Top Python Developer Jobs in Delhi

Manage strategic enterprise customer relationships, serving as the primary contact for technical support, training, issue resolution, and executive engagement. Partner with sales on account health, growth, and presales activities while advocating for customer needs internally. Apply data analytics, visualization, AI tools, and automation to improve reporting, insights, troubleshooting, and customer value. Support connectivity-focused products and regularly meet clients and attend company functions.

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.

Leads a ten-person platform engineering team responsible for infrastructure, systems engineering, DevOps, networking, test automation, modernization, reliability, and operational excellence. Owns technical direction, architecture, cloud and on-premises infrastructure, cost optimization, delivery, troubleshooting, hiring, performance management, and career development. Partners with engineering, QA, product, and US leadership while building team structure and future technical leaders.

Develop cloud-based applications with strong Angular and TypeScript expertise while contributing to AWS, Kubernetes/EKS, backend services, microservices, CI/CD, infrastructure as code, and platform engineering initiatives. Build and support front-end and cloud services, troubleshoot containerized deployments, automate delivery pipelines, and collaborate across technology domains. Preferred experience includes Helm, Terraform/OpenTofu, Lambda, Node.js, Jenkins, cloud governance, event-driven systems, automated testing, and developer enablement tooling.

Develop data engineering and analytics solutions using Python, Snowflake, and AWS. Collaborate with analytics stakeholders to solve sophisticated problems, connect data to business strategy, and deliver measurable business value. The role requires strong analytical, technical, SQL, communication, and problem-solving skills, plus the ability to manage complex projects independently. Experience with large-scale datasets, relational and NoSQL databases, ETL tools, continuous integration, and Agile/Scrum is beneficial.

Supports power system studies and design for utility-scale renewable energy projects, including grounding, short-circuit, load-flow, arc-flash, protective coordination, ampacity, harmonic, and power-quality analyses. Builds system models, sizes medium-voltage collection cables, prepares technical reports, automates calculations, and supports interconnection studies. Works under senior engineer guidance while following IEEE, NESC, NEC, utility, quality, and safety standards.

Analyze business and operational performance across food delivery, services, and logistics. The role involves querying and validating data, investigating performance trends and root causes, modeling unit economics and profitability, evaluating pricing and promotional impacts, conducting cohort and retention analysis, and translating findings into actionable recommendations for stakeholders.

Entry-level AI trainee embedded in product squads to build and ship AI features. Work includes integrating LLM APIs, building model pipelines, prompt engineering, evaluation, experiments, full-stack feature integration, and writing tested maintainable code while being mentored toward independent AI engineer responsibilities.

Lead solution architecture and technical vision for platform teams, mentor engineering leads, ensure scalable resilient microservice-based web applications, drive CI/CD and code quality, collaborate across product, security, DevOps and architecture, and shepherd solutions through governance to meet business requirements.

The role involves building and scaling the Acceldata Open Data Platform, focusing on observability, coding, debugging, and collaborating with teams and the open-source community.

Design, develop, deploy, and maintain automated system tests for large-scale distributed systems. Create real-world test scenarios, improve automation methodologies, review system requirements and test plans, and collaborate with cross-functional teams. The role also includes mentoring less experienced engineers and evaluating testing infrastructure technologies.

Design, build, and deploy scalable ML models and pipelines from research to production. Own feature engineering, model tuning, real-time prediction, MLOps automation, monitoring, and lifecycle management to solve visibility, forecasting, and freight audit problems.

Own end-to-end delivery of software-engineering data programs, including scope, timelines, quality, throughput, cost, contributor performance, and customer reporting. Coordinate hundreds of distributed engineers, optimize annotation and evaluation workflows, analyze quality data, build automation and reusable playbooks, and serve as the primary client contact for AI research organizations. The role requires technical fluency sufficient to inspect code, tests, workflows, and evaluation results while leading large-scale operational execution.

Own complex enterprise telephony integrations and provide advanced post-onboarding technical support. Troubleshoot call failures using PCAPs, SIP traces, and carrier logs; improve call quality and reliability; support platforms including Twilio, Telnyx, Avaya, Genesys, and Amazon Connect; communicate technical issues to premium customers; and translate customer feedback into product improvements. The role also involves scripting troubleshooting automations and collaborating with Pacific Time customers and teams.

