Jobs at Fractal

Design, develop, and maintain scalable AWS data pipelines and ETL processes. Manage and optimize Redshift, PostgreSQL, and Oracle databases; write efficient SQL and Python/PySpark scripts; and use Informatica PowerCenter. Ensure data quality, collaborate with cross-functional teams, and support data warehousing solutions. Preferred experience includes Jenkins, SVN, Postman, Agile methodologies, and data warehousing best practices.

Design and deliver production-grade Generative AI and LLM solutions, including RAG pipelines, agentic workflows, APIs, and reusable frameworks. Build, train, fine-tune, evaluate, and optimize AI systems for accuracy, latency, cost, reliability, and safety. Translate business needs into measurable AI outcomes, collaborate with technical and business stakeholders, contribute to architecture and proposals, and mentor junior team members.

Provides L3 production support for GCP-based data platforms and pipelines, resolving complex incidents, performing root cause analysis, supporting enhancements, and improving automation, monitoring, and reliability. Requires expertise with Dataproc, BigQuery, Spark, Hive, Airflow, Python, Scala, and Bash. The role includes on-call support, mentoring L1/L2 teams, maintaining operational documentation, and collaborating on data platform performance, security, and scalability improvements.

Analyze and optimize marketing campaign ROI across channels, evaluate app and partner data, conduct funnel, cohort, attribution, and retention analyses, and develop actionable recommendations. The role requires Marketing Mix Modeling, Multi-Touch Attribution, forecasting, segmentation, and statistical analysis. The consultant will collaborate with product, analytics, engineering, and marketing stakeholders to define measurement strategies, build reporting mechanisms, and translate complex data into business insights that improve adoption, retention, revenue, and campaign effectiveness.

Leads enterprise-wide GenAI transformation programs from strategy and use-case prioritization through deployment, scaling, governance, and value realization. Partners with executives, business teams, data scientists, AI engineers, architects, security, and operations to deliver AI, analytics, automation, and data initiatives. Responsibilities include program governance, roadmaps, budgeting, risk management, solution planning, testing, compliance, adoption, change management, executive reporting, and capability building.

Leads Fractal’s Azure practice, including strategy, team management, client engagement, service delivery, technical direction, budgeting, and business development. Drives Azure-based Generative AI and Agentic AI strategies, architectures, governance, accelerators, and enterprise implementations. Partners with Microsoft and clients to identify transformation opportunities, shape proposals, deliver executive presentations, and build organizational AI capabilities through innovation programs and training.

Lead the end-to-end development, deployment, and maintenance of production-grade AI solutions. Design agentic AI systems with tool integrations, orchestration frameworks, and multi-step reasoning workflows. Develop LLM-based solutions using prompt engineering, evaluation, and monitoring practices. Build scalable automation applications with Python and AWS, while establishing and maintaining CI/CD pipelines for reliable deployment and continuous improvement.

Design, build, monitor, and optimize scalable data pipelines, models, and cloud data infrastructure. Integrate diverse data sources, implement quality and governance processes, automate deployments and testing, troubleshoot reliability issues, and document solutions. Collaborate with analysts, data scientists, and stakeholders to support analytics, reporting, and machine learning initiatives. Participate in rotating out-of-office on-call support.

Design and deliver scalable Generative AI solutions using LLMs, RAG, AI agents, vector databases, and multimodal models. Lead cloud, MLOps, security, governance, and architecture strategies across AWS, Azure, and Google Cloud. Translate business needs into technical solutions, support client workshops and pre-sales, present strategies to executives, and mentor data science, ML engineering, and software teams.

Design and lead scalable Generative AI solutions using LLMs, RAG, AI agents, vector databases, cloud platforms, and MLOps/LLMOps. Translate business needs into secure technical architectures, conduct client workshops, support pre-sales, and present AI strategies to executives. Establish governance, security, monitoring, and compliance frameworks while mentoring data scientists, ML engineers, and software teams. Evaluate emerging technologies, guide implementation approaches, and drive enterprise AI adoption.

