Senior DevOps Engineer – AWS, AI Infrastructure

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Software Mind

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1999

🤖 Artificial Intelligence

☁️ SaaS

📡 Telecommunications

💰 Private Equity Round on 2020-12

Artificial Intelligence • SaaS • Telecommunications

Software Mind is a technology company that specializes in software development and digital transformation services. With a focus on AI and cloud solutions, the company offers a wide range of services including custom software development, mobile app development, and cloud consulting. Software Mind serves various industries such as financial services, telecom, biotech, and media, providing tailored solutions to accelerate digital transformations and business growth globally.

📋 Description

• Provision and configure a dedicated VPC and segmented cloud environment on AWS • Build the baseline CI/CD pipeline and maintain and evolve it across all delivery phases • Configure and manage the vector store infrastructure (OpenSearch/Pinecone on AWS) • Set up and manage the observability stack: CloudWatch, X-Ray, alerting thresholds, and LLM-specific monitoring • Implement infrastructure-as-code for all environments (dev, staging, production) using Terraform or CDK • Manage secrets, KMS encryption key configuration, and tenant-scoped access controls • Configure LLM provider connectivity (OpenAI / Anthropic / Amazon Bedrock enterprise tier, zero-data-retention) • Define and implement environment promotion strategy aligned with the 2-week sprint cadence • Support incremental ingestion pipeline infrastructure requirements and nightly scheduling

🎯 Requirements

• 6+ years in DevOps or cloud infrastructure engineering; strong AWS specialisation required • Infrastructure-as-code: Terraform, CloudFormation, or AWS CDK • CI/CD tooling: GitHub Actions, AWS CodePipeline, or equivalent • Core AWS services: VPC, ECS, Lambda, S3, DynamoDB, API Gateway, Cognito, CloudWatch, X-Ray • Experience designing and operating multi-tenant cloud environments with tenant-level data isolation • AI Experience (Required Not Optional) • Experience configuring and managing vector store infrastructure (OpenSearch, Pinecone, Weaviate, or equivalent) in a production environment • Familiarity with LLM provider APIs (OpenAI, Anthropic, or Amazon Bedrock) in a production/enterprise configuration, including zero-data-retention tier setup • Understanding of AI-specific observability concerns: token usage monitoring, latency profiling for LLM calls, and model response logging

🏖️ Benefits

• Excellent work environment certified by Great Place To Work • Professional development opportunities