Top Python Developer Jobs in Delhi

Design and implement production-grade AI agent harnesses, build and operate MLOps pipelines with Kubeflow, fine-tune foundation LLMs (LoRA/QLoRA, SFT, RLHF), deploy and manage services on Kubernetes, integrate agent frameworks, and apply software engineering best practices to move models from prototype to production.

Design, build, and optimize Power BI dashboards and automated ETL/data pipelines for supply chain KPIs. Integrate SAP, Databricks, and Microsoft Fabric/Azure sources, ensure data integrity and governance, enable predictive analytics, train stakeholders, and drive continuous improvement across supply chain analytics.

Design, prototype, and deliver agentic AI solutions using ML and generative models. Partner with product, engineering, and delivery teams to build, evaluate, and deploy LLM-based solutions, run experiments and POCs, and communicate technical recommendations to stakeholders.

Serve as a finance-focused SAP S/4HANA functional advisor: review SI designs, validate end-to-end finance processes (FI/CO/COPA), produce functional documentation, lead UAT/integration testing, support change management, and partner with finance, SI, and IT during go-live and hypercare.

Gather, clean, and analyze data from multiple sources; build and maintain Power BI and Excel dashboards; run SQL queries and Python scripts for automation; collaborate with cross-functional teams to interpret trends and communicate insights; create documentation and improve reporting processes.

Build and ship responsive, high-performance web applications using React and TypeScript. Translate designs into accessible UI components, optimize performance, integrate with REST/GraphQL APIs, collaborate with product/design/backend teams, participate in code reviews, and contribute to frontend architecture, testing, and CI/CD. Support occasional backend tasks if needed.

Manage and maintain SIEM infrastructure, focusing on threat detection and incident response within a Microsoft ecosystem. Responsibilities include monitoring alerts, developing detection rules, and mentoring junior analysts.

Perform exploratory analysis, build dashboards and reports (Tableau), write SQL queries, use Python for data cleaning and predictive models, collaborate with stakeholders, communicate insights, and maintain data models, pipelines, and quality checks.

Develop and deploy production-grade Generative AI services using LLMs, RAG, embeddings and vector retrieval. Build APIs and microservices with FastAPI, integrate models and enterprise workflows, optimize model accuracy and latency, implement monitoring/logging/evaluation frameworks, and support cloud/Docker deployments.

Design, develop, and maintain Power BI dashboards and semantic models using Snowflake as the data warehouse. Build efficient SQL queries, DAX calculations, implement RLS, optimize performance, schedule refreshes, and collaborate with stakeholders to translate requirements into scalable BI solutions.

Design, build, and maintain scalable test automation frameworks and suites for web, API, microservices, and backend systems. Integrate tests into CI/CD, perform functional, integration, regression, performance and E2E testing, analyze results, report defects, and drive quality engineering best practices across teams.

As a Backend Engineer, you will develop and maintain core backend infrastructure, build integrations, and work closely with frontend engineers to enhance user experience.

As a Senior Backend Engineer, you will develop and maintain backend systems, collaborate with frontend teams, and leverage AI for finance solutions.

As a Technical Pre-Sales Specialist, you will lead technical discovery, configure demos, and collaborate with teams to translate customer challenges into AI-driven solutions.

The Staff Platform Engineer will lead the architecture, development, and scaling of API-based transaction processing systems, ensuring reliability and performance while mentoring other engineers.

Provide customer-facing DevOps and platform engineering support: debug OpenTelemetry instrumentation, optimize ClickHouse, troubleshoot Kubernetes, design observability solutions, build tooling and automation, engage the open-source community, and establish scalable customer engineering processes.

Participate in a fixed-term accelerator program conducting data automation and aggregation to build dashboards, perform quantitative analysis to identify risk events and loss exposure, and investigate cases to categorize risk typologies and summarize behavioral patterns.

The Infrastructure Engineer will enhance IAC, CI/CD pipelines, and scalable cloud infrastructure while collaborating with multiple teams on incident response and observability solutions.

The CyberArk Engineer will implement PAM solutions, collaborate with clients, automate processes, and develop governance frameworks within enterprise environments.

The role involves owning AI-powered product features, designing LLM systems, making architecture decisions, and connecting engineering work to business outcomes, with a focus on independent ownership and domain understanding.

Implement, configure, and customize Actimize ActOne Case Management and STAR modules, build integrations (alert ingestion, RCM APIs, UI Java plugins), create custom forms/plugins, configure users/roles/workflows/LDAP, and write complex SQL for AML-related transaction monitoring and reporting. Provide presentations and stakeholder communication.

Own and build production AI/LLM applications end-to-end: architect RAG and agentic systems, implement function/tool calling, optimise inference costs, run evaluation frameworks, deploy on Kubernetes, and integrate with third-party platforms while collaborating with product teams to improve quality, latency, and cost.

Develop and optimize machine learning models, manage project priorities, and improve real-world solutions using advanced ML techniques.

Develop and maintain backend solutions for Machine Learning infrastructure. Collaborate on large scale software design and project management.

The Applied AI Researcher will design experiments, train models, and build pipelines for a GenAI platform while contributing to research and deploying systems in production.