Associate Data Architect I

9 - 12 Years
1 Opening
Trivandrum

Role Proficiency:

Leverage expertise in a technology area (e.g. Infromatica Transformation Terradata data warehouse Hadoop Analytics) Responsible for Architecture for a small/mid-size projects.

Outcomes:

Measures of Outcomes:

Outputs Expected:

Strategy & Planning:

Operational Management :

Project Control and Review :

Knowledge Management & Capability Development :

Requirement gathering and Analysis:

People Management:

Alliance Management:

Technology Consulting:

Innovation and Thought Leadership:

Project Management Support:

Stakeholder Management:

New Service Design:

Skill Examples:

Knowledge Examples:

• Data visualization
  • Data migration

  • RDMSs (relational database management systems SQL

  • Hadoop technologies like MapReduce Hive and Pig.

  • Programming languages especially Python and Java

  • Operating systems like UNIX and MS Windows.

  • Backup/archival software.
  
  
  Additional Comments:

  AI Architect Role Summary: Hands-on AI Architect with strong expertise in Deep Learning, Generative AI, and real-world AI/ML systems. The role involves leading the architecture, development, and deployment of AI agent-based solutions, supporting initiatives such as intelligent automation, anomaly detection, and GenAI-powered assistants across enterprise operations and engineering. This is a hands-on role ideal for someone who thrives in fast-paced environments, is passionate about AI innovations, and can adapt across multiple opportunities based on business priorities. Key Responsibilities: • Design and architect AI-based solutions including multi-agent GenAI systems using LLMs and RAG pipelines. • Build POCs, prototypes, and production-grade AI components for operations, support automation, and intelligent assistants. • Lead end-to-end development of AI agents for use cases such as triage, RCA automation, and predictive analytics. • Leverage GenAI (LLMs) and Time Series models to drive intelligent observability and performance management. • Work closely with product, engineering, and operations teams to align solutions with domain and customer needs. • Own model lifecycle from experimentation to deployment using modern MLOps and LLMOps practices. • Ensure scalable, secure, and cost-efficient implementation across AWS and Azure cloud environments. • Key Skills & Technology Areas: • AI/ML Expertise: 8+ years in AI/ML, with hands-on experience in deep learning, model deployment, and GenAI. • LLMs & Frameworks: GPT-3+, Claude, LLAMA3, LangChain, LangGraph, Transformers (BERT, T5), RAG pipelines, LLMOps. • Programming: Python (advanced), Keras, PyTorch, Pandas, FastAPI, Celery (for agent orchestration), Redis. • Modeling & Analytics: Time Series Forecasting, Predictive Modeling, Synthetic Data Generation. • Data & Storage: ChromaDB, Pinecone, FAISS, DynamoDB, PostgreSQL, Azure Synapse, Azure Data Factory. • Cloud & Tools: o AWS (Bedrock, SageMaker, Lambda), o Azure (Azure ML, Azure Databricks, Synapse), o GCP (Vertex AI – optional) • Observability Integration: Splunk, ELK Stack, Prometheus. • DevOps/MLOps: Docker, GitHub Actions, Kubernetes, CI/CD pipelines, model monitoring & versioning. • Architectural Patterns: Microservices, Event-Driven Architecture, Multi-Agent Systems, API-first Design. Other Requirements: • Proven ability to work independently and collaboratively in agile, innovation-driven teams. • Strong problem-solving mindset and product-oriented thinking. • Excellent communication and technical storytelling skills. • Flexibility to work across multiple opportunities based on business priorities. • Experience in Telecom, E- Commerce, or Enterprise IT Operations is a plus. ________________________________________ ________________________________________ ________________________________________

python,pandas,AIML,GENAI