Top Python Developer Jobs in Delhi

Support reliability, monitoring, and modernization of Kubernetes-based microservices platforms. Build Datadog observability solutions including dashboards, alerts, APM, metrics, logs, and tracing; integrate tooling with AWS and CI/CD pipelines; automate operational tasks with Python; manage agents, integrations, API keys, and access controls; and lead platform maintenance and improvements for reliability, scalability, and performance.

The Full Stack Engineer will manage carrier integrations, act as a forward deployed engineer for top accounts, and resolve bug backlogs, ensuring smooth operations and customer satisfaction.

Lead a regional follow-the-sun DevSecOps pod, drive ASPM integrations and AI-enabled secure code scanning, perform secure code reviews and infrastructure architecture guidance, own technical escalations, facilitate cross-timezone shift hand-offs, mentor engineers, and ensure 24/7 delivery velocity and system security in a regulated enterprise environment.

Designs, builds, and supports scalable cloud data platforms across Azure and AWS. Leads Databricks-based ETL/ELT pipelines, lakehouse architecture, data transformation, API integrations, automation, monitoring, CI/CD, and Infrastructure as Code. Partners with architecture, security, FinOps, analytics, and business teams to deliver secure, governed, reliable, and cost-effective solutions. Provides technical leadership, establishes engineering standards, mentors engineers, and resolves complex data, integration, and platform issues.

Build, support, and maintain scalable cloud data platforms across Azure and AWS. Develop Databricks, Spark, PySpark, SQL, Python, ETL/ELT, and REST API ingestion pipelines. Monitor and troubleshoot cloud integrations, apply security and governance standards, and improve reliability and cost efficiency. Collaborate with architecture, security, FinOps, analytics, and business teams to deliver trusted data for reporting, AI, and operational decisions.

The Tech Lead will oversee integration and automation projects, convert functional requirements into technical specifications, and guide the development team in delivering solutions on time.

Administer and oversee IBM z/OS and associated subsystems, including CICS, Db2, RACF, storage, security, monitoring, and performance management. Lead software installations, upgrades, SMP/E maintenance, incident resolution, automation, compliance, and operational standards across global deployments. Coordinate managed service providers and partner with engineering, security, and application teams on modernization, CI/CD, APIs, z/OS Connect, and hybrid-cloud initiatives. Participate in 24x7 on-call support and AIOps-driven monitoring improvements.

Build and operate resilient IAM authentication platforms across AWS, Azure, Active Directory, and Entra ID. Develop infrastructure-as-code, CI/CD pipelines, cloud automation, monitoring, security improvements, self-healing capabilities, and cost optimization solutions. Provide operational support for hybrid and multi-cloud environments while using PowerShell and Python to automate deployments and platform management.

Senior Analyst responsible for designing and optimising data pipelines and models, extracting and transforming data using SQL and Python, working with Databricks/PySpark, supporting business analytics and AI initiatives, and engaging stakeholders to deliver data solutions within financial services.

The Tech Lead will oversee integration and automation solutions, create technical specifications, guide the tech team, ensure timely delivery, and support impact analysis on systems.

The Senior Staff Software Engineer will lead the architecture of the agentic platform, define shared service designs, partner with teams for reusable capabilities, provide technical leadership, and implement cost-management and evaluation pipelines.

As a Staff Software Engineer, you will develop backend services for the agentic platform, integrating AI capabilities and ensuring system reliability, security, and developer usability.

Assist Kroll's valuation practice by analyzing illiquid and structured alternative assets. Review investment documents, gather client data, build DCF/market/option pricing models, compute financial ratios, prepare reports and presentations, support client relationships, and attend industry events. Gain exposure to bespoke investment structures and industry professionals.

Lead and grow the India engineering team (initially 5 engineers) across product, SRE, and InfoSec; own technical roadmap, drive scalable secure systems, mentor and hire, partner with US product and data teams, and implement engineering best practices for reliability and incident response.

Lead architecture and delivery of enterprise Generative AI solutions: design LLM-based RAG pipelines, multi-agent systems, and secure cloud deployments; establish LLMOps best practices; advise clients, run PoCs, and mentor engineering teams to operationalize scalable, compliant AI systems.

Build and maintain dbt data models and tested SQL transformations, create dashboards and reports, write Python automation, follow Git/GitHub CI/CD workflows, monitor data quality, and partner with stakeholders to deliver trusted business metrics.

Operate and automate production infrastructure, respond to on-call incidents, improve monitoring and deployments, build scalable cloud-native systems, debug production issues, and plan infrastructure growth using config management, containers, and orchestration.

Build and maintain automation tooling converting SOPs into automation routines. Optimize systems and cloud management across Windows and Linux at scale, manage public cloud services, networking, databases, container orchestration, CI/CD pipelines, provide level-3 support runbooks, and participate in on-call rotations within an Agile, global environment.

Leads data architecture, measurement design, monitoring, dashboards, validation, reconciliation, privacy, access control, lineage, and executive reporting for public-sector AI engagements. Establishes reusable architectures and indicator frameworks, ensures systems remain trustworthy after launch, and mentors analysts. Requires substantial data engineering or analytics experience, government programme exposure, production SQL and Python, cloud platform ownership, and the ability to defend metrics with senior decision-makers.

The Data Manager oversees the environmental data lifecycle, ensuring data integrity from collection to reporting, while managing compliance and quality assurance for environmental standards.

Build and own frontend features for student- and educator-facing web applications using React, Next.js, TypeScript, and GraphQL. Responsibilities include component architecture, API integration, testing, performance optimization, accessibility, security, production monitoring, and staged delivery. The engineer will also contribute to AI-powered learning experiences, shared components, observability, and backend/API changes as needed, while collaborating with Product, Design, Backend, and Content Operations.

Design and implement a unified orchestration layer coordinating vendor and internal LLMs and human agents. Build production-grade Python services, drive ML projects from design to delivery, ensure secure, scalable AI-enabled customer experiences, and collaborate across teams to meet security, compliance, and performance standards.

Conduct applied research on voice-agent evaluation and self-improvement: design audio-native metrics and adversarial datasets, build observability and tracing for cascade failures, mine production traces to generate fine-tuning or prompt fixes, and validate improvements under adversarial replay. Collaborate to ship solutions and publish research.

Manage and validate environmental data in EQuIS, perform data migration and QA/QC, configure EQuIS workflows, develop Power BI dashboards, support project teams and labs, and produce documentation, SOPs, and standardized data management processes.

Senior business analyst liaison for Financial Crime data delivery: analyze complex data sets, perform data profiling and source-to-target mapping, translate business needs into technical requirements, prioritize backlog, support development and testing (UAT/BVT), investigate incidents and drive resolution.