
Senior Full Stack (React + Python ) Developer Role
- AI
- Devops
- Design Thinking
- LLM APIs
- RAG
- CI/CD
- React.js
- JavaScript
- TypeScript
- HTML5
- CSS3
- Python
- FastAPI
- Django
- Flask
- System Design
- NoSQL
- MySQL
- PostgreSQL
- MongoDB
- REST API
- End-to-End Testing
- Jest
- pytest
- Playwright
- Cypress
- Azure
- AWS
- GCP
- Docker
- Kubernetes
- Vector Search
- Machine Learning
- Agile
- LangChain
- LangGraph
- Semantic Kernel
- MLOps
It's fun to work in a company where people truly BELIEVE in what they are doing!
We're committed to bringing passion and customer focus to the business.
Job Locations -BENGALURU/MUMBAI/CHENNAI/ PUNE/ NOIDA/ GURUGRAM/ HYDERABAD/ COIMBATORE
About Company
Fractal is a leading AI and analytics company that helps global enterprises turn data into decisions at scale. We are looking for a hands-onSenior Full Stack Engineer with 6+ years of experience to design, build, and scale enterprise-grade digital products across front-end, back-end, APIs, cloud, DevOps, and AI-enabled application layers. This role requires strong engineering ownership, practical design thinking, and the ability to deliver secure, reliable, and high-performing solutions in collaboration with architects, TPMs, and cross-functional teams.
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Role Brief:
You will own critical feature implementation across web applications, APIs, integrations, cloud-native services, and AI-powered capabilities. The role combines deep hands-on engineering with practical participation in technical design, code quality, performance optimization, and operational excellence.
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You will work closely with architects, TPMs, product managers, QA engineers, DevOps engineers, designers, and peer developers to translate solution intent into scalable, maintainable, and production-ready systems.
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Key responsibilities include:
- Develop robust, efficient, and maintainable code for critical features, ensuring both functional and non-functional requirements are met.
- Participate in system and solution design discussions, contributing practical implementation insights, technical trade-offs, and pseudo-code where needed.
- Act as a technical point of contact for day-to-day implementation issues, troubleshoot challenges quickly, and drive timely resolution.
- Enforce and improve code quality through code reviews, engineering standards, automated testing, and secure development practices.
- Collaborate closely with architects, TPMs, product teams, and platform teams to translate high-level designs and AI use cases into scalable, secure, and production-ready solutions.
- Build and integrate AI-powered application capabilities such as copilots, intelligent assistants, summarization, search, recommendations, and workflow augmentation using LLM APIs and related services where relevant.
- Implement AI-enabled solution patterns including prompt orchestration, retrieval-augmented generation (RAG), grounding strategies, structured outputs, tool or function calling, and quality or safety guardrails for enterprise use cases.
- Support and improve DevOps practices including build pipelines, CI/CD workflows, automated testing, release readiness, and engineering observability.
- Monitor, troubleshoot, and optimize application, system, and AI feature performance in line with project objectives, reliability expectations, latency targets, and cost considerations.
- Document technical designs, implementation decisions, and operational considerations to support maintainability, auditability, and knowledge transfer.
- Mentor junior engineers by sharing best practices, reviewing work products, and guiding them on sound engineering approaches.
- Contribute to technical proposals, estimations, reusable assets, and implementation improvements including automation, refactoring, and component reuse.
- Maintain compliance with security, quality, governance, and audit expectations, and contribute to broader process and capability improvement initiatives within CDT.
Must Have
- 6+ years of hands-on experience building enterprise-grade full-stack applications, with strong ownership of complex engineering workstreams from design through delivery.
- Strong expertise in one or more modern front-end frameworks such asReact, , along with solid command ofJavaScript/TypeScript,HTML5, andCSS3.
- Strong back-end engineering experience in at least one major stack such asPython (FastAPI, Django, Flask).
- Strong understanding of system design fundamentals, design patterns, API design, scalability, reliability, performance optimization, and distributed application architecture.
- Experience with relational and/or NoSQL databases such as MySQL, PostgreSQL, SQL Server, MongoDB, or similar, including schema design and query performance tuning.
- Hands-on experience building and consuming REST APIs and working with modern integration patterns across services and external systems.
- Strong understanding of responsive web design, reusable component-based architecture, accessibility basics, and front-end performance optimization.
- Hands-on experience with automated testing practices including unit, integration, and end-to-end testing using tools such as Jest, PyTest, Playwright, Cypress, or equivalent.
- Working experience with cloud platforms such asAzure,AWS, orGCP, including deployment, configuration, observability, and support for cloud-native environments.
- Hands-on experience with containerization and modern engineering environments using tools such asDocker, Kubernetes, or equivalent platforms.
- Strong understanding of DevOps and secure SDLC practices including CI/CD pipelines, source control workflows, code reviews, build automation, and release quality controls.
- Hands-on experience integrating AI capabilities into applications, including LLM APIs, prompt design, structured outputs, tool or function calling, and building reliable user-facing AI features.
- Good understanding of retrieval-augmented generation (RAG), vector search, grounding strategies, prompt orchestration, and common GenAI failure modes such as hallucination and response inconsistency.
- Experience implementing evaluation, monitoring, and guardrails for AI-enabled features, including response quality checks, fallback handling, latency and cost awareness, and privacy or security considerations for enterprise use cases.
- Ability to translate solution architecture into detailed implementation plans and contribute effectively to technical design discussions with architects and engineering leads.
- Strong troubleshooting and debugging skills, with the ability to rapidly resolve production and implementation issues while maintaining engineering quality.
- Experience mentoring junior engineers and contributing to engineering best practices, reusable assets, and continuous improvement initiatives.
- Excellent problem-solving, collaboration, and communication skills, with the ability to work effectively in cross-functional and client-facing delivery environments.
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Nice to Have
- Experience working in Agile delivery environments with close collaboration across product, QA, DevOps, TPM, and architecture teams.
- Exposure to performance tuning, observability, logging, monitoring, caching, and reliability engineering practices in production systems.
- Experience contributing to reusable frameworks, shared components, internal accelerators, or broader engineering capability-building initiatives.
- Prior experience supporting estimations, technical proposals, solutioning discussions, or client-facing technical workshops.
- Exposure to AI engineering frameworks and tooling such as LangChain, LangGraph, Semantic Kernel, vector databases, model gateways, or similar ecosystems for building production-grade GenAI applications.
- Experience with LLMOps or MLOps practices such as prompt versioning, evaluation pipelines, experiment tracking, workflow observability, and responsible AI controls.
- Exposure to building AI copilots, agentic workflows, recommendation systems, or domain-specific GenAI solutions for enterprise products.
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What success looks like in this role
- Own critical full-stack feature implementation and deliver high-quality solutions with minimal oversight.
- Convert architecture intent into scalable, secure, and production-ready implementations across core and AI-enabled application capabilities.
- Uphold strong engineering standards across code quality, testing, security, documentation, performance, and DevOps practices.
- Act as a dependable technical anchor by resolving implementation issues quickly and collaborating effectively across functions.
- Drive continuous improvement through reuse, automation, maintainability, mentoring, and contribution to team capability building.
- Deliver reliable AI-enabled experiences with appropriate quality, safety, observability, and cost awareness.
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If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
Hiring Related Queries
India:HiringsupportIndia@fractal.ai
Outside India:HiringsupportROW@fractal.ai
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Senior Full Stack (React + Python ) Developer Role · Fractal Analytics Pvt. Ltd.