Top Python Developer Jobs in Delhi

Build and maintain customer-facing dashboard features across frontend and backend using React.js, Spring Boot, and Python. Develop REST APIs, data pipelines, and responsive UIs; participate in design, code reviews, testing, and production support to improve reliability and performance. Collaborate with Product and Design to deliver features and continuously improve developer productivity and application quality.

Build, optimize, and maintain scalable AWS-based data pipelines and data lakes (Snowflake/Databricks). Implement streaming ingestion (Kinesis/Kafka), CDC, automated data quality checks, and ML-ready feature stores. Collaborate with Product, ML, and Analytics teams, own pipeline QA, observability, and participate in on-call rotations to resolve production data issues.

Deploy, configure, and operate Rhombus Power's AI platform across cloud, on-premises, and edge environments. Install and validate hardware, networking, and compute infrastructure; support AWS, Docker, containerized applications, CI/CD, monitoring, and troubleshooting. Perform site readiness, rack mounting, backups, UAT, and disaster recovery. Act as on-site technical liaison, maintain deployment documentation, escalate issues, and provide ongoing operational support for defense customers.

Build full-stack product surfaces, backend services, APIs, databases, dashboards, internal tools, vendor workflows, and observability for reinforcement learning data and evaluation systems. Develop interfaces for browsing environments, inspecting trajectories, reviewing quality, debugging failures, and understanding model behavior. Partner with research, operations, vendors, and go-to-market teams to translate ambiguous requirements into reliable products. The role also involves production debugging and cloud infrastructure collaboration.

Design and implement AI-powered data pipelines and workflows combining LLMs, embeddings, vector search, and RAG to transform structured and unstructured data into business-ready outputs. Build APIs and full-stack integrations, produce Excel/PDF/Word deliverables, optimize relational and vector data stores, and prototype scalable AI solutions while contributing to engineering best practices.

Lead architecture and production of complex multi-agent LLM systems. Design evaluation pipelines (Evals), optimize RAG and vector search for scale, manage cost and latency tradeoffs, translate product requirements into agent behaviors, and mentor junior AI engineers.

Design and implement semi-autonomous AI agents and orchestration layers, integrate models with third-party tools, build feedback/learning systems, and maintain LLM pipelines and MLOps for enterprise environments.

Lead the engineering team to design, build and deploy AI-agent driven enterprise solutions. Architect full-stack apps, LLM services, and cloud infrastructure. Hands-on implementation, performance troubleshooting, recruit and mentor engineers, and align technical architecture with business goals.

Lead development and review of financial and valuation models, drive insights through analytics (Python, Power BI, Alteryx, SQL Server), design automation solutions, engage directly with clients and stakeholders, prepare client-ready demo tools, and manage cross-functional coordination across regions.

Design, build, and optimize AI-driven automation workflows using platforms like n8n, Make, and Zapier. Train, fine-tune, and deploy custom LLMs (OpenAI, Hugging Face, TensorFlow) and integrate LLM APIs. Collaborate with stakeholders, troubleshoot and document workflows, and stay current on generative AI and automation technologies.

Design, build, and optimize AI-driven automation workflows using platforms like n8n, Make, and Zapier. Train, fine-tune, and deploy custom LLMs (OpenAI, Hugging Face, etc.), integrate LLM APIs, collaborate with stakeholders, troubleshoot and document solutions, and stay current on generative AI advances. Mandatory technical assessment required.

Own and improve production infrastructure reliability, deployments, Infrastructure-as-Code, Kubernetes environments, automation, CI/CD, monitoring, alerting, and observability. Investigate incidents, optimize system performance, maintain documentation and runbooks, and support DNS, WAF, CDN, and caching infrastructure. The role requires strong Linux administration, Bash scripting, networking, Git, and containerization skills, with independent ownership and collaboration across development and operations teams.

The Technical Marketing Engineer will create technical content, demonstrate products, engage with developers, collaborate cross-functionally, and support marketing initiatives.

The DevOps Engineer designs and manages AWS cloud infrastructure, automates operations, develops CI/CD pipelines, and ensures robust monitoring and observability.

Build end-to-end infrastructure for AI agents: design React/TypeScript UIs, implement Python agent harnesses, develop Kubeflow-based MLOps pipelines, fine-tune foundation LLMs (LoRA/QLoRA/SFT/RLHF), deploy and operate services on Kubernetes, integrate agent frameworks, and apply software engineering best practices, testing, and CI/CD.

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.

As a Domain Architect, you will deploy, integrate, and optimize telecom core network solutions, focusing on automation and cloud technologies. Responsibilities include supporting network solutions, contributing to automation tasks, testing network performance, and collaborating with cross-functional teams.

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.

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.

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.

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.

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.