Top Python Developer Jobs in Delhi

Architect, build, and operate end-to-end AI automation systems: CLI frameworks, MCP servers, agent tooling, production pipelines, evaluation and monitoring. Own prompt and context engineering, multi-agent orchestration, integration with external tools, governance, and metrics to measure automation and business impact.

Design, develop, and deliver UiPath automation solutions (POCs to production). Gather and document process requirements with SMEs, participate in design sessions, and support mentoring of junior developers. Follow WonderBotz standards and best practices for RPA implementations.

Principal Data Engineer responsible for building big-data solutions using PySpark and Databricks, writing and optimizing SQL, developing Python pipelines, and working with Hadoop/Hive, Git, Airflow/Dagster, and Azure.

Customer-facing AI Engineer who designs, builds, and deploys production-grade LLM and agent-based solutions. Responsibilities include architecting agent systems, implementing RAG pipelines, integrating with platform signals and vector DBs, overseeing end-to-end ML lifecycle, writing clean Python code, and collaborating with customers and internal teams to ensure scalable, monitored deployments.

Lead the development of AI/ML solutions, providing technical leadership and driving project frameworks from ideation to deployment, while collaborating with various teams to overcome challenges and ensure best practices.

As an Engineering Manager, you'll lead a team of engineers, providing technical guidance, strategy, and project management to develop solutions that prevent cyber breaches.

The role involves designing and building bespoke financial valuation models, ensuring analytical depth and accuracy, while integrating them into scalable frameworks using advanced modeling techniques.

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.

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 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.

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

Lead verification for complex CPU/SoC IP and subsystems: define verification strategies and test plans, build verification environments, run and debug simulations/emulations, apply random-stimulus and coverage-driven techniques, and mentor engineers while improving verification methodologies and tools.

Build and maintain cloud infrastructure, CI/CD pipelines, containerized workloads, and infrastructure-as-code systems on AWS. Manage production databases, monitoring, logging, observability, version control workflows, and deployment infrastructure. Support mobile release pipelines and optimize infrastructure costs as needed. The role is remote within Europe and involves collaborating with a small consumer AI platform team.

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 delivery of scoped software features and models for scalable web and membership-experience platforms. Designs, develops, tests, debugs, and maintains reliable software using Java, Python, Node.js, APIs, CI/CD, automated testing, and AI/ML integrations. Collaborates with stakeholders, conducts code reviews, monitors performance, translates requirements into technical solutions, supports production systems, mentors peers, and promotes engineering excellence and continuous improvement.

Leads architecture and development of large-scale batch and real-time data platforms and pipelines. Ensures data quality, governance, reliability, observability, scalability, and cost efficiency while building self-service capabilities. Supports analytics, machine learning, and generative AI teams with trusted data infrastructure. Establishes engineering standards, mentors engineers, and drives platform health across multiple teams. The role requires expertise in data integration, distributed processing, data modeling, cloud platforms, CI/CD, and infrastructure automation.

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.

Lead architecture and design of cloud-native, carrier-grade telecom applications using Kubernetes and Java. Translate business requirements into scalable solutions, implement Helm-based deployments, optimize performance and reliability, support cloud/virtualized/bare-metal deployments, guide Agile development, and collaborate with product, engineering, and customer teams.