Python Developer Experienced

Overview

Experience Required:
3-5 years of hands-on experience in full-stack development, system design, and supporting AI/ML data-driven solutions in a production environment.

Key Responsibilities

• Implementing Technical Designs: Collaborate with architects and senior stakeholders to understand high-level designs and break them down into detailed engineering tasks. Implement system modules and ensure alignment with architectural direction.
• Cross-Functional Collaboration: Work closely with software developers, data scientists, and UI/UX teams to translate system requirements into working code. Clearly communicate technical concepts and implementation plans to internal teams.
• Stakeholder Support: Participate in discussions with product and client teams to gather requirements. Provide regular updates on development progress and raise flags early to manage expectations.
• System Development & Integration: Develop, integrate, and maintain components of AI/ML platforms and data-driven applications. Contribute to scalable, secure, and efficient system components based on guidance from architectural leads.
• Issue Resolution: Identify and debug system-level issues, including deployment and performance challenges. Proactively collaborate with DevOps and QA to ensure resolution.
• Quality Assurance & Security Compliance: Ensure that implementations meet coding standards, performance benchmarks, and security requirements. Perform unit and integration testing to uphold quality standards.
• Agile Execution: Break features into technical tasks, estimate efforts, and deliver components in sprints. Participate in sprint planning, reviews, and retrospectives with a focus on delivering value.
• Tool & Framework Proficiency: Use modern tools and frameworks in your daily workflow, including AI/ML libraries, backend APIs, front-end frameworks, databases, and cloud services, contributing to robust, maintainable, and scalable systems.
• Continuous Learning & Contribution: Keep up with evolving tech stacks and suggest optimizations or refactoring opportunities. Bring learnings from the industry into internal knowledge-sharing sessions.
• Proficiency in using AI-copilots for Coding: Adaptation to emerging tools and knowledge of prompt engineering to effectively use AI for day-to-day coding needs.

Technical Skills

• Hands-on experience with Python-based AI/ML development using libraries such as TensorFlow, PyTorch, scikit-learn, or Keras.
• Hands-on exposure to self-hosted or managed LLMs, supporting integration and fine-tuning workflows as per system needs while following architectural blueprints.
• Practical implementation of NLP/CV modules using tools like SpaCy, NLTK, Hugging Face Transformers, and OpenCV, contributing to feature extraction, preprocessing, and inference pipelines.
• Strong backend experience using Django, Flask, or Node.js, and API development (REST or GraphQL).
• Front-end development experience with React, Angular, or Vue.js, with a working understanding of responsive design and state management.
• Development and optimization of data storage solutions, using SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra), with hands-on experience configuring indexes, optimizing queries, and using caching tools like Redis and Memcached.
• Working knowledge of microservices and serverless patterns, participating in building modular services, integrating event-driven systems, and following best practices shared by architectural leads.
• Application of design patterns (e.g., Factory, Singleton, Observer) during implementation to ensure code reusability, scalability, and alignment with architectural standards.
• Exposure to big data tools like Apache Spark, and Kafka for processing datasets.
• Familiarity with ETL workflows and cloud data warehouse, using tools such as Airflow, dbt, BigQuery, or Snowflake.
• Understanding of CI/CD, containerization (Docker), IaC (Terraform), and cloud platforms (AWS, GCP, or Azure).
• Implementation of cloud security guidelines, including setting up IAM roles, configuring TLS/SSL, and working within secure VPC setups, with support from cloud architects.
• Exposure to MLOps practices, model versioning, and deployment pipelines using MLflow, FastAPI, or AWS SageMaker.
• Configuration and management of cloud services such as AWS EC2, RDS, S3, Load Balancers, and WAF, supporting scalable infrastructure deployment and reliability engineering efforts.

Personal Attributes

• Proactive Execution and Communication: Able to take architectural direction and implement it independently with minimal rework with regular communication with stakeholders
• Collaboration: Comfortable working across disciplines with designers, data engineers, and QA teams.
• Responsibility: Owns code quality and reliability, especially in production systems.

Problem Solver: Demonstrated ability to debug complex systems and contribute to solutioning.

Key: Python, Django, Django ORM, HTML, CSS, Bootstrap, JavaScript, jQuery, Multi-threading, Multi-processing, Database Design, Database Administration, Cloud Infrastructure, Data Science, self-hosted LLMs

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Science, or a related field.
• Relevant certifications in cloud or machine learning are a plus.

Package: 6-11 LPA

Job Types: Full-time, Permanent

Pay: ₹600,000.00 - ₹1,100,000.00 per year

Work Location: In person