Focaloid Technologies - Senior Data Architect - AI/ML System

Description :

Key Responsibilities :

- Architecture & Solution Design

- Architect end?to?end data platforms, AI/ML systems, and GenAI solutions across cloud environments.

- Design scalable data pipelines, lakehouses, warehouses, and real?time processing architectures.

- Define reference architectures, best practices, and reusable frameworks for Data & AI delivery.

- Ensure solutions meet performance, security, governance, and compliance requirements.

Technical Leadership :

- Provide architectural oversight to engineering teams across data engineering, ML, and GenAI projects.

- Review solution designs, code, and deployment pipelines to ensure technical quality.

- Guide teams on modern data stacks, cloud-native patterns, and AI/ML engineering practices.

- Mentor engineers and analysts to strengthen Data & AI capabilities.

Client Engagement & Presales :

- Work with sales and presales to craft solution architectures, proposals, and technical presentations.

- Engage with client architects, product owners, and C's uite stakeholders to understand business needs.

- Translate business challenges into scalable, outcome?driven Data & AI solutions.

- Support estimation, scoping, and technical risk assessment.

Delivery Excellence :

- Oversee implementation of data platforms, ML models, and GenAI workflows.

- Ensure adherence to architectural standards, data quality, and engineering best practices.

- Drive performance optimization, cost efficiency, and reliability across deployed systems.

- Establish CI/CD, MLOps, and LLMOps pipelines for production?grade deployments.

Innovation & Thought Leadership :

- Evaluate emerging technologies across AI/ML, GenAI, LLMOps, and cloud data platforms.

- Build accelerators, reusable components, and architectural blueprints.

- Contribute to internal knowledge sharing, blogs, whitepapers, and tech talks.

Technical Skills & Expertise :

Data Engineering & Analytics :

- Strong expertise in SQL, ETL/ELT, data modeling, and pipeline orchestration.

- Experience with lakehouse and warehouse platforms (Databricks, Snowflake, Redshift, BigQuery).

- Hands?on with PySpark, Python, Scala, and distributed data processing.

AI/ML :

- Experience in feature engineering, model development, evaluation, and optimization.

- Familiarity with ML frameworks : TensorFlow, PyTorch, Scikit?learn, XGBoost, LightGBM.

- Applied ML experience in forecasting, NLP, classification, clustering, and anomaly detection.

GenAI & LLM Ecosystems :

- Experience designing RAG architectures and LLM?powered applications.

- Knowledge of vector databases (Pinecone, Qdrant, FAISS, Chroma).

- Familiarity with multi?agent frameworks (LangGraph, CrewAI, AutoGen).

- Strong understanding of embeddings, prompt engineering, fine?tuning, and document intelligence.

Cloud Platforms :

- Hands?on experience with at least one major cloud :

- Azure : Azure AI, OpenAI, Data Factory, Synapse, Databricks.

- AWS : Bedrock, Glue, Athena, S3, SageMaker.

- GCP : Vertex AI, BigQuery, Dataflow.

MLOps & LLMOps :

- CI/CD for ML and GenAI pipelines.

- Model deployment using Docker, Kubernetes, and serverless patterns.

- Monitoring for drift, accuracy, hallucination checks, and model lifecycle management.

Requirements :

- Bachelors degree in Engineering, Computer Science, or related field.

- 1015 years of experience in Data Engineering, AI/ML, or Cloud Data Architecture.

- Proven experience architecting enterprise's cale data and AI solutions.

- Strong understanding of cloud-native architectures and modern data stacks.

- Experience working with cross?functional teams in a matrix environment.

- Excellent communication and stakeholder engagement skills.

- Ability to translate business needs into robust technical architectures.

- Strong problem's olving mindset with a focus on scalability, security, and performance.