI\nPromote responsible AI practices by evaluating model fairness, explainability, bias, security, and data quality.\nDocument assumptions, risks, methodologies, and limitations in a transparent and accessible manner.\nEnsure adherence to regulatory requirements, model governance frameworks, and enterprise AI policies.\nLeadership & Mentoring\nMentor junior data scientists, machine learning engineers, and developers.\nPromote best practices in software development, experimentation, MLOps, AI engineering, and model governance.\nContribute to a culture of innovation, continuous learning, and technical excellence.\nRequired Qualifications\nTechnical Skills\n8+ years of experience in Data Science, Machine Learning, AI Engineering, or related fields.\nExpert-level proficiency in Python and PySpark for large-scale data processing and model development.\nStrong experience with:FastAPI\nREST APIs\nMicroservices Architecture\nObject-Oriented Programming\nSoftware Engineering Best Practices\n\nHands-on experience with:LangChain\nLangGraph\nRAG Architectures\nAgentic AI Frameworks\nLLM Application Development\n\nStrong expertise in:Azure Machine Learning\nAzure OpenAI Service\nAzure Databricks\nAzure Data Lake\nMLOps and CI/CD Practices\n\nExperience developing and deploying enterprise-grade AI/ML solutions in cloud environments.\nMachine Learning & AI\nDeep understanding of:Supervised Learning\nUnsupervised Learning\nDeep Learning\nEnsemble Methods\nNLP\nTime-Series Forecasting\nAnomaly Detection\nRisk Modeling\n\nStrong understanding of model evaluation, feature engineering, experimentation, validation, and explainability.\nDomain Experience\nPrior experience supporting:Investment Banking\nCapital Markets\nBrokerage Operations\nTrade Surveillance\nRisk Management\nFront Office or Middle Office Functions\n\nUnderstanding of financial products, market data, and regulatory expectations is highly desirable.\nSoft Skills\nExcellent communication and stakeholder management skills.\nAbility to explain complex technical topics to non-technical audiences.\nStrong analytical and problem-solving capabilities.\nExperience working effectively within distributed and hybrid teams.\nPreferred Qualifications\nExperience with vector databases such as Pinecone, Azure AI Search, Weaviate, or ChromaDB.\nKnowledge of containerization technologies including Docker and Kubernetes.\nExperience with CI/CD pipelines and DevOps practices.\nExposure to Responsible AI, Model Risk Management, and AI governance frameworks.\nAzure certifications in AI, Data Science, or Machine Learning.\n\"Please note, this role is not able to offer visa transfer or sponsorship now or in the future.\"\nWe'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.\nSalary and Other Compensation:\nApplications will be accepted until Sept 07, 2026,\nThe annual salary for this position is between $ 90,000 - $ 150,000 depending on experience and other qualifications of the successful candidate.\nThis position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.\nBenefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:\nMedical/Dental/Vision/Life Insurance\nPaid holidays plus Paid Time Off\n 401(k) plan and contributions\nLong-term/Short-term Disability\nPaid Parental Leave\nEmployee Stock Purchase Plan\nDisclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. 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