Top Python Developer Jobs in Delhi

Build and ship customer-facing AI features for Scout, including agentic LLM workflows, tool calling, RAG pipelines, evaluations, guardrails, and prompt engineering. Develop full-stack services and interfaces using backend languages, TypeScript, React, and mobile technologies. Deploy scalable, secure systems on AWS and Kubernetes, with monitoring, testing, and CI/CD. Own features end-to-end, collaborate with stakeholders, make product decisions, and contribute to reliable AI infrastructure and engineering practices.

Leads biomedical data science for clinical and health research, integrating clinical, observational, EHR, genetic, wearable, electrophysiological, and video data. Develops signal-processing methods, machine-learning models, probabilistic and time-series analyses, scalable data pipelines, and reproducible workflows. Validates clinically relevant models, supports disease phenotyping and predictive modeling, ensures compliance with pharmaceutical and healthcare standards, and communicates technical findings to clients and stakeholders.

Build data infrastructure and reliable pipelines, analyze product usage, train traditional and LLM-based models, define product metrics, run experiments, and translate findings into product and go-to-market decisions. The role combines data science, data engineering, product analytics, machine learning, and stakeholder communication, with ownership across data modeling, evaluation, experimentation, and product insight generation.

Develop and maintain automation, infrastructure, and monitoring solutions for large-scale distributed compute systems. Troubleshoot complex systemic issues, deploy software safely at scale, participate in on-call rotations, restore service-impacting incidents, and improve observability and reliability. The role requires expert Linux systems administration, configuration management, performance optimization, infrastructure automation, and proficiency with Python or Golang, cloud platforms, and monitoring technologies.

Define and evolve scalable, secure, cloud-native EMS architectures for autonomous telecom networks. Lead requirements analysis, system design, development, troubleshooting, performance optimization, and technical decisions. Build multi-agent pipelines and agent harnesses, drive AI-enabled SDLC adoption, and modernize engineering practices using Java, microservices, Kubernetes, OpenShift, automated testing, and CI/CD. Collaborate across product, platform, architecture, verification, and network-element teams while mentoring engineers.

Leads statistical programming for pharmaceutical clinical development studies, independently creating SDTM and ADaM datasets, specifications, tables, listings, graphs, and regulatory submission materials. Develops and validates SAS and R programs, oversees CRO programming deliverables, supports clinical reports and FDA submissions, maintains programming standards, and contributes to CRFs, validation plans, data transfers, SOPs, and work instructions.

Build and improve CI/CD pipelines, release automation, deployment workflows, infrastructure-as-code, and DevOps tooling. Triage pipeline issues, automate manual processes, maintain documentation and runbooks, support data center infrastructure, and improve platform security through hardening and credential management. Collaborate with globally distributed SRE and development teams, providing primary DevOps support during India business hours and coordinating handoffs to U.S.-based teams.

Support Web3 users and technical operations across Telegram, Discord, blockchain infrastructure, RPC services, and AI-powered support workflows. Triage node and synchronization issues, develop and troubleshoot Telegram Bots and Mini Apps, maintain knowledge-base content, coordinate urgent issue resolution, and document solutions. The role requires blockchain fundamentals, programming ability, technical troubleshooting, responsive communication, and five-day weekly availability.

Lead development of foundational platform services, including identity, authorization, search, and API infrastructure. Design scalable architectures, optimize database performance, build internal developer tools, improve observability and frontend reliability, and collaborate with product teams. The role includes writing tested code, conducting reviews, documenting platform capabilities, supporting internal users, and evaluating or integrating AI-assisted development and LLM-powered systems.

Maintains corporate production services through ticket management, incident response, observability, monitoring dashboards, and operational automation. Uses AI-assisted tools and agentic workflows to improve triage, root-cause analysis, documentation, and self-healing capabilities. Writes automation code, supports data pipelines and cloud infrastructure, manages on-call responsibilities, and partners with global stakeholders to resolve issues and improve service reliability.

Develop and maintain high-availability distributed systems supporting network automation, observability, and identity management. Responsibilities include designing software, improving testing and deployment, monitoring systems, supporting the full product lifecycle, evaluating emerging technologies, and mentoring junior engineers. The role requires programming experience with Python, Go, or shell scripting; Linux/Unix development; internet protocols; and version control systems.

Own HR data mapping into Amazon Redshift, maintain data dictionaries and metric definitions, and build executive dashboards in QuickSight and Power BI. Analyze workforce metrics, optimize SQL queries, resolve data quality issues, and partner with HR, recruiting, compensation, and leadership teams. The role supports recurring reporting, privacy-compliant handling of sensitive employee data, and potentially AI-powered analytics solutions.

