Technical Anchor Ford Credit IT is seeking an AI-Powered Technical Anchor to serve as a hands-on leader and technical authority for cross-functional product teams. This individual will partner closely with Forward Deployed Engineers (Java &

- React), work extensively within Google Cloud Platform (GCP), and leverage modern Generative AI technologies. The ideal candidate will drive key architectural decisions, champion strong software craftsmanship practices—including Test-Driven Development (TDD) and pair programming and mentor fellow engineers. They will also collaborate closely with Leadership, Product teams, Architects, and upstream/downstream application owners to deliver high-impact AI-powered products into production applications. 1.

Technical

Leadership &

- Strategy Be the Technical Authority: Design overall application architecture, code quality, and managing technical debt.

Lead in a Balanced Team: Partner with Product Managers, Product Designers, and business leaders to evaluate feasibility, shape product roadmaps, and translate requirements into actionable user stories.

Set the Engineering Standard: Raise the bar for software craftsmanship by driving practices like Test-Driven Development (TDD), Pair Programming, Continuous Integration/Continuous Delivery (CI/CD), and automated code reviews.

Grow the Team: Coach, mentor, and level up engineers in clean code principles, GCP architecture, and AI-assisted development tools.

- Full-Stack Application Architecture (Java &
- React) Architect Resilient Java Backends: Design and scale secure, high-concurrency microservices using Java 17 (Spring Boot), gRPC, and REST APIs.

Guide Interactive React Frontends: Lead frontend design using React, TypeScript, and contemporary state management to deliver smooth, real-time user experiencesmincluding streaming AI response UI and interactive dashboards.

Standardize AI Tooling:



Establish best practices for AI coding assistants (GitHub Copilot, Claude, Cursor, Gemini Code Assist) to boost velocity without compromising on code security or quality.

- AI Architecture, RAG &
- LLMOps Integration Design Enterprise GenAI Systems: Architect scalable AI capabilities leveraging GCP Vertex AI, foundation models (Gemini, Claude, PaLM), and custom model fine-tuning.

Build RAG Pipelines: Create high-efficiency semantic retrieval systems with GCP Vector Search, Pgvector, or dedicated vector databases, using advanced chunking, reranking, and context caching strategies.

Enable Agentic Workflows: Construct multi-agent orchestrations, tool-execution harnesses, and function-calling workflows with frameworks like LangChain, LlamaIndex, or AutoGen. AI Observability &

- Guardrails: Build telemetry for response latency, cost tracking (token budget management), prompt injection protection, drift/hallucination detection, and fallback systems.
- GCP Infrastructure &
- Cloud Operations Modern Cloud Infrastructure: Drive cloud-native designs using Cloud Run, Google Kubernetes Engine (GKE), Pub/Sub, BigQuery, and Terraform for Infrastructure-as-Code (IaC).

Enterprise

Security &

- Compliance: Enforce robust IAM policies, VPC networking security, data encryption, and AI compliance standards.

DevOps Pipelines: Build and maintain automated CI/CD pipelines to ensure safe, continuous releases across all cloud environments. Core Background 10 years of professional full-stack software development experience,



including at least 2–3 years as a Technical Lead, Software Architect, or Technical Anchor. Proven experience leading engineering teams through complex technical choices and delivering production software.

Technical Skill Set Java Mastery: Deep expertise in Java 17 and frameworks like Spring Boot, Quarkus, or Micronaut. Strong grasp of event-driven design (Kafka, Pub/Sub), REST/gRPC, databases (PostgreSQL, Cloud Spanner/Bigtable), and TDD.

React Mastery: Senior-level proficiency in React, TypeScript, state management (Redux Toolkit, Zustand, React Query), and real-time streaming interfaces (WebSockets, SSE).

Google Cloud Expertise: Hands-on operational experience across core GCP tools (Cloud Run, GKE, IAM, Pub/Sub, Compute Engine) and Vertex AI.

Applied GenAI Knowledge: Hands-on experience architecting RAG pipelines, vector indices, LLM orchestration frameworks, and prompt security/cost management. Nice-to-Haves Certifications: GCP Professional Cloud Architect, GCP Professional ML/Data Engineer, or AIGP (AI Governance). Advanced AI &

- DevOps: Fine-tuning open-source models (Llama, Gemma), OWASP LLM Top 10 security framework, and hands-on container orchestration with Docker, Kubernetes, Helm, and Terraform.

What Success Looks

Like in This Role (KPIs) Architectural Quality &

- Stability: High uptime, zero critical production outages, and low defect rates across both Java and React codebases.

Delivery Velocity: High, predictable sprint velocity powered by automated testing, continuous integration, and AI-assisted workflows. AI System Accuracy &

- Cost Control: Low hallucination rates, optimized response times, and effective token budget management. Team Health &
- Craftsmanship: Strong developer satisfaction, high adoption of team practices (TDD and pairing), and minimal technical debt accumulation.

Experience Level Senior Level

📌 Technical Anchor - AI-Powered Full-Stack Software Architect and Leader (Chennai)
🏢 Ford Motor
📍 Chennai