Software Development Engineering

The AI Engineer with 5 to 8 years experience responsible for designing and deploying production-ready AI infrastructure and machine learning models. They architect Agentic AI workflows, RAG systems, and high-performance data pipelines to drive digital transformation through Generative AI, Computer Vision, and NLP solutions.

AI Architecture & MLOps: Design AI-centric data architectures (Vector/Graph databases) and create blueprints for the end-to-end AI lifecycle, from data ingestion to monitoring.

 

Solution Delivery: Translate business requirements into technical AI solutions, defining user stories and acceptance criteria for NLP, CV, and Agentic AI use cases.

 

Technical Implementation: Develop and deploy scalable applications using Docker, Kubernetes, and API frameworks (FastAPI, FASTMCP, REST).

 

Model & Data Management: Design high-dimensional data models (embeddings), fine-tune LLMs/Vision models, and ensure data quality for AI/ML workloads.

 

Governance & Standards: Establish standards for prompt engineering and model fine-tuning while ensuring compliance with security, GDPR, and industry regulations.

 

Collaboration & Innovation: Lead Agile ceremonies, evaluate emerging technologies (LangChain, LlamaIndex, new LLMs), and perform impact analysis for global business needs.

Experience: Bachelor’s degree with 5–8 years in AI architecture or ML development.

 

Core AI/ML: Proficiency in Python, AI/ML algorithms, NLP, Computer Vision, and cloud AI platforms (e.g., Vertex-AI).

 

Generative AI: Expertise in Agentic AI, RAG, MCP tools, and frameworks like LangChain or LlamaIndex.

 

LLM & Fine-tuning: Hands-on experience with LLMs (GPT, Claude, Llama) and fine-tuning models for custom production datasets.

 

Infrastructure: Experience with Docker, Kubernetes, and building robust API frameworks.

 

Data Systems: Proficiency in SQL, NoSQL, Graph, and Vector databases (e.g., BigQuery, Databricks).

 

Process & Soft Skills: Strong Agile knowledge, requirement gathering, and the ability to manage global stakeholders through clear communication and problem-solving.

 

Web Development: Design, develop, test, and maintain Java/J2EE, Angular, Spring Boot, and Postgres/Alloy DB applications following Ford design standards and Test-Driven Development (TDD) practices.

 

Good to Have:

 

Any AI related certifications.

Experience in the Automotive industry and related compliance domains.

Specific exposure to GCP data services (Cloud SQL, Postgres).