Top Python Developer Jobs in Delhi

Design and build reinforcement-learning training environments and diverse tasks to evaluate and improve LLM agents; iterate rapidly on task designs from customer feedback, deliver high-quality outputs with minimal supervision, and maintain PST overlap for collaboration.

Create realistic computer-use tasks for AI agents on Linux desktops. Responsibilities include designing multi-step scenarios, preparing files and documents, writing agent instructions, developing Python setup and scoring scripts, testing environments, and documenting tasks. Requires Python, daily AI tool usage, basic AI/ML experience, Ubuntu and virtual machine familiarity, attention to detail, and Git basics. Experience building RL environments or computer-use benchmarks is preferred.

Conduct quantitative research on low-GHG renewable fuels for marine and aviation sectors, including cost, lifecycle emissions, and availability analyses. Develop technical reports, policy briefs, figures, and recommendations for policymakers, industry, and other stakeholders. Present findings, support outreach events, and collaborate with global research teams and external partners. The role focuses on Indian and international fuels policies and requires strong analytical, communication, and research capabilities.

Mentor high school students on STEM research, computational projects, engineering prototypes, competitions, and publications. Responsibilities include refining research ideas, supporting programming, debugging, data analysis, modeling, simulations, literature reviews, technical writing, and presentations. The mentor also identifies STEM opportunities, reviews application materials, develops workshops and resources, and aligns student projects with broader university application strategies.

Own end-to-end data engineering and BI delivery, including scalable ETL/ELT pipelines, data quality, Power BI semantic models, reports, dashboards, and recurring data processes. Maintain Synapse and Power BI tooling, support production incidents, ensure governance and reliability, and partner with stakeholders on trusted datasets. Enable self-service analytics and natural-language data access through AI. The role requires strong SQL, Azure, Power BI, and regulated-industry experience.

Design, build, and maintain automated and exploratory tests for web and mobile apps. Create test plans, UI/API automation, compatibility and performance testing, perform root-cause analysis, improve test coverage, and develop testing tools and infrastructure to ensure product stability and user-focused quality.

Design and evaluate ASIC/FPGA chip-design workflows spanning RTL development, verification, synthesis, physical design, timing closure, and sign-off. Create reference implementations, testbenches, constraints, grading criteria, and EDA environments for assessing AI-generated designs. Diagnose functional, coverage, timing, power, performance, and area issues, automate evaluation flows, identify recurring AI-agent failures, and document methodologies while collaborating with engineering and research teams.

The Senior Finance Planning Analyst analyzes financial and operational data, develops dashboards and self-service reporting, supports budgeting and forecasting, and provides financial modeling and variance analysis. The role partners with Accounting, Sales Operations, HR, IT, BI, and Data Engineering teams to integrate ERP and business-system data, improve FP&A tools, automate reporting, and deliver actionable insights to leadership.

Build and maintain scalable data platforms, including Airflow ingestion pipelines, Kafka streaming, Spark workloads, data lakes, and database solutions. Develop secure, containerized applications for air-gapped environments; optimize ingestion, queries, and production performance. Ensure data quality, lineage, observability, and SLA compliance while translating customer needs into data products. Create documentation and operational runbooks, troubleshoot production issues, and collaborate with engineers, analysts, and business stakeholders.

Designs and delivers end-to-end automation solutions for Lilly’s global Finance organization. Responsibilities include assessing opportunities, developing and testing software, creating architecture and test documentation, supporting UAT and integrations, troubleshooting production issues, resolving defects, and assisting with QA, audits, migrations, and risk mitigation. The role uses Python, PySpark, TypeScript, PostgreSQL, AWS, Microsoft Fabric, SAP, and other APIs, while collaborating with finance, technology, analyst, and business teams.

Lead and mentor a cross-functional engineering team while designing, building, deploying, and monitoring scalable distributed systems. Drive DevOps ownership, automated testing, reliability, performance, observability, and frequent software releases. Partner with Product, Data, and Platform teams on architecture and technical strategy, evaluate trade-offs, improve engineering practices, and apply AI to accelerate software development.

Build and operate AI-native backend services in Python, integrating LLMs, agents, tool calls, vision models, and document intelligence pipelines. Productionize AI prototypes with guardrails, fallbacks, caching, testing, monitoring, observability, and evaluations. Design scalable async and event-driven systems while managing latency and token costs. Own services end to end across distributed systems, databases, cloud infrastructure, and high-volume production workflows.

