Job ID: INFIT002
Hiring / Immediate joiners
AI/ML Architect
Locations: Bangalore (On-site)
Employment Type: Full-Time
Experience Required: 8+ Years
Send Resume: [email protected]/7306892755
Job Description – AI/ML Architect (Generative AI & Enterprise AI Platforms)
Role Overview
We are seeking a highly experienced and hands-on AI/ML Architect with 8–10 years of experience in Artificial Intelligence, Machine Learning, Data Science, and Enterprise AI Engineering.
The ideal candidate will lead the design, architecture, and delivery of scalable AI/ML and Generative AI solutions across multiple business domains including retail, e-commerce, travel, customer experience, analytics, operations, automation, and enterprise productivity.
This role requires a strong technical leader who can identify business opportunities for AI adoption, define scalable AI strategies, architect production-grade solutions, mentor engineering teams, and drive AI initiatives from concept to deployment.
The candidate should possess strong expertise in Machine Learning, Generative AI, Agentic AI systems, Vector Search, RAG architectures, Cloud AI platforms, and MLOps best practices.
Key Responsibilities
AI/ML Solution Architecture
- Design and implement scalable AI/ML architectures for enterprise-grade applications.
- Lead end-to-end AI solution development including data pipelines, model development, deployment, monitoring, and optimization.
- Build reusable AI platforms, frameworks, and accelerators for organization-wide adoption.
Generative AI & Agentic AI
- Architect and develop Generative AI applications using Large Language Models (LLMs).
- Design Retrieval-Augmented Generation (RAG) systems using vector databases and semantic search.
- Build AI agent workflows with tool calling, multi-agent orchestration, and MCP-based integrations.
- Develop conversational assistants, coding assistants, automation agents, and enterprise copilots.
Machine Learning Engineering
- Develop and optimize ML models for:
- Recommendation systems
- Demand forecasting
- Price prediction
- Customer segmentation
- Fraud detection
- Predictive analytics
- Search ranking and relevance
- Behavioral analytics
- Optimization systems
Cloud & Platform Engineering
- Lead AI/ML implementations on cloud platforms, preferably Google Cloud Platform (GCP).
- Work with services such as:
- Vertex AI
- BigQuery
- Cloud Run
- GKE
- Pub/Sub
- Dataflow
- Vertex AI Search
- Cloud Storage
- Vector Search
MLOps & Deployment
- Establish MLOps best practices including:
- Model versioning
- Experiment tracking
- Feature engineering pipelines
- Drift detection
- Monitoring and observability
- Automated retraining workflows
- Deploy scalable AI services using:
- FastAPI / Flask
- Docker
- Kubernetes
- REST APIs
- CI/CD pipelines
- Microservices
Leadership & Collaboration
- Lead and mentor AI/ML engineers, data scientists, and backend engineering teams.
- Collaborate with product, business, and leadership stakeholders to translate business problems into AI-driven solutions.
- Evaluate emerging AI technologies and recommend strategic adoption opportunities.
Required Skills & Qualifications
Experience
- 8–10 years of experience in AI/ML, Data Science, AI Engineering, or related domains.
- Proven experience delivering production-grade AI/ML solutions.
Technical Skills
Programming & ML
- Strong proficiency in Python.
- Experience with:
- NumPy
- Pandas
- Polars
- Scikit-learn
- XGBoost
- TensorFlow
- PyTorch
Machine Learning
- Strong understanding of:
- Regression
- Classification
- Clustering
- Recommendation systems
- Forecasting models
- Anomaly detection
- Ranking systems
- Similarity search
- Optimization techniques
Generative AI
- Hands-on experience with:
- LLM applications
- RAG architecture
- Prompt engineering
- Embedding models
- Semantic search
- Hybrid search
- AI agents
- MCP integrations
- Tool calling workflows
AI Frameworks & Platforms
- Experience with:
- LangChain
- LangGraph
- LlamaIndex
- CrewAI
- AutoGen
Vector Databases & Search
- Experience with:
- Pinecone
- Weaviate
- FAISS
- Milvus
- Elasticsearch
- Vertex AI Vector Search
Cloud & Infrastructure
- Strong experience with GCP services and cloud-native architectures.
- Knowledge of:
- Docker
- Kubernetes
- GKE
- Serverless architectures
- Event-driven systems
MLOps
- Experience implementing:
- Model monitoring
- Experiment tracking
- Feature stores
- Model registry
- Logging and observability
- CI/CD for ML systems
Preferred Qualifications
- Experience in retail, e-commerce, finance, analytics, customer service, or enterprise automation domains.
- Experience with:
- Vertex AI Search
- Google Commerce Search
- Dialogflow CX / Google CX Agent
- OR-Tools
- Exposure to enterprise AI governance, scalability, and responsible AI practices.
Expected Outcomes
The AI/ML Architect will be responsible for:
- Defining and driving the organization’s AI strategy and roadmap.
- Delivering scalable and production-ready AI platforms.
- Improving customer experience, personalization, automation, and operational efficiency.
- Enabling enterprise-wide adoption of AI and Generative AI solutions.
- Establishing AI engineering and MLOps best practices across teams.
