Infis AI | Full Stack Engineer | india

5 days ago

india Infis AI Full time

Company Description

Infis AI enables businesses to achieve operational excellence with AI-powered visibility and seamless data integration. By connecting diverse systems like ERP, CRM, and QMS, our platform transforms raw data into actionable insights, helping organizations optimize workflows, identify bottlenecks, and make data-driven decisions in real time. AppShip empowers teams with tailored views and proactive alerts, ensuring compliance, efficiency, and scalability across departments and regions.


Note : This position will be with AppShip India Pvt Ltd , a wholly-owned subsidiary of AppShip Inc. As part of the AppShip family, you will contribute to the development of technology under the Infis.ai brand while collaborating with teams across geographies. AppShip India Pvt Ltd serves as a vital extension of our operations, driving innovation and excellence for our products.


Role Description

This is a full-time remote role for a Full Stack Engineer at Infis AI. The Full Stack Engineer will be responsible for core applications development, primarily involving the following skills:

  • Web App Development
  • Data Integration and ETL Pipelines
  • AI/ML Algorithms
  • Advanced Data Structures and Algorithms


As a key member of our engineering team, you will contribute to the development of our flagship Infis Platform. Your work will span multiple aspects of our technology stack, from implementing sophisticated algorithms to designing intuitive user experiences and optimizing backend performance.


Key Responsibilities


Software Development:

  • Design, develop, and maintain scalable backend services using languages like Python , Node.js , or similar.
  • Build responsive and intuitive frontend applications using frameworks like React or Angular .
  • Implement distributed system architectures inspired by frameworks like MapReduce .


Data Structures & Algorithms:

  • Develop and manage robust data pipelines, integrations, and ETL processes.
  • Develop heuristic methods and dynamic self-balancing data structures (e.g., AVL trees ) using graph databases like Neo4j or Amazon Neptune .
  • Work with Directed Acyclic Graphs (DAGs) and polytree structures .
  • Utilize real-time data processing frameworks like Apache Kafka or Spark Streaming .


AI/ML Implementation:

  • Employ Large Language Models (LLMs) to parse organizational documents and define entities.
  • Implement algorithms such as Density-Based Spatial Clustering (DBSCAN) , Principal Component Analysis (PCA) , t-SNE , and community detection algorithms.
  • Develop and deploy machine learning models using libraries such as TensorFlow , PyTorch , or scikit-learn .


Cross-Functional Collaboration:

  • Work closely with cross-disciplinary teams including product management, design, and operations.
  • Participate in code reviews, brainstorming sessions, and contribute building the best practices.



Qualifications

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • Minimum of 3 years of experience in software development with a track record of delivering high-quality projects.
  • Proficiency in both backend and frontend technologies for developing Web Applications .
  • Strong understanding of data integration tools and building ETL pipelines .
  • Experience with AI/ML algorithms and frameworks.
  • Familiarity with advanced algorithms and data structures, including MapReduce framework, Large Language Models (LLMs), Clustering algorithms (DBSCAN ), Dimensionality reduction techniques (PCA , t-SNE ), Community detection algorithms (Louvain , Girvan-Newman ), Graph theory and algorithms (DAGs , polytree structures , Hamiltonian paths ), Centrality measures, and similarity algorithms.
  • Experience with graph databases (Neo4j , Amazon Neptune ).
  • Familiarity with cloud platforms such as AWS , Azure , or Google Cloud .
  • Experience in Combinatorial Optimization is a plus.
  • Excellent problem-solving skills and the ability to adapt to new challenges.
  • Self-motivated and comfortable working in a fast-paced startup environment.
  • Strong communication skills and a collaborative mindset.


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