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Software Engineer II

Software Engineer II

Fujitsu

3 - 6 years

8 - 12 Lacs

bengaluru

Posted:19 hours ago| Platform:

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Skills Required

software engineer python github restful sprint ai react llm machine learning javascript microservices docker restful apis git devops full stack pytorch debugging gitlab agile aws ai model cloudformation architecture

Work Mode

Work from Office

Job Type

Full Time

Job Description

Role Purpose

We are seeking a highly autonomous and result-driven AI Software Engineer to transform cutting-edge research from Fujitsu LAB into production-ready Minimum Viable Products (MVPs). This role requires a versatile engineer who can independently drive the entire software development lifecyclefrom understanding high-level product requirements to implementing robust, scalable AI solutions across cloud infrastructure.

The ideal candidate thrives in fast-paced environments with short engineering cycles, can translate abstract requirements into actionable engineering tasks, and has a proven track record of delivering AI/ML products across diverse domains with minimal supervision. The ideal candidate should also be comfortable in working with non-AI products related to computing, security and quantum software.

Key Responsibilities

AI/ML Product Development

Transform Fujitsu LAB research prototypes and algorithms into production-grade MVPs

Design, develop, and deploy end-to-end AI/ML applications and services

Implement and optimize Large Language Models (LLMs) and machine learning pipelines for real-world applications

Work with advanced AI concepts such as Retrieval-Augmented Generation (RAG), AI agents, and prompt engineering.

Evaluate and test AI models using theoretical ML knowledge and practical frameworks.

Create scalable data processing pipelines for AI model training and inference

Full-Stack Development

Build robust backend services using Python and C++ for high-performance AI workloads

Develop responsive frontend interfaces using React and JavaScript

Design and implement RESTful APIs and microservices architectures

Integrate AI models with web applications and cloud services

Cloud Infrastructure & DevOps

Architect and deploy cloud-based systems using AWS CloudFormation or similar tools.

Build and maintain CI/CD pipelines for automated testing, deployment, and monitoring

Implement DevOps best practices and QA automation frameworks

Manage containerized applications using Docker and orchestration tools

Optimize cloud resource utilization and cost efficiency

System Architecture & Security

Design secure system architectures with proper authentication, authorization, and data protection

Implement encryption, secure API design, and vulnerability management.

Ensure system reliability through logging, monitoring, and disaster recovery strategies.

Project Management & Collaboration

Collaborate with product managers, researchers, and cross-functional teams.

Participate in Agile ceremonies and contribute to sprint planning and retrospectives.

Mentor junior engineers and foster a culture of knowledge sharing.

Conduct code reviews and promote best practices across the team.

Version Control & Software Lifecycle

Manage source code using GitHub/GitLab with proper branching strategies

Implement semantic versioning and release management practices

Maintain clean commit history and meaningful pull requests

Track issues, features, and technical debt systematically

Required Qualifications

Education & Experience

Bachelor's or Master's degree in Computer Science, Software Engineering, AI/ML, or related field

3-5 years of professional software development experience

Must have: Completed at least one production deployment of an LLM or machine learning model project

Technical Skills (Must Have)

Strong programming proficiency in:

Python (for AI/ML development, backend services)

C++ (for performance-critical components)

JavaScript/React (for frontend development)

Proven experience with:

LLM integration and deployment (Hugging Face, open-source models, LLM APIs, etc.)

Machine learning frameworks (PyTorch, vLLM, scikit-learn)

Cloud platforms, specifically AWS services

GitHub/GitLab workflows and Git version control

CI/CD pipeline design and implementation (GitLab CI, GitHub Actions)

DevOps practices and QA automation

Experience Requirements

Participated in multiple large-scale product projects across different domains

Deep understanding of complete software product lifecycle (planning, development, testing, deployment, maintenance)

Track record of shipping production AI/ML applications

Essential Soft Skills

High autonomy: Able to execute complex engineering tasks with minimal technical guidance

Rapid adaptability: Thrives in fast-paced environments with short development cycles

Requirement translation: Can independently convert high-level business requirements into detailed technical specifications

Self-motivated: Strong sense of ownership and accountability

Problem-solving: Excellent analytical and debugging skills

Strong communication skills for technical and non-technical audiences

Preferred Qualifications

Additional Technical Skills

Experience with MLOps tools (MLflow, DVC), model serving (FastAPI, TorchServe).

Knowledge of confidential computing, TEE, and AI security.

Understanding of hardware acceleration (GPU, TPU).

Familiarity with performance profiling and A/B testing frameworks.

Experience with distributed systems and microservices architecture

Relocation Supported

: Yes

Visa Sponsorship Approved:

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