Top Python Developer Jobs in Delhi

Develop and enhance features for EnrollWise, contribute to a scalable software architecture, review code, collaborate on design and technical feasibility, and maintain software quality.

The Site Reliability Engineer will monitor and ensure the reliability and performance of platforms using ELK and TICK stacks, bridging development and operations.

The AI QA Specialist will design and execute test strategies for AI systems, validate model outputs, implement monitoring dashboards, and ensure compliance with safety standards.

The Lead BigQuery / Graph DBA will design and optimize cloud-native data warehouses and graph databases, focusing on performance, integration with AI, and data governance.

The MDM Specialist will design and implement master data management solutions, integrate AI workflows, and ensure data governance and quality across customer and vendor domains.

Design and implement production-grade AI models and algorithms, lead AI initiatives across organizations, enhance Agentic AI capabilities, and collaborate with teams to develop high-impact AI features.

The DevOps Engineer will enhance software development and IT operations, focusing on automating processes, managing cloud infrastructure, and implementing CI/CD pipelines.

Lead and mentor a team of data analysts to design and implement analytics strategies, delivering insights and overseeing data accuracy and compliance.

Administer and govern the Snowflake-centered data platform and related tools (Databricks, Fivetran, dbt, Airflow, Monte Carlo). Optimize performance, implement data security (dynamic masking, RLS, SSO/SAML), automate operations with Python/SQL, monitor costs and resource usage, and optionally manage Tableau Cloud.

Lead and mentor a team of data scientists, overseeing ML initiatives and driving business impact through effective data science practices.

The Senior Data Scientist will lead ML initiatives, develop production-grade data science solutions, mentor junior team members, and collaborate with stakeholders to address complex problems.

The Senior Data Engineer will design and build data infrastructure and pipelines, enhance AI capabilities, and collaborate with teams on data solutions while mentoring junior engineers.

The Data Architect will design and implement data infrastructure, collaborating with teams to enhance data usage for analytics, automation, and AI, while ensuring compliance and governance.

Join Kroll as a Data Scientist to build and evaluate ML models, supporting deployment and monitoring, while collaborating with experienced teams in financial services and data integrity challenges.

The Application Development Analyst develops and maintains features within SaaS platforms, integrates systems, automates workflows, and improves efficiency.

Leads enterprise security architecture strategy and complex cross-functional initiatives involving Zero Trust, IAM, multi-cloud security, network and application segmentation, AI security, data protection, and cyber resiliency. Advises executives and stakeholders on security roadmaps, supplier risks, M&A due diligence, regulatory matters, and vulnerability remediation. Designs and validates security solutions, promotes automation and innovation, and delivers security transformations across a global organization.

Leads the architecture, development, deployment, and operation of scalable AI infrastructure, distributed systems, real-time data platforms, microservices, and agentic AI solutions. Defines technical vision, builds resilient and observable production services, processes high-volume network data, mentors engineers, and drives engineering excellence across intelligent networking and automation platforms.

Design, build, test, deploy, and maintain platform tools, APIs, services, and workflows to enable front-office quant research. Collaborate with researchers, portfolio managers, and engineers to translate requirements into scalable, reliable, secure solutions and improve platform usability and adoption.

Build end-to-end software features across frontend, backend, and AI components. Responsibilities include developing interfaces, APIs, backend services, data pipelines, automation workflows, and LLM-powered applications such as RAG systems and AI agents. The role involves testing, documentation, debugging, cross-functional collaboration, product iteration, and using AI coding tools to improve development speed and quality.

Design, deploy, and manage AWS and Azure cloud infrastructure, implement CI/CD automation, monitor and optimize performance and costs, enforce security and governance, build serverless solutions, troubleshoot cross-team issues, and maintain documentation and best practices.

Leads the launch of ElevenLabs in India by winning strategic customers, hiring and managing forward-deployed engineering teams, identifying AI use cases, architecting bespoke integrations, building demos, and delivering end-to-end customer projects. The role engages technical and executive stakeholders, guides AI implementation, presents solutions, and partners with Research and Product teams to incorporate market insights into products and models.

Develop and maintain reliable data pipelines, ELT processes, workflow orchestration, custom data connectors, and CI/CD pipelines using Airflow, Python, PySpark, Hive/Trino, SQL, and Snowflake. Collaborate with cross-functional teams, monitor and troubleshoot data workflows, validate and test data, document technical processes, and support data governance.

Build and deploy full-stack AI applications integrating LLMs, RAG architectures, vector databases, and multi-agent systems. Develop Python backends, APIs, ingestion pipelines, responsive interfaces, and real-time dashboards. Design and optimize PostgreSQL databases, containerize applications with Docker and Kubernetes, manage AWS and GPU infrastructure, and operate Linux environments. Mentor developers, conduct demonstrations, evaluate emerging AI technologies, and improve reliability through testing, debugging, performance tuning, and quality processes.

Leads the architecture and delivery of production-grade agentic and generative AI systems, including LLM agents, RAG pipelines, multi-agent workflows, and scalable cloud applications. Guides technical architecture, production engineering, LLMOps, evaluation, observability, security, and responsible AI practices. Mentors AI/ML and backend engineers, conducts design and code reviews, and collaborates with product, data, platform, security, compliance, and executive stakeholders.

Participate in structured SAP training covering S/4HANA, business processes, configuration concepts, testing, documentation, and troubleshooting. Assist senior consultants with requirements gathering, issue tracking, process analysis, and project scenarios. Develop functional or technical expertise across SAP areas such as FICO, MM, SD, ABAP, Basis, BTP, and SuccessFactors, with mentorship and preparation for entry-level SAP consulting roles.