Job Description
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 audit‑ready 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.
oftware: React/TypeScript and/or Python/Node/Java; REST/GraphQL; event‑driven 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: Hands‑on 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 awarene
