Top Python Developer Jobs in Delhi

Manage and operate CyberArk PAM components, implement secret vaulting and automated rotation, integrate credential retrieval for applications, ensure high availability and incident response, collaborate across teams, document procedures, and support compliance through audit trails.

Lead and own the information security program and security engineering at NEAR Foundation. Drive SOC 2 Type 2 and ISO 27001 readiness, run logging/monitoring/incident response, manage vulnerability and third-party risk, harden identity/access/endpoint stacks, automate security and compliance across SaaS, and advise on tooling and cloud security (AWS/GCP).

Perform protocol-focused security research to prevent vulnerabilities on Ethereum mainnet. Tasks include AI-assisted analysis, fuzzing, manual review, reviewing hardforks and spec changes, improving security tooling and automation, coordinating disclosures, and supporting audits and audit competitions while collaborating with devops, specifications authors, and client implementers.

Lead enterprise security architecture: define strategy, design and validate Zero Trust, IAM, multi-cloud and AI security solutions, advise senior stakeholders, perform security assessments and remediation, drive security automation and integrations across DevOps and business units.

Lead application security efforts by governing vulnerability management, automating security workflows, embedding SSDLC practices, partnering with engineering/GRC to meet compliance, and serving as a security SME during incident response and customer escalations.

Design, build, and deploy end-to-end agentic AI and LLM applications and predictive ML models for enterprise customers. Own full lifecycle from data exploration and model development to APIs, MLOps/LLMOps pipelines, and production deployment across cloud and on-prem. Implement guardrails, evaluation frameworks, and monitoring. Work directly with customers, contribute to pre-sales proofs-of-concept, and collaborate with cross-functional teams to deliver production-grade, secure, and maintainable AI solutions.

Design, build, test, and deploy scalable full-stack applications with emphasis on Java backend services and modern front-end frameworks. Implement cloud-native microservices, REST APIs, containerization, CI/CD pipelines, and support production performance, security, and observability in an Agile environment.

Design and execute ETL test plans to validate extraction, transformation, and loading processes. Perform source-to-target SQL validations, data reconciliation, regression and integration testing, monitor ETL jobs, report defects, and collaborate with engineers and analysts to ensure data quality and governance.

Design and deliver end-to-end architectures that integrate LLMs, agentic AI, chatbots, and voice/NLP into web/mobile apps. Define infrastructure, oversee API-first microservices, enable Azure-based deployments, ensure data security/privacy, and align Data Engineering with Application teams for scalable, production-grade AI solutions.

Lead application security by shifting left: perform threat modeling and secure design reviews, deploy SAST/DAST/SCA/secrets scanning, integrate security into CI/CD, run code reviews, track remediation SLAs, maintain asset inventory, lead Security Champions, train developers, and evaluate security tools and automation.

Lead threat modeling for AWS applications, integrate security into cloud designs, assess and mitigate risks, automate security tooling, support incident response and vulnerability management, ensure compliance, and train/mentor engineering teams on AWS security best practices.

Analyze application risks and implement security controls for web, mobile, and cloud platforms. Perform vulnerability assessments, drive remediation with engineering teams, and integrate security into SDLC/CI-CD pipelines. Ensure adherence to OWASP and security benchmarks, monitor cloud configurations for risks, and implement identity, access, and data protection controls.

Maintain and optimize production LLM/VLM services and microservices (Flask/FastAPI), manage async queues, deploy and monitor Uvicorn/Gunicorn hosts, integrate LLM routing tools, design prompt strategies, build feedback/evaluation pipelines, expose secure REST APIs, and track token usage, latency, and errors to ensure SaaS-grade AI performance.

Lead and own threat modeling for GCP-hosted systems: identify threats, vulnerabilities, and mitigations; integrate threat modeling into SDLC and CI/CD; advise on controls, conduct risk assessments, support incident post-mortems, mentor teams, and drive threat-modeling tool adoption and training.

Own and mature the enterprise security program: manage identity/SSO, EDR, MDM, and SaaS security; secure cloud and developer stacks (GitHub, AWS, GCP); run vulnerability management, backup testing, and incident response; ensure endpoint lifecycle governance and maintain compliance with ISO 27001 and SOC 2.

Design, implement, and operate security controls across cloud, infrastructure, and SaaS. Lead identity, detection, vulnerability, and incident response efforts; automate controls with IaC; support compliance (SOC 2, ISO 27001); mentor engineers and drive security architecture and detection engineering.

Senior Database/Data Integration Engineer with 5–6 years' PostgreSQL experience. Requires prior employment at a publicly listed company (2+ years). Preferred skills: AWS data services including Redshift, Python, PostgreSQL performance optimization, and familiarity with Splunk.

Design and maintain end-to-end test strategy, architectures and automated frameworks for telecom packet-core products. Plan and execute performance, scalability and functional tests, manage test environments, integrate tests into CI/CD, mentor offshore test teams, gather customer requirements, and present results to customers.

Lead design and delivery of end-to-end prototypes and production-ready solutions for emerging AI initiatives. Drive AI R&D, mentor engineers, establish engineering standards, communicate architecture to stakeholders, and enable rapid experimentation amid high ambiguity.

Plan and implement QA procedures for enterprise releases. Create and execute manual and automated test plans, automate test suites, analyze features, report metrics, participate in Agile scrums, and collaborate with product owners and developers on requirements and acceptance criteria.

Plan and implement QA procedures for enterprise releases; create and execute manual and automated test plans (including Selenium); automate test suites; analyze features for test approaches; participate in Agile scrums; collaborate with product owners and developers to define requirements and acceptance criteria; gather metrics and report test results.

Design and build web and mobile applications across backend and frontend stacks. Write high-quality code, develop large-scale projects, collaborate with cross-functional teams, manage projects using tools like JIRA, and troubleshoot application and environment issues.

Design and implement production GenAI solutions with a focus on RAG and Azure serverless platforms. Build backend APIs, scalable data pipelines for indexing/embedding/retrieval, deploy serverless Azure services, implement CI/CD and IaC, and enforce security, governance, and compliance while collaborating with cross-functional teams.

Translate customer objectives into solution storyboards and digital workflows; configure, deploy and support SaaS/cloud solutions for demos, trials and production. Build dashboards, provide data-driven insights, assist testing and UAT, and collaborate with Customer Success, Product and Engineering to feed customer feedback into the roadmap.

The M&E Analyst will design and manage monitoring and evaluation projects, develop indicators, analyze data, and provide recommendations for program improvement within the organization.