Fullstack Developer - AI

Adobe · Delhi

  • Experience3–4 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelmid
  • Posted3 Sept 2026
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About Adobe

Adobe is hiring in Delhi in technology software. This role looks for around 3+ years of experience.

Skills

  • Full Stack Development
  • React
  • JavaScript
  • TypeScript
  • Node.js
  • Python
  • Java
  • C#
  • SQL
  • NoSQL
  • data structures
  • algorithms
  • Generative AI
  • LLMs
  • prompt engineering
  • RAG
  • fine-tuning
  • pandas
  • scikit-learn
  • TensorFlow
  • PyTorch
  • cloud platforms
  • CI/CD
  • ML pipelines
  • AWS
  • Azure
  • GCP
  • DevOps
  • Jenkins
  • GitHub Actions
  • Docker
  • Kubernetes
  • Git
  • distributed systems

The role

A full-stack developer at a software product company builds intelligent product capabilities using Full Stack Development, Generative AI, and Data Science, taking innovation projects from prototypes through deployment. The role applies React, Node.js, Python, and cloud platforms to create AI-driven features, evaluate emerging technologies, and optimize distributed systems.

Full job description

Responsibilities:

Ideate, design, and drive end-to-end innovation projects, from concept and prototyping to implementation, testing, deployment, and iteration.

Build scalable, cutting-edge solutions leveraging full-stack development, AI, Generative AI (GenAI), and data science to solve complex business problems and create new product capabilities.

Apply AI/GenAI techniques (e. g., LLMs, RAG, prompt engineering, predictive modeling) to develop intelligent features, prototypes, and proof-of-concepts that push product boundaries.

Collaborate cross-functionally with engineering, product, design, and data teams to identify innovation opportunities, assess feasibility, mitigate risks, and deliver high-impact technical solutions.

Conduct technical reviews of systems and emerging technologies to evaluate readiness, identify gaps, risks, and opportunities, and provide actionable recommendations and mitigation strategies.

Demonstrate deep understanding of technology stacks from a functional and architectural standpoint; debug complex issues and optimize performance.

Develop and maintain comprehensive documentation for prototypes, AI models, frameworks, and innovative processes.

Mentor junior engineers, lead knowledge sharing, and contribute to Business Intelligence processes (e. g., dashboards, metrics, and knowledge base).

Take ownership of personal technical growth, staying current with emerging tools, AI advancements, and best practices in innovation and data science.

Manage multiple priorities effectively, delivering high-quality results in a fast-paced environment.

Requirements:

3+ years of hands-on experience in software development and driving technical innovation projects.

Strong full-stack development proficiency (e. g., frontend: React / JavaScript / TypeScript; backend: Node.js / Python / Java / C#; databases: SQL / NoSQL)

Solid programming fundamentals, including data structures, algorithms, and problem-solving.

Proven ability to lead end-to-end innovation projects (from ideation and architecture to delivery and measurement of impact).

Hands-on experience with AI / GenAI (e. g., LLMs, prompt engineering, RAG, fine-tuning) and data science (e. g., Python, pandas, scikit-learn, TensorFlow / PyTorch).

Expertise in modern tools and frameworks (e. g., cloud platforms, CI/CD, prototyping tools, ML pipelines).

Familiarity with cloud platforms (AWS / Azure / GCP), DevOps (Jenkins / GitHub Actions / Docker / Kubernetes), and version control (Git).

Excellent critical thinking, analytical skills, and ability to debug complex, distributed systems.

Strong communication skills with experience presenting technical recommendations and innovative ideas to stakeholders.

Bachelor's / Master's degree in Computer Science, Engineering, or a related field (or equivalent experience).

Preferred Qualifications:

Experience building innovative AI-driven features or products (e. g., generative tools, intelligent agents, predictive systems).

Contributions to open-source projects, research, or relevant publications in AI / innovation.

Certifications in cloud, AI / ML, or related fields (e. g., AWS / Azure ML).