Top Python Developer Jobs in Delhi

Develop Python-based automation and reusable data workflows, build and deploy ML, NLP, OCR and Generative AI solutions, design ETL/ELT pipelines, implement AI assistants and RAG solutions, support cloud analytics on Azure/AWS/Microsoft Fabric, and collaborate with stakeholders using Git/Azure DevOps and Agile.

Manage, validate, migrate, and QA/QC environmental data in EQuIS and related systems; configure workflows, build Power BI dashboards, support reporting, automate processes, and prepare documentation and SOPs to ensure data quality and compliance across global projects.

Manage, validate, QA/QC, migrate, and maintain environmental data in EQuIS and related systems. Configure EQuIS workflows, develop dashboards and reports (Power BI), support project teams and labs, perform data quality reviews, and produce documentation, SOPs, and training to standardize data management and reporting across projects.

Lead environmental data management initiatives across global projects: oversee EQuIS/Locus systems, integrate and QA/QC laboratory and field data, design dashboards and visualizations, perform SQL development and statistical analysis, manage data migrations, coordinate with labs and clients, mentor junior staff, and develop SOPs and automated workflows to ensure compliant, decision-ready environmental data solutions.

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.

Maintain, optimize, and troubleshoot large-scale datacenter LAN networks on Cisco Nexus platforms. Collaborate with architects and teams to implement changes, improve operations, document designs, and automate repetitive tasks using Terraform, Ansible, and Python. Support security, load balancing, routing, switching, and VPN solutions for a mission-critical SaaS environment.

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.

The Senior Data Engineer will build data pipelines, implement data governance, automate processes, and enhance data tooling to improve insights across teams.

Lead quality engineering across multiple delivery squads: define and enforce QA standards, build and maintain UI and API automation frameworks, participate in development and CI/CD, perform functional and performance testing, mentor QEs, and drive defect RCA with an SDET mindset.

Build LLM-powered dashboards, RAG pipelines, AI agents, and data pipelines for retail operations. Implement model monitoring, fine-tuning, A/B testing, and ML lifecycle processes. Integrate cloud warehouses, vector DBs, and visualization tools; collaborate with stakeholders to translate retail KPIs into AI-driven operational workflows and deploy solutions for store ops, maintenance, NSO, and CEO escalations.

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.

Provide pre-sales and post-sales AWS cloud architecture, migration assessment and strategy, proposal/RFI responses, technical presentations to C‑level clients, collaborate with sales and delivery teams, run POCs, and produce technical/ commercial proposals and thought leadership content.

Lead design and delivery of enterprise GIS solutions for environmental projects: advanced spatial analysis, web mapping and APIs, mobile data collection, geodatabase management, automation with Python/ArcPy, team mentorship, and client engagement.

Provide geospatial technical solutions for environmental and sustainability projects: design and maintain large GIS projects, process and integrate spatial data, produce technical maps, build field data collection systems (Survey123, Field Maps, Trimble), automate workflows with Python/ModelBuilder, publish online maps via ArcGIS Online/Enterprise, and apply remote sensing, GEE, and GeoAI techniques where required.

The Mapping City/Country Expert improves transit data and advises on urban and multi-modal transport, creating data policies and communicating insights to stakeholders.

Design, build, test, and maintain responsive front-end and back-end applications; develop APIs, databases, and security settings; debug and optimize software; support mobile-responsive features; write technical documentation; collaborate with data scientists/analysts and maintain the HRMS.

Design, build, and maintain backend APIs and services for a real-time supply chain visibility platform. Own system architecture, real-time event ingestion, data normalization, ML integration, monitoring, and production debugging while collaborating with Product and Data Science to deliver scalable, high-availability features.

Deploy alongside clients to transform heterogeneous multimodal data into semantic structures for AI reasoning. Design ontologies, segmentation, embedding and retrieval strategies, collaborate on ingestion pipelines, evaluate retrieval and reasoning performance, and translate insights into product and engineering signals.

Operate and own model lifecycle for defence and strategic deployments: design serving infra, CI/CD for model updates, monitoring/observability, evaluation/A-B testing, containerised serving for edge and air-gapped environments, collaborate on eval pipelines, create runbooks, and lead incident response for production model failures.

Design, build, and operate terabyte-scale data storage and ingestion platforms for on-premise and air-gapped AI deployments. Implement indexing, partitioning, query optimisation, pipeline orchestration, observability, capacity planning, and infrastructure automation while collaborating with data scientists and product teams.

Own end-to-end deployment of Sarvam's full AI stack in on-prem, air-gapped, and classified client environments. Act as technical SPOC from scoping to steady-state, diagnose integration and inference failures, manage deployment pipelines and model serving, drive adoption via training/documentation, and feed field learnings back into product.

Design, build, and maintain scalable backend and frontend systems using Python and modern frameworks; lead and mentor developers; manage delivery roadmaps; integrate frontend components; ensure performance, security, and production stability; and apply AI/ML techniques where applicable.

Lead and mentor a Southeast Asia engineering team; ensure code quality and testing; drive project progress; define integrations strategy; design, build, and maintain third-party integrations; align engineering efforts with product and leadership.

Lead customer-facing development and deployment of production-ready ML, Generative AI, and agentic AI solutions for supply chain challenges. Partner with customers from discovery through adoption, build scalable ML pipelines and prototypes, evaluate emerging AI technologies, collaborate cross-functionally, and mentor team members to drive measurable business impact.