Application Architect

Experience - 8-13 years

Location - Open

We are seeking an experienced Application Architect to lead the design, development, and evolution of large-scale digital products, AI/ML platforms, and enterprise systems. The ideal candidate is a hands-on technologist with strong experience in end-to-end product engineering , solution architecture , AI/ML systems , and cloud-native platforms .

This role requires a technical leader capable of working across UI/UX, middleware, microservices, data engineering, MLOps, and agentic AI ecosystems.

Key Responsibilities

1. Architecture & Technical Leadership

• Design end-to-end enterprise systems spanning UI frameworks, API layers, microservices, middleware, databases, and cloud infrastructure .
• Lead design and development of AI/ML platforms , agentic frameworks , automation workflows , and advanced analytics systems .
• Translate business requirements into scalable, secure, and maintainable technical architectures.
• Make high-impact decisions on system design, technology selection, performance, and fault tolerance.

2. Product Engineering & Development

• Oversee architecture and engineering of complex digital productsweb, mobile, cloud, and data-intensive platforms.
• Guide teams in building highly available systems using Python, FastAPI, Django, Node.js, React, React Native , and related technologies.
• Architect data processing, ETL/ELT, and AI pipelines using Airflow, NiFi, Beam, MLFlow , etc.

3. AI/ML & Agentic Systems

• Design multi-agent systems using LangGraph, AutoGen, CrewAI, Google ADK, MCP, A2A .
• Build GenAI workbenches, guardrail systems, RAG architectures, vector databases, embeddings, and model-driven workflows.
• Integrate LLMs, SLMs, and cloud AI platforms such as AWS Bedrock, Vertex AI, OpenAI, DeepSeek, Llama, Mistral .

4. Cloud Architecture

• Architect scalable systems across AWS, Azure, and GCP leveraging services such as EC2, EKS, S3, RDS, Redshift, Glue, CloudSQL, Spanner, Synapse, ADLS, and more.
• Implement cloud security, monitoring, cost optimization, and distributed application deployments.

5. Stakeholder & Delivery Management

• Collaborate with clients, business teams, and senior leadership to define technical strategies and roadmaps.
• Lead agile delivery, sprint planning, technical reviews, and release management.
• Drive end-to-end execution for platforms supporting large user bases and mission-critical workloads.

6. Team Leadership

• Lead, mentor, and manage large cross-functional teams of developers, data scientists, and engineers.
• Foster best practices in coding, architecture reviews, DevOps, testing, and CI/CD pipelines.

Required Skills & Expertise

Technical Skills

• Architecture & Design: Microservices, distributed systems, event-driven architectures, API design.
• Languages & Frameworks: Python, Node.js, JavaScript, React/Redux, Django, FastAPI, DRF, GraphQL.
• AI Ecosystem: LangChain, LangGraph, LlamaIndex, vLLM, Triton, DeepSpeed, guardrails, vectorDBs (Milvus, Chroma, Faiss).
• ML Ecosystem: Scikit-Learn, PyTorch, TensorFlow, HuggingFace Transformers, MLFlow, ONNX Runtime, HF Tokenizers, BERT/DistilBERT pipelines, model quantization (INT8/FP16), model distillation, pruning.
• Mobile Ecosystem: React Native, Flutter, Native Android, Hybrid App Development.
• Cloud Platforms: AWS, Azure, GCP, Digital Ocean.
• Databases: PostgreSQL, MongoDB, MySQL, Redis, ElasticSearch, Neo4J, GraphDB.
• Data Engineering: Airflow, NiFi, Beam, MLFlow, Airbyte.
• DevOps: CI/CD, containerization, Kubernetes, monitoring, logging frameworks.

Soft Skills

• Excellent stakeholder communication and client management.
• Strong analytical thinking and problem-solving ability.
• Demonstrated leadership in large-scale delivery.
• Ability to drive innovation, transformation, and platform thinking.