Owns end-to-end delivery of generative AI solutions, including LLMs, RAG, and AI agents, for BFSI applications. Translates business needs into AI product roadmaps and technical requirements, coordinates business, data science, and engineering teams, and leads AWS deployments. Defines success metrics and monitors model performance, adoption, governance, compliance, and business outcomes while staying current with agentic AI and enterprise AI platforms.

Establish and operationalize enterprise AI governance for a financial services organization. Responsibilities include defining governance frameworks, building an AI Registry, governing AI agents and applications, designing evaluation and testing methodologies, establishing architecture and risk controls, ensuring regulatory compliance, and leading stakeholder adoption. The role requires expertise in AI governance, responsible AI, enterprise architecture, cloud platforms, model risk, agentic AI, and financial services regulations.

Develop and maintain demand forecasts across products, markets, customers, and channels. Analyze sales, inventory, promotions, seasonality, and market trends; investigate forecast performance and root causes; support product launches, lifecycle planning, and S&OP. Create reports and dashboards using Excel, SQL, Power BI, or Tableau, maintain planning data in ERP/MRP systems, and collaborate with Sales, Marketing, Supply Planning, Finance, and Analytics teams.

Leads Azure solution architecture for complex data platforms, translating business requirements into scalable technical designs. Designs data models, integrations, provisioning interfaces, CI/CD pipelines, monitoring, and MLOps solutions. Advises clients on Azure services, cost optimization, platform strategy, and enterprise adoption while overseeing delivery standards, estimates, RFP responses, and stakeholder collaboration. Requires extensive software development, data engineering, Azure, dbt, Data Vault, Python, Spark, and analytics experience.

Senior Test Engineer responsible for manual and automated functional, integration, and regression testing for a Card Management System. Duties include translating requirements into test scenarios, configuring systems, validating releases, tracking defects, supporting deployments, troubleshooting issues, and improving testing processes. The role collaborates with business, product, development, and operations stakeholders in Agile delivery environments, with TOSCA experience and financial services knowledge highly valued.

Lead business analysis for insurance transformation and system migration initiatives. Assess impacts across data, processes, workflows, and reconciliation requirements; align stakeholders across underwriting, pricing, operations, product, digital, and data teams; identify risks and dependencies; develop target-state solutions; prepare executive-ready options papers and presentations; and translate business needs into actionable requirements.

Lead the engineering side of an agentic AI invoice-to-cash product, owning architecture, front end, services, data, infrastructure, platform decisions, delivery, quality, CI/CD, releases, and incident response. Manage and coach engineers while contributing code to complex areas. Partner with AI leadership and product management on system interfaces, feasibility, sequencing, trade-offs, and roadmap execution.

Develops GenAI and NLP models for text classification, sentiment analysis, entity recognition, translation, and semantic analysis. Responsibilities include text preprocessing, feature engineering, model training and evaluation, exploratory data analysis, algorithm optimization, and large-scale data processing. The role collaborates with engineering and domain teams to integrate NLP solutions, documents methodologies, and applies current machine learning advances to business problems.

Develop and maintain Power BI dashboards, reports, data models, KPIs, and executive scorecards using SQL and healthcare claims data. Analyze trends, anomalies, savings opportunities, compliance risks, and Payment Integrity performance. Partner with business, compliance, clinical, and technology stakeholders to translate requirements into scalable regulatory and operational analytics solutions. Ensure data quality, governance, and reporting consistency while supporting forecasting, root cause analysis, and AI-enabled analytics initiatives.

Develops end-to-end generative AI and NLP solutions using LLMs, including chatbots, search, summarization, Document AI, and content generation. Conducts research, builds supporting libraries and frameworks, and applies prompt engineering, fine-tuning, vector databases, and cloud AI services. May also work with computer vision, audio, and video models. Collaborates cross-functionally throughout the software development lifecycle, contributing to design, testing, deployment, maintenance, code reviews, and technical roadmaps.