Principal Engineer AI, Data & Cloud
- Virtusa
- 10 - 18 years
- Hyderabad
- 21 hours ago
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Job Description
Job Description for Principal Engineer AI, Data & Cloud in Chennai, TN:
Key responsibilities
Technical leadership:
- Define solution and data architectures; set engineering standards; make build/buy/reuse decisions across app, data, and AI components.
Delivery ownership:
- Own roadmap execution from discovery to production; break down work, manage risks/dependencies, and ensure quality, reliability, and cost control.
Software engineering:
- Guide implementation in modern stacks (e.g., React/TypeScript, Python/Node/Java); enforce CI/CD, testing, secure coding, and performance practices.
Cloud engineering:
- Design and operate workloads on AWS (or equivalent) with IaC (Terraform/CloudFormation), networking, security (IAM Roles, least privilege), observability, resilience, and FinOps.
AI engineering:
- Integrate LLM/RAG/agents safely (Bedrock/OpenAI), define guardrails, evaluation, and monitoring; establish LLMOps for reliable updates and traceability.
Data engineering:
- Lead ingestion, transformation, and orchestration (e.g., SnapLogic/Airflow), data modeling, quality (DQ rules), lineage, and SLAs across batch/streaming.
Data Platform integration:
- Leverage and extend the enterprise Data Platform (e.g., Snowflake, governance catalog) for standardized pipelines, access controls, cost optimization, and reuse.
Compliance and security:
- Ensure adherence to AZ standards, privacy, and (where relevant) GxP; automate controls (policy as code, secret detection) with auditready evidence.
Stakeholder management:
- Partner with Product, Arve systems; proven delivery across app, data, and AI components.
Cloud:
- AWS (or similar) VPC, IAM Roles, ECS/EKS/Lambda, S3, API Gateway; IaC; observability (CloudWatch); reliability and cost optimization.
Software:
- React/TypeScript and/or Python/Node/Java; REST/GraphQL; eventdriven patterns; automated testing; performance engineering.
AI:
- LLMs and agent frameworks (RAG, vector stores), prompt/guardrails, evaluation/telemetry; secure integration of foundation models.
Data engineering:
- ETL/ELT design, SQL, data modeling, orchestration, CDC, streaming (Kafka/Kinesis), data quality and lineage.
Data Platform:
- Handson with Snowflake (warehouses, roles, policies, cost controls), governance and catalog tooling.
DevOps:
- CI/CD (GitHub Actions), containers, dependency and secret management.
Security/compliance:
- Identity and access control, least privilege, encryption, and regulated environment awareness
Job Classification
Industry: Financial ServicesFunctional Area / Department: Healthcare & Life SciencesRole Category: Healthcare & Life Sciences - OtherRole: Healthcare & Life Sciences - OtherEmployement Type: Full timeContact Details:
Company: VirtusaLocation(s): Hyderabad+ View Contact
Keyskills: LLM / Generative AI AWS / Cloud Data Engineering
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