The Senior Data & AI Architect will lead the design and implementation of scalable, secure, and governed AI-driven data platforms on AWS, enabling advanced analytics, AI productivity tools, and next-generation agentic AI systems. This role blends cloud architecture, data engineering, AI system design, DevOps, and governance, with a strong emphasis on enterprise-grade solutions that deliver measurable business value. The architect will act as a technical authority, defining reference architectures, guiding engineering teams, and ensuring best practices across data management, AI workflows, security, and cloud FinOps.

Key Result Areas and Activities :

- Architect and deliver cloud-native AI and data platforms on AWS at enterprise scale.

- Design reusable data ingestion and processing frameworks supporting batch and streaming workloads.

- Lead implementation of agentic AI systems, RAG pipelines, and AI productivity enablers.

- Establish standards for data modeling, governance, quality, security, and FinOps.

- Drive CI/CD and Infrastructure-as-Code (IaC) adoption across data and AI pipelines.

- Mentor engineering teams and review designs, code, and architectural decisions.

- Partner with business stakeholders to translate requirements into scalable technical solutions.

Essential Skills :

- Experience designing and operating AWS based cloud architectures using S3, EC2, EMR, Lambda, and serverless frameworks, with exposure to secure, fault tolerant, and cost optimized designs.

- Proficiency in Python, SQL, PySpark, and Scala, with experience optimizing distributed data processing workloads and implementing testing/validation frameworks.

- Working knowledge of open table formats and data representations such as Delta Lake, Apache Iceberg, Parquet, and JSON, including schema evolution and partitioning strategies.

- Hands on experience with cloud data platforms like Databricks and/or Snowflake, including query optimization and warehouse performance tuning.

- Understanding data modeling, data warehousing, RDBMS, Big Data ecosystems, and building semantic layers for analytics consumption.

- Familiarity with batch, streaming, event driven, and real time data architectures, including Lambda/Kappa models, metadata driven ingestion frameworks, and PII compliant designs.

- Exposure to data governance and cloud cost management, including data cataloging, lineage, quality checks, compliance, and FinOps practices.

- Experience or strong interest in Applied AI systems, including :

1. LLM development and deployment (GPT 4 class, BERT, T5)

2. RAG implementations using FAISS, Elasticsearch, LangChain, or LlamaIndex

3. Agentic workflows using frameworks like Ray or RLlib

4. Prompt engineering, response tuning, and safety guardrails

- Familiarity with modern AI platforms and tooling, such as Snowflake Cortex, Databricks Lakehouse AI / Genie, LangChain, MCP based architectures, Agentcore, and building APIs or services around AI workflows.

- Experience with CI/CD pipelines, Terraform / Infrastructure as Code, Git based workflows, and automated testing for data and AI systems.

Desirable Skills :

- Experience in the Media & Entertainment domain (preferred).

- Working knowledge of BI and analytics tools such as MicroStrategy, Amazon QuickSight, Power BI.

- Exposure to design thinking methodologies for user-centric solution design.

- Understanding front-end design concepts and UI/UX integration.

- Familiarity with Angular based UI integration patterns.

Qualifications :

- Bachelors degree in engineering, or related field.

- Minimum 11+ years of experience across data engineering, cloud platforms, and solution architecture.

- Proven experience leading large-scale data and AI initiatives in enterprise environments.

- Strong stakeholder communication and architectural documentation skills.

Qualities :

- Strategic thinker with strong architectural judgment.

- Excellent communication skills across technical and non-technical audiences.

- Ability to lead and influence without direct authority.

- Strong mentoring mindset and commitment to technical excellence.

- Comfortable operating in fast-paced, multi-location, cross-functional teams.

- Results-driven, ownership-oriented, and continuous learning.

Location : Pune, Maharashtra, India