Top Python Developer Jobs in Delhi

Lead development and deployment of AI models and agentic architectures, collaborate with cross-functional teams to translate business needs into technical solutions, ensure data readiness for S4, monitor production performance, apply prompt engineering and automation, and uphold data governance and ethical AI practices.

Lead design, development, deployment, and monitoring of advanced AI/ML models and agentic solutions. Collaborate with cross-functional teams, translate business needs into technical specifications, ensure data readiness for S4, apply prompt engineering and automation, and uphold data governance and ethical standards.

Lead technical design and implementation of Salesforce Data Cloud and MCP personalization solutions. Architect data models and ingestion pipelines, enable identity resolution and audience activation, integrate MarTech systems, ensure data quality and privacy compliance, troubleshoot integrations, mentor engineers, and support journey orchestration and roadmap planning for real-time personalized experiences.

Lead consultative pre-sales technical engagements, design integration and AI solution strategies across Boomi's platform, deliver demos and presentations, support RFIs/RFPs and POCs, collaborate with account teams and partners, and act as a trusted advisor to demonstrate business value and ROI.

Lead architecture and delivery of Control Center platform capabilities, evolving it into an AI-agent-ready operations platform. Design MCP registries, AI orchestration, access automation, guardrails, and HITL workflows. Mentor engineers, drive cross-team roadmaps, own backend services reliability, SLOs, observability, incident response, and collaborate with Security and Product to deliver secure, compliant internal tooling.

Design and implement Generative AI solutions to improve operational efficiency. Collaborate with teams to identify opportunities and ensure data governance.

Develop, implement, and deploy scalable machine learning models for healthcare solutions. Collaborate cross-functionally to integrate models, analyze data to improve performance, ensure data quality, and stay current with ML advancements to support patient care and operational efficiency.

Analyze large healthcare datasets to extract insights, build data models, reports and dashboards, ensure data quality, collaborate with cross-functional teams, and present findings to stakeholders.

Design, develop, and deploy autonomous AI agents and LLM-powered systems for resume optimization, job matching, career coaching, and AI interviews. Build multi-agent workflows, RAG systems, vector databases, prompt engineering and fine-tuning pipelines, agent evaluations, and human-in-the-loop oversight. Integrate LLMs into web applications and browser extensions while ensuring production scalability and reliability. Collaborate with engineering, product, design, and company leadership, and develop traditional machine learning workflows where needed.

Leads a team of data engineers and owns the architecture, implementation, governance, security, and optimization of a GCP Data Lakehouse platform. Responsibilities include designing Spark and Delta Lake pipelines, managing Unity Catalog, improving SQL and ETL performance, enabling analytics and machine learning use cases, implementing CI/CD with GitLab and Jenkins, and communicating technical strategies to stakeholders.

Lead design and delivery of Salesforce Data Cloud CDP solutions: architect data models and ingestion pipelines, integrate with Marketing Cloud (MCP) and MarTech, ensure data quality, privacy compliance, performance, mentor engineers, and support audience segmentation and journey orchestration.

Lead end-to-end delivery for technical programs across infrastructure, DevOps, and IT operations. Maintain a single source of truth for projects, map cross-team dependencies, drive decision forums, prepare executive briefs, and build AI-driven automation and integrations (Jira, Confluence, ServiceNow, Slack/Teams) to reduce manual coordination. Build KPI dashboards, detect risks early, and resolve blockers through stakeholder influence and technical literacy.

The Senior Data Engineer is responsible for developing Python applications, optimizing data pipelines, integrating APIs, and collaborating with teams to deliver data solutions.

Support economic consulting engagements by cleaning, validating, and preparing large datasets; write SAS, Python, and SQL programs to automate workflows; perform statistical and econometric analyses; produce tables, charts, and reports; document methodologies; collaborate with international teams and senior staff to ensure high-quality analytical outputs.

Lead architecture and delivery of Salesforce Data Cloud solutions: design data models and ingestion pipelines, integrate with Marketing Cloud and MarTech, ensure identity resolution, privacy compliance, and performance, mentor engineers, and support audience segmentation and journey orchestration.

Use data and advanced analytics to solve complex business problems, design and deploy scalable ML/data products on cloud platforms, collaborate with clients and cross-functional teams, and communicate actionable insights.

The Solutions Architect will design, optimize, and deliver technology solutions, focusing on cloud technologies and collaborating with stakeholders to align strategies with business goals.

Build and deploy machine learning models on large healthcare datasets, extract actionable insights, develop scalable data processing systems, collaborate with cross-functional teams, and communicate findings to stakeholders to improve patient outcomes.

Design, operate, and optimize a large-scale distributed architecture and microservices. Troubleshoot production issues and improve API gateways, ensuring system reliability and performance. Engage in CI/CD improvements and contribute to service decoupling.

Architect and build automated application security layers across the SDLC for a large financial services program. Develop Python-based security runbooks, AI-enabled secure code scanning, hardened baseline automation, and CI/CD integrations for SAST, DAST, and SCA tools. Review complex Java and Python code, provide code-level remediation guidance, tune scanning tools, and support secure coding adoption with high autonomy.

Founding Machine Learning Engineer to design, build, train, evaluate, and deploy ML models and pipelines. Own end-to-end ML projects, work with large datasets, perform feature engineering and experimentation, and integrate models into production. Influence ML architecture, best practices, and product roadmap in an early-stage environment.

Lead enterprise CDP and MarTech architecture strategy and delivery. Define future-state architectures, lead integrations across CDP/CRM/AdTech/Analytics/AI, oversee ingestion pipelines, enforce data governance and privacy, mentor engineers, and drive AI-enabled personalization and journey orchestration.

Lead enterprise CDP and MarTech architecture engagements: define future-state architectures, oversee multi-platform integrations (CDP, CRM, AdTech, Analytics, AI), ensure data governance and privacy, drive ingestion pipelines and activation workflows, embed AI/ML capabilities, mentor teams, and translate business requirements into scalable technical solutions.

Support reliability, monitoring, and modernization of Kubernetes-based microservices platforms. Build Datadog observability solutions including dashboards, alerts, APM, metrics, logs, and tracing; integrate tooling with AWS and CI/CD pipelines; automate operational tasks with Python; manage agents, integrations, API keys, and access controls; and lead platform maintenance and improvements for reliability, scalability, and performance.

The Full Stack Engineer will manage carrier integrations, act as a forward deployed engineer for top accounts, and resolve bug backlogs, ensuring smooth operations and customer satisfaction.