Architect AWS AI

Position: Architect - AWS and AI

Location: Nagpur/Pune/Chennai

Purpose of the Position: 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:
• LLM development and deployment (GPT 4 class, BERT, T5)
• RAG implementations using FAISS, Elasticsearch, LangChain, or LlamaIndex
• Agentic workflows using frameworks like Ray or RLlib
• 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.