Fulfillment IQ - AI Software Engineer - Python/LLM/NLP

Description :

Job Title : AI Software Engineer

Location : Bangalore, KA

Job Type : Full-Time (Onsite/Hybrid)

Reports to : IT Head from the Development team

About Fulfillment IQ (FIQ) :

At Fulfillment IQ, were disruptors in the supply chain and logistics sector.

As an award-winning supply chain tech company, we design and deliver cutting-edge solutions for D2C brands, retailers, and 3PLs.

Our teams thrive on solving complex logistics challenges, from developing custom software and advising on tech stack selection to implementing advanced supply chain technology.

If youre passionate about problem-solving, thrive in dynamic environments, and want to make an impact, wed love to have you on board.

Role Overview :

As an AI Software Engineer at Fulfillment IQ, you will design, develop, and deploy intelligent applications that leverage generative AI, machine learning, and natural language processing.

Youll collaborate with engineers, product managers, and domain experts to deliver scalable solutions across supply chain, logistics, and enterprise automation.

This role requires expertise in AI/ML model development, software engineering best practices, and deploying AI solutions into production environments.

Key Responsibilities :

- Design and implement AI-powered applications with a focus on NLP, LLM fine-tuning, and generative AI.

- Develop production-ready code and integrate AI solutions with APIs, databases, and enterprise systems.

- Build rapid prototypes using AI-assisted coding tools (e.g., Claude, GitHub Copilot, Cursor) to accelerate delivery.

- Apply software engineering best practices including automated testing, CI/CD, and scalable architecture design.

- Evaluate, optimize, and monitor AI model performance for accuracy, efficiency, and reliability.

- Document workflows, prompt engineering strategies, and best practices for future development.

Qualifications & Skills :

- Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or related field.

- 3-5 years of professional experience in AI/ML engineering or applied NLP.

- Strong programming skills in Python (preferred), with experience in frameworks such as TensorFlow, PyTorch, or Hugging Face.

- Hands-on experience with AI-assisted coding tools (Claude, GitHub Copilot, Cursor, etc.)

- Solid understanding of software architecture, RESTful APIs, and cloud platforms (AWS, GCP, or Azure).

- Proficiency with Git and CI/CD pipelines.

- Strong analytical mindset with the ability to validate and refine AI outputs.

Preferred Qualifications :

- Experience in supply chain, logistics, or enterprise applications.

- Familiarity with MLOps tools and practices for managing model lifecycle.

- Exposure to computer vision, recommendation systems, or time-series modeling.

Month-to-Month Activities (Summary) :

- Months 12 : Align with product + engineering on yearly goals.

- Months 34 : Improve data pipelines and monitoring tools.

- Months 56 : Train new candidate models.

- Months 79 : Package and deploy first production-ready models.

- Months 1012 : Optimize model performance (reduce inference cost/latency).

Key Performance Indicators (KPIs) :

- development efficiency metrics :like cycle time, deployment frequency, change failure rate.

- AI model performance (accuracy, precision, recall),.

- business impact metrics (ROI, cost reduction, process automation levels), and quality and reliability metrics (bug rates,.

AI Model Performance KPIs :

- Accuracy, Precision, Recall :Measures of how well the AI model performs its intended function.

- Model Confidence/Probability Scores :The AI's certainty in its outputs.