Job Description

an AI Engineer with strong techno‑functional depth to drive end‑to‑end delivery across data analytics, AI/ML pipelines, cloud and digital transformation initiatives. This hands‑on role operates at the intersection of business and technology, ensuring high‑quality execution of both client and internal programs. The individual will be responsible for end‑to‑end development of cloud‑native AI and analytics solutions designing scalable architectures, implementing LLM‑driven components, building robust data and ML workflows, and delivering secure, efficient, production‑grade systems on AWS that translate business objectives into actionable, high‑impact technical outcomes.

AI/ML Solution & Platform Engineering

• Design and develop the SQL engine using AWS-native AI/ML services and scalable architectures.
• Build LLM pipelines leveraging Bedrock/SageMaker, including embeddings, fine-tuning, and inference endpoints.
• Develop schema-grounding components (metadata embeddings, similarity scoring, table/column ranking).
• Implement SQL generation guardrails: security policies, sanitization, role-based access, explain-first logic.
• Build automated evaluation frameworks for accuracy, safety, latency, and cost metrics.

Analytics & Business Alignment

• Work with analytics teams to define semantic layers, KPI frameworks, and SQL standards.
• Develop taxonomies, data dictionaries, and metadata required for accurate LLM grounding.
• Ensure all generated SQL adheres to business-approved logic, governance, and KPI definitions.
• Drive adoption of NL-based analytics across business teams, product teams, and analyst communities.

Cloud Delivery & Governance

• Architect secure AWS solutions following best practices for IAM, VPC, KMS, encryption, and network segmentation.
• Implement robust CI/CD and MLOps workflows for continuous deployment and monitoring.

• 5–7 years in AI/ML engineering, analytics engineering, or cloud solution development.
• Experience building LLM-powered applications, preferably Natuaral Language to SQL or semantic search.
• Experience working with data pipelines, BI or data science teams to address business use cases.