Top Python Developer Jobs in Delhi

Supports government-to-government AI and digital transformation engagements by researching partner countries, maintaining the country pipeline, drafting dossiers and proposals, coordinating delegations and exchanges, documenting meetings, and preparing milestone and funder reporting. The role requires clear writing, strong organization, public-source research skills, and interest in government and funder decision-making. Exposure to digital government, international work, languages, spreadsheets, or Python is useful but not required.

Build and deploy mobile applications for low-connectivity environments, backend services on AWS, internal data-review tools, and APIs or on-device integrations for machine-learning models. Own releases, monitoring, logging, security, testing, CI, documentation, and rapid prototypes. The role requires production application ownership, database design, mobile release experience, offline-first development, asynchronous collaboration, and occasional field deployment travel.

Develop, support and maintain Oracle EBS R12 and Oracle Cloud ERP technical solutions for Finance modules. Build PL/SQL packages, reports, data models, and integrations; troubleshoot production issues; participate in testing, documentation, and cloud/patch updates while collaborating with analysts and senior developers.

Own client accounts and improve brand visibility across AI search platforms. Responsibilities include auditing AI visibility, identifying and implementing content, schema, and technical fixes, preparing client updates and reports, and automating recurring tasks with scripts and workflows. The role uses AI tools extensively and requires clear communication, rapid learning, practical debugging, and comfort working directly with clients.

Build and operate governed MLOps and LLMOps platforms on Databricks. Productionize ML and GenAI models, RAG pipelines, vector search, and inference services; implement CI/CD, data quality, security, lineage, observability, incident response, disaster recovery, and cost controls. Partner with data science, engineering, platform, product, and security teams to ensure reliable, secure, compliant, and cost-effective AI workloads across development, QA, and production environments.

Build governed Databricks Lakehouse foundations and productionize machine learning and GenAI solutions, including forecasting, anomaly detection, NLP, RAG, and predictive analytics. Develop reliable batch and streaming workflows, CI/CD, monitoring, governance, security, lineage, and semantic models. Collaborate with product, data, platform, and domain teams to deliver measurable customer value while meeting reliability, compliance, cost, and operational objectives.

Owns the design, development, operation, and scaling of SOAR playbooks, security automation workflows, and integrations across a 24/7 MDR platform. The role automates alert triage, enrichment, investigation, containment, and incident response while improving detection quality and analyst efficiency. Responsibilities include integrating SIEM, EDR/XDR, identity, cloud, and ticketing systems; defining automation KPIs; building dashboards; ensuring workflow reliability and observability; and partnering with SOC, incident response, threat hunting, and engineering teams.

Develop high-performance core applications that collect and move large volumes of data. Own features and modules across the development lifecycle, building enterprise-grade, server-side, multithreaded, asynchronous, cloud-scale systems. Responsibilities include SQL performance programming, database design, and collaboration across remote teams using Scrum and Agile methodologies. Cybersecurity, SaaS integrations, data modeling, and ontology experience are advantageous.

Develop, deploy, and maintain machine learning and AI solutions, including predictive models, NLP applications, chatbots, LLMs, and agentic AI systems. Build scalable data and ETL pipelines using cloud platforms, big data technologies, and databases. Apply TensorFlow, PyTorch, Hugging Face, and cloud AI services while creating data visualizations and optimizing analytics workflows.

Lead and grow Cloudflare's India Customer Engineering team as a technical people leader. Provide hands-on architecture and escalation support, drive regional technical strategy, partner with sales to close deals, run operating cadence for pipeline and adoption, hire and coach CE talent, and surface product and competitive feedback.

Perform second-line triage and incident response, lead investigations and post-incident improvements, build runbooks and automation, tune detection across cloud/SaaS/container environments, support Web3 product launches, and mentor peers while participating in 24/7 rotational coverage.

Own and operate large-scale backend systems supporting network, SD-WAN, SASE, and security infrastructure. Build services, APIs, data pipelines, and automation primarily in Go and Python. Lead system design, incident response, post-mortems, reliability improvements, and greenfield development. Mentor engineers, guide technical decisions, improve engineering productivity, and collaborate across teams on complex platform initiatives.

Develops Power BI dashboards, gathers stakeholder requirements, analyzes business metrics, and delivers actionable insights. Leads BI projects, mentors junior team members, maintains documentation and process compliance, supports data automation, and collaborates with IT and business solutions teams on data initiatives. Requires advanced Excel and SQL skills, expert Power BI knowledge, large dataset experience, and strong stakeholder and team management capabilities.

