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Full Stack Engineer

Full Stack Engineer

Covalense DigitalThane, IN
1 day ago
Job description

Job Title

Full-Stack + Generative AI Engineer

Job Type

Full-time

About the Role

We are looking for a talented Full-Stack + Generative AI Engineer to build, deploy, and maintain AI-driven applications. You will work across frontend, backend, and AI / ML components to deliver features that leverage state-of-the-art generative models. You will collaborate with product, data science, and engineering teams to bring innovative solutions to production.

Key Responsibilities

  • Design, develop, and maintain full-stack web applications (frontend and backend) with clean, scalable, and maintainable code.
  • Integrate generative AI / large language models (LLMs) into user-facing applications (chatbots, intelligent assistants, content generation, etc.).
  • Build and maintain RESTful or GraphQL APIs for AI integration and data access.
  • Work on data pipelines, ingestion, and preprocessing of structured and unstructured data.
  • Use vector stores / embedding databases / semantic search (for RAG and other AI use cases).
  • Develop prompt engineering, fine-tuning, and model optimization for generative AI services.
  • Ensure system reliability, monitoring, and observability of AI services in production.
  • Collaborate with UX / design teams to build responsive and interactive frontends.
  • Ensure security, data privacy, and compliance in AI features.
  • Participate in code reviews, mentor junior engineers, and help define best practices.

Required Skills & Qualifications

  • Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience).
  • At least 3–5 years of experience in full-stack development.
  • Strong proficiency in one or more backend languages / frameworks (e.g. Python - Flask, FastAPI, Django; Node.js; Java; etc.).
  • Good frontend skills using React / Angular / Vue (JavaScript / TypeScript).
  • Experience using cloud platforms (AWS, GCP, Azure) and working with containerization (Docker, Kubernetes).
  • Experience with AI / ML frameworks or services; familiarity with LLMs, prompt engineering.
  • Understanding of vector databases, embeddings, retrieval-augmented generation (RAG).
  • Solid understanding of REST APIs, microservices architecture.
  • Version control (Git), CI / CD pipelines, automated testing.
  • Preferred Skills

  • Prior work deploying generative AI solutions in production.
  • Experience with frameworks / libraries such as LangChain, LlamaIndex, etc.
  • Experience with agent-based architectures or multi-agent systems.
  • Skills in scaling and optimizing performance, latency, and resource usage.
  • Familiarity with real-time data / streaming, graph databases.
  • Experience in domain-specific AI (NLP, computer vision, or other relevant fields).
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