Senior_AI_developer

Roles & Responsibilities: Implementation & validation of AI-powered solutions with modular, reusable components using Python, REST APIs & in-house developed AI framework/s; Contribute to the development of AI pipelines, from data ingestion to model deployment and monitoring; Collaborate across domains to integrate AI/LLM capabilities to realize use cases such as AI-powered ASPICE assessments, Artefacts evaluation, etc.; Optimize agent behavior for safety, efficiency, and explainability. Technical Skills: Strong programming background in Python with experience in AI/ML frameworks (e.g., LangChain, Hugging Face, OpenAI APIs); Knowhow of RAG concept; Understanding of LLMs, Embeddings, and multi-model reasoning; API orchestration, and GenAI prompt engineering; Familiarity with tools like Git, GITHUB, versioning concepts; Strong analytical and problem-solving skills with a user-centric design mindset; Familiarity of A2A, MCP protocols; Workflow Management: Experience with workflow automation tools like PowerAutomate, n8n; Hands-on experience with GenAI foundation models and vector databases, leveraging foundational AI models for advanced capabilities; Familiarity with automotive standards such as ASPICE PAM model (Good to have)

Responsibilities

Implementation & validation of AI-powered solutions with modular, reusable components using Python, REST APIs & in-house developed AI framework/s; Contribute to the development of AI pipelines, from data ingestion to model deployment and monitoring; Collaborate across domains to integrate AI/LLM capabilities to realize use cases such as AI-powered ASPICE assessments, Artefacts evaluation, etc.; Optimize agent behavior for safety, efficiency, and explainability

Requirements

Any Bachelor’s or Master’s degree; 3–4 years of hands-on experience in AI model development, deployment, and optimization; Strong command of Python and libraries; Deep understanding of machine learning algorithms, model training workflows, and deep learning architectures (CNN, RNN, Transformers); Experience with data wrangling, preprocessing, and feature engineering for model readiness; Skilled in developing and integrating models via APIs (Flask, FastAPI) and containerization using Docker; Proficiency in model evaluation metrics, hyperparameter tuning, and performance analysis; Experience with Git and collaborative code development workflows; Strong analytical mindset and ability to troubleshoot complex model behaviors; Strong programming background in Python with experience in AI/ML frameworks (e.g., LangChain, Hugging Face, OpenAI APIs); Knowhow of RAG concept; Understanding of LLMs, Embeddings, and multi-model reasoning; API orchestration, and GenAI prompt engineering; Familiarity with tools like Git, GITHUB, versioning concepts; Strong analytical and problem-solving skills with a user-centric design mindset; Familiarity of A2A, MCP protocols; Workflow Management: Experience with workflow automation tools like PowerAutomate, n8n; Hands-on experience with GenAI foundation models and vector databases, leveraging foundational AI models for advanced capabilities

Nice to have

Experience working with Large Language Models (LLMs), Generative AI, or prompt engineering; Familiarity with cloud AI platforms; Knowledge of MLOps practices — CI/CD for ML, model monitoring, and retraining pipelines; Exposure to computer vision or NLP-based AI systems; Familiarity with automotive standards such as ASPICE PAM model (Good to have)