Own the platform powering AI voice agents, including runtime and orchestration, real-time voice infrastructure, enterprise security capabilities, evaluation and observability systems, and production reliability. Build Kubernetes and GitOps infrastructure, CI/CD, incident response, and self-service tooling. Integrate speech and LLM technologies while ensuring low latency, scalability, auditability, data isolation, and measurable agent improvement across regulated enterprise deployments.

Own application security across mobile apps, APIs, microservices, cloud infrastructure, AI products, and third-party integrations. Responsibilities include threat modeling, architecture reviews, penetration testing, secure coding, vulnerability management, incident response, SSDLC onboarding, CI/CD security tool integration, cloud hardening, developer training, and communicating risk. The role also assesses AI and LLM security risks and develops production guardrails and automation.

Develop and maintain manual and automated tests for software and hardware, analyze CI test results, manage integration environments and test data, document defects, and collaborate with development teams. The role involves Python or JavaScript test automation, Jenkins-based CI integration, code reviews, AWS and VMware environments, Linux, and investigation of new testing tools and frameworks.

Design, develop, test, and deploy high-performance software for automated trading systems. Collaborate with quantitative researchers to define requirements, solve technical and quantitative problems, and build scalable, reliable live-trading systems. Continuously improve proprietary trading-system performance, scalability, and reliability while working across software engineering, mathematics, and quantitative finance.

Own Plane’s infrastructure and operational architecture across cloud, multi-cloud, self-hosted, sovereign, and air-gapped environments. Lead Kubernetes, GitOps, CI/CD, security, observability, incident response, disaster recovery, database operations, compliance, cost optimization, and reliability. Build automated deployments and support secure AI workload infrastructure, including open-weight models. Partner across engineering teams to improve deployment speed, operational resilience, and developer experience.

Own the frontend architecture of Plane’s local-first, real-time client. Responsibilities include client-side state, synchronization, caching, offline behavior, conflict resolution, performance optimization, dense data views, collaborative editing, design systems, and engineering standards. Partner with product, design, and backend teams to deliver scalable features across work items, boards, and documents.

Lead discovery, rapid prototyping, and deployment of production-ready AI solutions for supply chain and manufacturing. Build Python-based RAG pipelines, semantic search, multi-agent workflows, data integrations, and enterprise platform connections. Engage frontline operations, translate business needs into technical requirements, manage agile delivery, and ensure prototypes are scalable and transferable to core engineering teams. Work across SAP, MES, shop-floor platforms, databases, telemetry, and unstructured data while collaborating with security, data, and architecture teams.

Build and maintain automation solutions for accounts payable processes, including Excel and Access VBA applications, reporting tools, prototypes, and small-scale applications. Develop frontend and backend Microsoft-based solutions, troubleshoot and optimize system logic, implement production fixes, document systems, and test enhancements. The role requires translating business needs into accurate, hands-free workflows using RPA, AI, OCR, scripting, and cloud technologies.

Supports and operates NVIDIA’s large-scale on-premises and cloud network infrastructure in a 24/7 global operations environment. Responsibilities include monitoring alerts, resolving incidents within SLAs, troubleshooting network issues, managing IP infrastructure and datacenter interconnects, coordinating vendors, implementing upgrades and capacity expansions, improving operational workflows, and documenting best practices. The role requires extensive networking protocol knowledge, cloud experience, automation exposure, and strong incident-management and communication skills.

Develop generative AI applications and agentic workflows using Python, LLMs, RAG, vector databases, and frameworks such as LangChain, LangGraph, and LlamaIndex. Build AI agents integrating APIs, tools, databases, and enterprise services. Develop FastAPI REST APIs, apply machine learning libraries, optimize prompts and model performance, evaluate responses, detect hallucinations, and secure AI-generated code. Collaborate within SDLC and Agile development practices.

Manage financial and operational analytics, including reporting, reconciliation, fund movement, regulatory reporting, dashboards, and ad-hoc analysis. Deliver actionable insights for business decisions, product development, and process optimization. Collaborate with Finance, Sales, Operations, Product, Tech, and external payment partners while maintaining accurate data and reports.

Design, build, and maintain scalable data pipelines and ETL/ELT workflows using Azure Data Factory, Databricks, PySpark, Python, and SQL. Transform large datasets, optimize data ingestion and queries, monitor pipeline performance, resolve data quality issues, support data modeling, document engineering standards, and contribute to cloud data infrastructure improvements. The role also involves collaboration with architects and senior engineers and requires familiarity with Azure Synapse, Delta Lake, governance, and security.