Manage an operations team supporting SaaS Kubernetes applications across OCI and AWS. Lead incident response, ticket triage, technology rollouts, troubleshooting, operational SLA improvement, automation, and infrastructure engineering. Mentor Operations Engineers and collaborate with architects, stakeholders, Engineering, and Client Services. The role requires extensive experience with cloud environments, large-scale .NET applications, Kubernetes, Terraform, automation, operating systems, containers, performance analysis, and full-stack troubleshooting.

Maintain and improve a highly available logistics platform running .NET Core microservices on Kubernetes. Responsibilities include defining SLOs, building observability, managing Kubernetes and infrastructure as code, automating operations, supporting CI/CD, responding to incidents, tuning PostgreSQL, planning capacity, testing resilience, and reducing cloud costs. The role participates in on-call rotations and collaborates with development, DevOps, and QA teams.

Leads the design, development, and maintenance of scalable ETL/ELT pipelines and data products across distributed, multi-cloud environments. Defines data engineering architectures, resolves complex production issues, and designs efficient data solutions. Provides technical leadership and mentorship while collaborating with architects, engineers, and business stakeholders. Requires expertise in big data, AWS services, data warehousing, databases, data modeling, orchestration, streaming, security, observability, version control, containers, and modern development practices.

Designs, builds, deploys, and supports secure, scalable cloud data solutions and pipelines for enterprise clients. Translates business requirements into data architectures, integration patterns, and models; ensures performance, reliability, governance, and documentation. Provides technical leadership during reviews and workshops, collaborates with engineering and analytics teams, contributes reusable accelerators and best practices, mentors colleagues, and manages client engagements through delivery.

Develop and maintain data pipelines, models, database structures, and orchestrations on Microsoft Azure. Transform vessel, project, campaign, and third-party data into high-quality datasets and reports. Collaborate with business stakeholders to refine requirements, support data scientists and report developers, and design modern cloud data solutions. The role requires strong data modeling, ER modeling, SQL or programming experience, and at least five years of relevant experience.

Build, deploy, and maintain customer-facing production software for frontier AI labs. Develop full-stack applications with React, TypeScript, and backend technologies; translate customer requirements into scalable solutions; and improve reliability, performance, and maintainability. Collaborate with engineering, research, product, operations, and globally distributed teams while contributing to customer deployments and the growth of Handshake AI’s engineering organization in India.

Develop, test, maintain, and optimize scalable applications using React, React.js, and Python or .NET. Collaborate with cross-functional teams on system integration, architecture, debugging, documentation, and coding best practices. Evaluate emerging technologies and apply AI tools, including generative and agentic AI, to enhance application functionality.

Develop and configure insurance and fintech applications, build web applications using ReactJS and Python, and work with REST APIs. The role requires strong programming fundamentals, database knowledge, and effective communication. The developer will also learn NextJS and API management, with TypeScript and AWS experience considered advantageous. Experience working at a product company is mandatory, along with willingness to use AI development tools.

Build and deliver scalable SaaS features for government agencies using full-stack technologies including ReactJS, TypeScript, GraphQL, and NodeJS. Responsibilities include translating business requirements into technical solutions, writing maintainable software, debugging complex issues, improving engineering processes, mentoring junior engineers, and evaluating emerging technologies. The role also involves AI-driven user experiences, workflow automation, observability, and event-driven architecture.

Design and develop scalable data-intensive applications and cloud solutions using RDBMS, SQL, Python, and Google Cloud. Build data pipelines and integrations with Spanner, Datastream, Dataflow, and CDC. Create data models, optimize production code, manage Git workflows and CI/CD releases, and apply software engineering practices for security, scalability, testing, and observability. Collaborate with architects, engineers, and business teams to deliver reliable technical solutions.

Test insurance and reinsurance risk-modeling software in an agile environment. Responsibilities include analyzing requirements, creating and executing test plans, automating test cases, debugging issues, maintaining acceptance and regression repositories, documenting defects and test artifacts, tracking results, communicating status, supporting product and development teams, improving QA processes, and training new hires.

Designs and leads enterprise-scale cloud data platforms and analytics solutions using Snowflake, Python, SQL, and Azure technologies. Responsibilities include data architecture, migration, governance, optimization, and technical leadership. The role also architects generative AI, LLM, and RAG solutions, mentors engineering teams, conducts design reviews, develops roadmaps, and translates business requirements into secure, scalable technical solutions.

Designs and maintains scalable data engineering solutions using Python, SQL, and Snowflake. Builds ETL/ELT pipelines, data warehouses, data lakes, and React interfaces while integrating generative AI, LLMs, RAG, and intelligent automation. Responsibilities include Snowflake architecture, data governance, CI/CD, testing, performance optimization, stakeholder collaboration, Agile participation, business data analysis, and mentoring junior developers.