Technical Anchor

As a Technical Anchor, you will be a key driver in Ford’s digital evolution, bridging the gap between sophisticated AI technologies and robust full-stack engineering. You will lead a balanced product team to design, develop, and deploy high-quality software using a modern tech stack, including React, Java/Spring Boot, and DialogFlow.

Your role is dual-faceted: you will architect natural, human-like conversational flows leveraging state-of-the-art NLP/LLM frameworks while ensuring the underlying architecture is scalable, secure, and cloud-native. You will champion Software Craftsmanship, mentor team members in Test-Driven Development (TDD) and Pair Programming, and research emerging AI trends to influence enterprise-level technology shifts.

• Technical Leadership: Lead the end-to-end design and implementation of Conversational AI and Full-Stack solutions across web and mobile platforms.
• AI Architecture: Architect complex multi-turn dialogues, manage NLU/LLM frameworks, and oversee the fine-tuning and deployment of AI models.
• Software Craftsmanship: Champion an Agile/XP environment, driving quality through Pair Programming, Test-Driven Development (TDD), and robust CI/CD pipelines.
• Full-Stack Development: Build scalable front-end frameworks (React) and back-end microservices (Java/Spring Boot) integrated with cloud-native platforms.
• Strategic Collaboration: Partner with cross-functional teams to define product requirements, prioritize value-driven deliverables, and research emerging AI trends.

Basic Qualifications:

• Education: B.E. / B.Tech / M.C.A.
• Experience: Minimum 10+ years of hands-on experience in software development and technical leadership.
• Back-End: 4+ years of experience with the Spring Platform (Spring Boot, MVC, Cloud).
• Front-End: 4+ years of experience with React and 3+ years with other frameworks like Angular or GraphQL.
• Cloud/API: 3+ years of experience with Microservices (REST/SOAP) and 2+ years of Cloud-Native development (GCP, AWS, or Azure).

Preferred Qualifications:

• AI/ML Expertise: Proven experience with Large Language Models (LLMs) such as OpenAI, Gemini, or LLaMA, including development and fine-tuning.
• Frameworks: Proficiency with NLP/Deep Learning frameworks like TensorFlow, PyTorch, Hugging Face, or spaCy.
• Conversational Platforms: Experience with DialogFlow, Amazon Lex, or Microsoft Bot Framework.
• Voice Technologies: Familiarity with Speech-to-Text (STT), Text-to-Speech (TTS), and telephony integrations.
• Agile Tools: Expert knowledge of CI/CD tools (GitHub, Jenkins), testing frameworks (JUnit, Selenium), and monitoring tools (Splunk, Dynatrace).
• Certifications: Relevant certifications in Conversational AI, NLP, or Google Cloud AI are a significant plus.