Build data-driven go-to-market solutions that prioritize accounts, identify revenue opportunities, automate sales and marketing workflows, and improve pipeline, expansion, retention, and productivity. Develop scoring and intelligence models, integrate commercial data sources, validate data quality, measure workflow performance, build dashboards, coordinate platform implementations, manage vendors, and explore AI-assisted account research and outreach. Partner cross-functionally with Sales, Marketing, Customer Success, IT, Data, and Revenue Operations teams.

Designs and reviews security architecture, performs threat modeling and cloud assessments, responds to incidents, manages security tools, and advises engineering teams on secure development. Conducts code and vulnerability reviews using OWASP and MITRE ATLAS, evaluates AI and LLM security risks, and supports security monitoring, risk assessment, data protection, and compliance across applications, infrastructure, and endpoints.

Design, deploy, and automate scalable hybrid cloud infrastructure across AWS and Azure using IaC (Terraform/CloudFormation/ARM/Bicep). Build CI/CD pipelines, implement observability (Prometheus, Grafana, Datadog, CloudWatch, Splunk), lead incident response and RCA, define SLIs/SLOs, enforce DevSecOps practices, manage access (IAM/Azure AD/RBAC), and collaborate with engineering teams to optimize reliability and performance.

Design and verify complex CPU/SoC IP by planning verification, building constrained-random UVM or C/C++ test environments, or using formal SVA tools. Debug RTL (Verilog) in simulation/emulation, write functional coverage, and close verification holes to meet tape-out requirements.

Design, build, and deploy production generative AI features, including LLM applications, RAG pipelines, and agentic systems. Develop scalable Python and cloud backend services, evaluate model accuracy and performance, optimize reliability and cost, and implement monitoring, security, and observability. Collaborate with product, design, and engineering teams while mentoring teammates and exploring emerging AI technologies.

Designs and maintains automated test frameworks and suites for functional, integration, load, performance, API, UI, and system testing. Develops test strategies, improves CI/CD automation infrastructure, validates distributed systems, identifies coverage gaps, investigates defects, and enhances software reliability and quality engineering practices in collaboration with engineering and release teams.

Develop, deploy, and maintain scalable AI/ML pipelines and production systems, including LLMs and generative AI models. Collaborate with data scientists, software engineers, architects, and clients to integrate AI capabilities into products. Optimize model performance, latency, and cost on AWS, GCP, and Azure, using Docker, Kubernetes, CI/CD, monitoring, versioning, and other MLOps practices.

Leads 24x7 NOC operations, major incident management, cloud infrastructure support, monitoring, and operational excellence. Oversees incident response, SLA and reliability targets, stakeholder communications, shift handoffs, runbooks, ITSM processes, root-cause analysis, and automation. Manages AWS and Azure environments, Linux and Windows systems, networking, Kubernetes, databases, and monitoring platforms. Mentors NOC engineers and drives continuous improvement across production support operations.

Provides research and data-analysis support to economists focused on monetary economics and financial markets in Asia and the Pacific. Responsibilities include preparing publications and presentations, collecting and validating data, reviewing methodologies, developing databases, identifying new data sources, applying advanced analytics, and collaborating on innovation projects. The role bridges economics, data, and technology in a multicultural international environment.

Leads compute-focused cloud engineering initiatives involving software engineering, cloud platforms, containerization, orchestration, infrastructure provisioning, monitoring, logging, and cloud security. Provides technical leadership, independently solves complex design problems, guides technical teams, and collaborates cross-functionally to implement scalable cloud solutions and DevSecOps practices.

Owns highly available AWS and EKS platforms, CI/CD pipelines, infrastructure as code, observability, incident response, reliability engineering, and security operations. The role designs resilient cloud environments, manages Kubernetes and Docker workloads, automates delivery and operations, leads major-incident response, establishes SLOs, and coordinates vulnerability remediation. It also mentors engineers and improves production readiness, disaster recovery, and operational efficiency.

Designs and maintains scalable data pipelines and ETL/ELT workflows using Python, SQL, and Azure Databricks. Manages large structured and semi-structured datasets, data models, monitoring, quality controls, troubleshooting, and production support. Integrates LLM and Generative AI capabilities, including APIs, embeddings, prompt engineering, and RAG workflows, into data solutions. Collaborates with engineering, analytics, and business teams while following security, CI/CD, documentation, and maintainability best practices.

Develops, validates, deploys, and maintains SAS-based clinical data programming, dashboards, reports, and analytics solutions. The role supports clinical data review, reconciliation, risk-based quality management, centralized monitoring, site performance oversight, and study decision-making. Responsibilities include requirements gathering, data extraction and transformation, quality control, stakeholder presentations, documentation, SOP compliance, workflow automation, and mentoring less-experienced colleagues.