Monitor and validate market data deliveries, batch processes, and feeds for SaaS clients. Troubleshoot data quality and technical issues, manage incidents, coordinate releases and production patches, and support API-related client queries. Develop standard operating procedures, automate manual checks using Python, engage vendors, and lead post-mortem and root-cause analysis activities. The role requires financial markets knowledge, especially derivatives and multiple asset classes, along with Excel, SQL, troubleshooting, and communication skills.

Leads data science and machine learning architecture engagements, analyzing diverse datasets and deploying models using cloud and big data technologies. Designs scalable, cost-effective solutions, including generative AI applications, and provides technical leadership across client delivery and presales activities. Creates standards, accelerators, reports, and presentations; mentors junior staff; and communicates technical concepts to business stakeholders.

Lead a 20-person software engineering and SDET team, overseeing people development, hiring, delivery, capacity planning, escalations, architecture reviews, engineering practices, and cross-team initiatives. Build scalable team leadership structures, mentor emerging leaders, and apply AI-enabled workflows and solutions. Partner with product leadership on roadmaps and execution while maintaining strong technical credibility in software architecture, distributed systems, Python, APIs, databases, testing, and CI/CD.

Design, deploy, and maintain AWS and Databricks data infrastructure, data lakes, and scalable ETL pipelines. Build custom ingestion services and connectors using Airbyte, Go, and Python; optimize performance, reliability, monitoring, and data quality. Implement cloud data governance, security, access controls, encryption, and compliance practices while collaborating with platform engineers, analysts, and stakeholders.

Own the architecture and delivery of production-grade generative and agentic AI systems, including LLM agents, RAG pipelines, multi-agent workflows, APIs, and cloud-native services. Establish AI engineering, evaluation, observability, guardrail, and LLMOps practices while mentoring AI/ML and backend engineers. Collaborate with Product, Data, Platform, Security, and Compliance teams to deliver scalable, secure, and business-ready solutions, and provide technical direction on GenAI strategy and architecture.

Leads the identification, development, testing, and scaling of AI and automation solutions across internal delivery processes and future customer-facing use cases. Builds automated test suites, scripts repetitive workflows, pilots generative AI and agentic tools, creates reusable automation assets, tracks measurable value, and enables teams through training and knowledge sharing. Collaborates with project managers, product owners, process owners, testing communities, and delivery teams to ensure maintainable, responsible, and broadly adopted solutions.

Design, build, and maintain enterprise ETL/ELT pipelines in Microsoft Fabric; ingest and transform data from diverse sources into dimensional star schemas; optimize performance and cost; implement data quality checks and monitoring; document architecture and pipelines; collaborate with analysts, stakeholders, and global engineering teams to deliver Power BI-ready analytics datasets.

Architect, develop, integrate, test, debug, and optimize embedded software for diverse hardware platforms using RTOS, bare-metal, Zephyr, and Linux environments. Lead software architecture, system validation, test automation, and multi-threaded application development while collaborating with hardware and software teams. Define test strategies, analyze defects, document designs, conduct code reviews, mentor engineers, optimize performance and power usage, and contribute to open-source projects.

Owner of day-to-day IT infrastructure and network operations: manage LAN/WAN/SD-WAN, routers, switches, firewalls, Windows/Linux servers, virtualization, AWS/Azure, monitoring and backup. Implement security (EDR/XDR, DLP, SIEM), automate with PowerShell/Python, perform patching, DR, incident RCA, and maintain documentation and compliance.

Lead and operate cloud infrastructure and DevOps/SRE practices for a high-scale SaaS platform. Build CI/CD and IaC, manage Kubernetes and Kafka/MSK, implement observability, security and cost-optimization, mentor engineers, participate in on-call incident response, and support data migration and distributed architecture at scale.

Lead pre-sales cloud solutioning for enterprise customers: design secure, scalable AWS architectures, run discovery workshops, define migration/modernization strategies, produce technical proposals/RFP responses, engage CXO stakeholders, and work with sales and delivery teams to close cloud transformation deals.