Full Stack AI Architect

Location: Bengaluru

Job Location:

Chennai, Noida, Bangalore, Hyderabad

Role Summary

We are seeking a Full-Stack AI Architect to design, build, and scale end-to-end AI-driven applications. This role combines software architecture, full-stack engineering, and applied AI/ML system design. The ideal candidate will translate business problems into scalable AI solutions, own the technical blueprint across frontend, backend, data, and AI layers, and guide teams through implementation and productionization.

Key Responsibilities:

AI & System Architecture

- Design end-to-end AI system architectures covering data ingestion, model training/inference, APIs, UI, and deployment
- Select appropriate ML/LLM architectures (classical ML, DL, GenAI, RAG, agents) based on use cases
- Define model lifecycle management (training, versioning, monitoring, retraining)
- Architect scalable, secure, and cost-efficient AI platforms

Backend & API Engineering

- Design and develop high-performance backend services using Python/Java/Node.js
- Build REST/Graph

QL APIs for AI services and enterprise integrations
- Implement authentication, authorization, observability, and fault tolerance
- Optimize latency and throughput for real-time AI inference

Frontend & UX Integration

- Guide development of AI-enabled user interfaces using React, Angular, or Vue
- Enable conversational, analytical, or decision-support experiences
- Ensure explainability and usability of AI outputs for end users

Data Engineering & MLOps

- Design data pipelines using SQL/No

SQL, data lakes, and warehouses
- Implement MLOps pipelines (CI/CD for models, monitoring, drift detection)
- Work with tools such as MLflow, Kubeflow, Airflow, or equivalent
- Ensure data quality, governance, and compliance

Cloud, Dev Ops & Security

- Architect AI workloads on Azure
- Containerize and orchestrate services using Docker and Kubernetes
- Ensure enterprise-grade security, privacy, and compliance (PII, SOC2, GDPR, HIPAA where applicable)
- Optimize cloud costs and system reliability

Technical Leadership

- Act as technical authority across AI and full-stack engineering
- Review designs, mentor engineers, and set coding/architecture standards
- Collaborate with product, data science, and business stakeholders
- Drive POCs, MVPs, and production rollouts

Required Skills &

Qualifications:

Core Technical Skills

- Strong experience in Python (mandatory) and one backend language (Java/Node.js)
- Expertise in ML/DL frameworks (Tensor Flow, PyTorch, scikit-learn)
- Hands-on experience with LLMs, GenAI, RAG, embeddings, vector databases
- Solid knowledge of frontend frameworks (React preferred)
- Strong API design and distributed systems knowledge

Architecture & Platforms

- Experience designing enterprise-scale AI systems
- Cloud-native architecture experience (AWS/Azure/GCP)
- Strong understanding of microservices, event-driven systems, and asynchronous processing

Data & MLOps

- Proficiency in SQL, data modeling, and data pipelines

- Experience with model deployment, monitoring, and lifecycle automation
- Familiarity with feature stores and experiment tracking

Preferred Qualifications

- Experience with AI agents, autonomous workflows, or conversational AI
- Knowledge of Big Query, Snowflake, or enterprise analytics platforms
- Exposure to regulated industries (healthcare, finance, pharma)
- Prior role as Architect, Tech Lead, or Principal Engineer
- Master’s degree in computer science, AI/ML, or related field

Soft Skills

- Strong problem-solving and system-thinking mindset
- Ability to communicate complex AI concepts to non-technical stakeholders
- Leadership, mentoring, and cross-functional collaboration skills
- Product-oriented mindset with focus on business outcomes