Top Tech Jobs & Startup Jobs in Delhi

Evaluate generative AI systems, RAG pipelines, and agents using Python-based frameworks and evaluation platforms. Responsibilities include model and agent quality assessment, Responsible AI validation, RAI metrics reporting, golden and synthetic dataset creation, and establishing AI observability and tracing with OpenTelemetry.

Develop, configure, and support RSA Archer GRC solutions, including applications, workflows, data feeds, dashboards, reports, integrations, and automation. Translate business and compliance requirements into scalable technical solutions, troubleshoot issues, migrate packages across development environments, and prepare technical documentation. Collaborate with cross-functional stakeholders on enhancements involving risk, compliance, audit, and information security processes.

Develop, enhance, and maintain Tungsten platform features, modules, and integrations. Translate business requirements into scalable technical solutions, write maintainable full-stack code, troubleshoot complex issues, and ensure stability through testing and automation. Optimize performance, security, and user experience while collaborating with product owners in Agile environments. The role also involves enterprise SaaS, workflow, rules engine, document processing, cloud, API, and third-party system integration work.

Provides technical leadership for Dynamics 365 CE and Power Platform development. Leads and mentors developers, defines solution architectures, designs data models and integrations, enforces Microsoft best practices and TDD, and oversees secure, scalable delivery. Collaborates with business analysts, product owners, and subject matter experts to clarify requirements, leads technical workshops, evaluates emerging technologies, and supports DevOps, CI/CD, and ALM pipelines using Azure DevOps.

Leads infrastructure solution architecture and account management for presales engagements, including RFIs, RFPs, proposals, solution estimation, pricing, presentations, and customer meetings. Manages large bids through contracting and transition, while driving cross-selling, upselling, revenue, gross margin, forecasting, account planning, resource allocation, and pipeline management. Requires expertise in Digital Workplace, End User Computing, Hybrid Cloud, infrastructure managed services, and cross-functional coordination.

Leads BI engineering migration from SAS to Dataform on Google Cloud. Responsibilities include developing advanced SQL, migrating reporting workflows, analyzing requirements, managing stakeholders, and applying extensive BI and data engineering expertise.

Lead enterprise architecture strategy for a global financial institution. Review fraud-domain application portfolios, assess architecture options and build-versus-buy decisions, conduct rationalization assessments, define target-state “north star” architectures, and create estimates, roadmaps, and transition architecture diagrams. Serve as a technical authority while translating complex business challenges into scalable solutions and collaborating with technical and business stakeholders.

Lead the conversion of BI reporting and data engineering workflows from SAS to Dataform on Google Cloud. Responsibilities include advanced SQL development, reporting migration, requirements analysis, stakeholder management, and leveraging extensive BI and data engineering experience.

Lead the design, development, and maintenance of enterprise Power BI dashboards, reports, and semantic models. Partner with business stakeholders and data engineers to define requirements, validate data, optimize DAX and data models, support data quality and governance, and participate in UAT and production deployments across Microsoft Fabric and Azure data platforms.

Designs scalable conceptual, logical, and physical data models and implements Data Vault architectures for enterprise data lakes and lakehouses. Collaborates with stakeholders, data engineers, data scientists, and analysts to translate requirements into data solutions. Deploys and optimizes models using Azure data services, ensures security and compliance, documents data flows, and integrates disparate data sources for historical tracking and scalable performance.